diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/BitwiseOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/BitwiseOps.java
index 12d0322041e..830585ab124 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/BitwiseOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/BitwiseOps.java
@@ -62,8 +62,8 @@ public final class BitwiseOps {
    *  </pre>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code BitwiseAnd} output and operands
    * @return a new instance of BitwiseAnd
    */
@@ -92,8 +92,8 @@ public <T extends TNumber> BitwiseAnd<T> bitwiseAnd(Operand<T> x, Operand<T> y)
    *  </pre>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code BitwiseOr} output and operands
    * @return a new instance of BitwiseOr
    */
@@ -122,8 +122,8 @@ public <T extends TNumber> BitwiseOr<T> bitwiseOr(Operand<T> x, Operand<T> y) {
    *  </pre>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code BitwiseXor} output and operands
    * @return a new instance of BitwiseXor
    */
@@ -173,7 +173,7 @@ public <T extends TNumber> BitwiseXor<T> bitwiseXor(Operand<T> x, Operand<T> y)
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Invert} output and operands
    * @return a new instance of Invert
    */
@@ -213,8 +213,8 @@ public <T extends TNumber> Invert<T> invert(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code LeftShift} output and operands
    * @return a new instance of LeftShift
    */
@@ -256,8 +256,8 @@ public <T extends TNumber> LeftShift<T> leftShift(Operand<T> x, Operand<T> y) {
    *  </pre>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RightShift} output and operands
    * @return a new instance of RightShift
    */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java
index 685dda6e2ac..d69c44cc0c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java
@@ -141,8 +141,8 @@ public final class DataOps {
   /**
    * A container for an iterator resource.
    *
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AnonymousIterator
    */
   public AnonymousIterator anonymousIterator(List<Class<? extends TType>> outputTypes,
@@ -153,10 +153,10 @@ public AnonymousIterator anonymousIterator(List<Class<? extends TType>> outputTy
   /**
    * The AssertCardinalityDataset operation
    *
-   * @param inputDataset the inputDataset value
-   * @param cardinality the cardinality value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param cardinality The cardinality value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AssertCardinalityDataset
    */
   public AssertCardinalityDataset assertCardinalityDataset(Operand<? extends TType> inputDataset,
@@ -179,8 +179,8 @@ public AssertCardinalityDataset assertCardinalityDataset(Operand<? extends TType
    *  {@code data.AssertNextDataset} passes through the outputs of its input dataset.
    * @param transformations A {@code tf.string} vector {@code tf.Tensor} identifying the transformations that are
    *  expected to happen next.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AssertNextDataset
    */
   public AssertNextDataset assertNextDataset(Operand<? extends TType> inputDataset,
@@ -201,8 +201,8 @@ public AssertNextDataset assertNextDataset(Operand<? extends TType> inputDataset
    * @param inputDataset A variant tensor representing the input dataset.
    * @param numWorkers A scalar representing the number of workers to distribute this dataset across.
    * @param index A scalar representing the index of the current worker out of num_workers.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of AutoShardDataset
    */
@@ -215,12 +215,12 @@ public AutoShardDataset autoShardDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that batches {@code batch_size} elements from {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param batchSize A scalar representing the number of elements to accumulate in a batch.
    * @param dropRemainder A scalar representing whether the last batch should be dropped in case its size
    *  is smaller than desired.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of BatchDataset
    */
@@ -233,10 +233,10 @@ public BatchDataset batchDataset(Operand<? extends TType> inputDataset, Operand<
   /**
    * Records the bytes size of each element of {@code input_dataset} in a StatsAggregator.
    *
-   * @param inputDataset the inputDataset value
-   * @param tag the tag value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param tag The tag value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of BytesProducedStatsDataset
    */
   public BytesProducedStatsDataset bytesProducedStatsDataset(Operand<? extends TType> inputDataset,
@@ -247,17 +247,17 @@ public BytesProducedStatsDataset bytesProducedStatsDataset(Operand<? extends TTy
   /**
    * The CSVDatasetV2 operation
    *
-   * @param filenames the filenames value
-   * @param compressionType the compressionType value
-   * @param bufferSize the bufferSize value
-   * @param header the header value
-   * @param fieldDelim the fieldDelim value
-   * @param useQuoteDelim the useQuoteDelim value
-   * @param naValue the naValue value
-   * @param selectCols the selectCols value
-   * @param recordDefaults the recordDefaults value
-   * @param excludeCols the excludeCols value
-   * @param outputShapes the value of the outputShapes property
+   * @param filenames The filenames value
+   * @param compressionType The compressionType value
+   * @param bufferSize The bufferSize value
+   * @param header The header value
+   * @param fieldDelim The fieldDelim value
+   * @param useQuoteDelim The useQuoteDelim value
+   * @param naValue The naValue value
+   * @param selectCols The selectCols value
+   * @param recordDefaults The recordDefaults value
+   * @param excludeCols The excludeCols value
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of CSVDataset
    */
   public CSVDataset cSVDataset(Operand<TString> filenames, Operand<TString> compressionType,
@@ -270,11 +270,11 @@ public CSVDataset cSVDataset(Operand<TString> filenames, Operand<TString> compre
   /**
    * The CacheDatasetV2 operation
    *
-   * @param inputDataset the inputDataset value
-   * @param filename the filename value
-   * @param cache the cache value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param filename The filename value
+   * @param cache The cache value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of CacheDataset
    */
   public CacheDataset cacheDataset(Operand<? extends TType> inputDataset, Operand<TString> filename,
@@ -286,15 +286,15 @@ public CacheDataset cacheDataset(Operand<? extends TType> inputDataset, Operand<
   /**
    * The ChooseFastestBranchDataset operation
    *
-   * @param inputDataset the inputDataset value
-   * @param ratioNumerator the ratioNumerator value
-   * @param ratioDenominator the ratioDenominator value
-   * @param otherArguments the otherArguments value
-   * @param numElementsPerBranch the value of the numElementsPerBranch property
-   * @param branches the value of the branches property
-   * @param otherArgumentsLengths the value of the otherArgumentsLengths property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param ratioNumerator The ratioNumerator value
+   * @param ratioDenominator The ratioDenominator value
+   * @param otherArguments The otherArguments value
+   * @param numElementsPerBranch The value of the numElementsPerBranch attribute
+   * @param branches The value of the branches attribute
+   * @param otherArgumentsLengths The value of the otherArgumentsLengths attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ChooseFastestBranchDataset
    */
   public ChooseFastestBranchDataset chooseFastestBranchDataset(
@@ -308,10 +308,10 @@ public ChooseFastestBranchDataset chooseFastestBranchDataset(
   /**
    * The ChooseFastestDataset operation
    *
-   * @param inputDatasets the inputDatasets value
-   * @param numExperiments the value of the numExperiments property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDatasets The inputDatasets value
+   * @param numExperiments The value of the numExperiments attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ChooseFastestDataset
    */
   public ChooseFastestDataset chooseFastestDataset(Iterable<Operand<? extends TType>> inputDatasets,
@@ -322,10 +322,10 @@ public ChooseFastestDataset chooseFastestDataset(Iterable<Operand<? extends TTyp
   /**
    * Creates a dataset that concatenates {@code input_dataset} with {@code another_dataset}.
    *
-   * @param inputDataset the inputDataset value
-   * @param anotherDataset the anotherDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param anotherDataset The anotherDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ConcatenateDataset
    */
   public ConcatenateDataset concatenateDataset(Operand<? extends TType> inputDataset,
@@ -337,17 +337,17 @@ public ConcatenateDataset concatenateDataset(Operand<? extends TType> inputDatas
   /**
    * Creates a dataset that reads data from the tf.data service.
    *
-   * @param datasetId the datasetId value
-   * @param processingMode the processingMode value
-   * @param address the address value
-   * @param protocol the protocol value
-   * @param jobName the jobName value
-   * @param consumerIndex the consumerIndex value
-   * @param numConsumers the numConsumers value
-   * @param maxOutstandingRequests the maxOutstandingRequests value
-   * @param iterationCounter the iterationCounter value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param datasetId The datasetId value
+   * @param processingMode The processingMode value
+   * @param address The address value
+   * @param protocol The protocol value
+   * @param jobName The jobName value
+   * @param consumerIndex The consumerIndex value
+   * @param numConsumers The numConsumers value
+   * @param maxOutstandingRequests The maxOutstandingRequests value
+   * @param iterationCounter The iterationCounter value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of DataServiceDatasetV2
    */
@@ -399,8 +399,8 @@ public DatasetToGraph datasetToGraph(Operand<? extends TType> inputDataset,
    * Outputs the single element from the given dataset.
    *
    * @param dataset A handle to a dataset that contains a single element.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of DatasetToSingleElement
    */
   public DatasetToSingleElement datasetToSingleElement(Operand<? extends TType> dataset,
@@ -443,8 +443,8 @@ public DeleteIterator deleteIterator(Operand<? extends TType> handle,
    * @param rowShape A vector representing the dense shape of each row in the produced
    *  SparseTensor. The shape may be partially specified, using {@code -1} to indicate
    *  that a particular dimension should use the maximum size of all batch elements.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of DenseToSparseBatchDataset
    */
   public DenseToSparseBatchDataset denseToSparseBatchDataset(Operand<? extends TType> inputDataset,
@@ -473,8 +473,8 @@ public DeserializeIterator deserializeIterator(Operand<? extends TType> resource
    *  {@code N} data inputs should produce the next output element.
    * @param dataInputDatasets {@code N} datasets with the same type that will be interleaved according to
    *  the values of {@code selector_input_dataset}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of DirectedInterleaveDataset
    */
@@ -489,9 +489,9 @@ public DirectedInterleaveDataset directedInterleaveDataset(
   /**
    * Creates a dataset containing elements of first component of {@code input_dataset} having true in the last component.
    *
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of FilterByLastComponentDataset
    */
   public FilterByLastComponentDataset filterByLastComponentDataset(
@@ -509,12 +509,12 @@ public FilterByLastComponentDataset filterByLastComponentDataset(
    *  <li>One tensor for each value in {@code other_arguments}.</li>
    *  </ul>
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param otherArguments A list of tensors, typically values that were captured when
    *  building a closure for {@code predicate}.
    * @param predicate A function returning a scalar boolean.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of FilterDataset
    */
   public FilterDataset filterDataset(Operand<? extends TType> inputDataset,
@@ -527,8 +527,8 @@ public FilterDataset filterDataset(Operand<? extends TType> inputDataset,
    * Creates a dataset by applying {@code tf.data.Options} to {@code input_dataset}.
    *
    * @param inputDataset A variant tensor representing the input dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of FinalizeDataset
    */
@@ -541,12 +541,12 @@ public FinalizeDataset finalizeDataset(Operand<? extends TType> inputDataset,
   /**
    * The FixedLengthRecordDatasetV2 operation
    *
-   * @param filenames the filenames value
-   * @param headerBytes the headerBytes value
-   * @param recordBytes the recordBytes value
-   * @param footerBytes the footerBytes value
-   * @param bufferSize the bufferSize value
-   * @param compressionType the compressionType value
+   * @param filenames The filenames value
+   * @param headerBytes The headerBytes value
+   * @param recordBytes The recordBytes value
+   * @param footerBytes The footerBytes value
+   * @param bufferSize The bufferSize value
+   * @param compressionType The compressionType value
    * @return a new instance of FixedLengthRecordDataset
    */
   public FixedLengthRecordDataset fixedLengthRecordDataset(Operand<TString> filenames,
@@ -561,13 +561,13 @@ public FixedLengthRecordDataset fixedLengthRecordDataset(Operand<TString> filena
    *  Dataset variant, and FlatMapDataset will flatten successive results
    *  into a single Dataset.
    *
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    *  {@code other_arguments}, to a Dataset variant that contains elements matching
    *  {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of FlatMapDataset
    */
   public FlatMapDataset flatMapDataset(Operand<? extends TType> inputDataset,
@@ -579,14 +579,14 @@ public FlatMapDataset flatMapDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that invokes a function to generate elements.
    *
-   * @param initFuncOtherArgs the initFuncOtherArgs value
-   * @param nextFuncOtherArgs the nextFuncOtherArgs value
-   * @param finalizeFuncOtherArgs the finalizeFuncOtherArgs value
-   * @param initFunc the value of the initFunc property
-   * @param nextFunc the value of the nextFunc property
-   * @param finalizeFunc the value of the finalizeFunc property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param initFuncOtherArgs The initFuncOtherArgs value
+   * @param nextFuncOtherArgs The nextFuncOtherArgs value
+   * @param finalizeFuncOtherArgs The finalizeFuncOtherArgs value
+   * @param initFunc The value of the initFunc attribute
+   * @param nextFunc The value of the nextFunc attribute
+   * @param finalizeFunc The value of the finalizeFunc attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GeneratorDataset
    */
   public GeneratorDataset generatorDataset(Iterable<Operand<?>> initFuncOtherArgs,
@@ -616,8 +616,8 @@ public GeneratorDataset generatorDataset(Iterable<Operand<?>> initFuncOtherArgs,
    * @param reduceFunc A function mapping the current reducer state and an element of {@code input_dataset},
    *  concatenated with {@code reduce_func_other_arguments} to a new reducer state.
    * @param finalizeFunc A function mapping the final reducer state to an output element.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GroupByReducerDataset
    */
   public GroupByReducerDataset groupByReducerDataset(Operand<? extends TType> inputDataset,
@@ -633,16 +633,16 @@ public GroupByReducerDataset groupByReducerDataset(Operand<? extends TType> inpu
    * Creates a dataset that computes a windowed group-by on {@code input_dataset}.
    *  // TODO(mrry): Support non-int64 keys.
    *
-   * @param inputDataset the inputDataset value
-   * @param keyFuncOtherArguments the keyFuncOtherArguments value
-   * @param reduceFuncOtherArguments the reduceFuncOtherArguments value
-   * @param windowSizeFuncOtherArguments the windowSizeFuncOtherArguments value
+   * @param inputDataset The inputDataset value
+   * @param keyFuncOtherArguments The keyFuncOtherArguments value
+   * @param reduceFuncOtherArguments The reduceFuncOtherArguments value
+   * @param windowSizeFuncOtherArguments The windowSizeFuncOtherArguments value
    * @param keyFunc A function mapping an element of {@code input_dataset}, concatenated
    *  with {@code key_func_other_arguments} to a scalar value of type DT_INT64.
-   * @param reduceFunc the value of the reduceFunc property
-   * @param windowSizeFunc the value of the windowSizeFunc property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param reduceFunc The value of the reduceFunc attribute
+   * @param windowSizeFunc The value of the windowSizeFunc attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GroupByWindowDataset
    */
   public GroupByWindowDataset groupByWindowDataset(Operand<? extends TType> inputDataset,
@@ -656,9 +656,9 @@ public GroupByWindowDataset groupByWindowDataset(Operand<? extends TType> inputD
   /**
    * Creates a dataset that contains the elements of {@code input_dataset} ignoring errors.
    *
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of IgnoreErrorsDataset
    */
@@ -671,8 +671,8 @@ public IgnoreErrorsDataset ignoreErrorsDataset(Operand<? extends TType> inputDat
   /**
    * The InitializeTableFromDataset operation
    *
-   * @param tableHandle the tableHandle value
-   * @param dataset the dataset value
+   * @param tableHandle The tableHandle value
+   * @param dataset The dataset value
    * @return a new instance of InitializeTableFromDataset
    */
   public InitializeTableFromDataset initializeTableFromDataset(Operand<? extends TType> tableHandle,
@@ -688,15 +688,15 @@ public InitializeTableFromDataset initializeTableFromDataset(Operand<? extends T
    *  InterleaveDataset will interleave sequences of up to {@code block_length}
    *  consecutive elements from {@code cycle_length} input elements.
    *
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param cycleLength the cycleLength value
-   * @param blockLength the blockLength value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param cycleLength The cycleLength value
+   * @param blockLength The blockLength value
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    *  {@code other_arguments}, to a Dataset variant that contains elements matching
    *  {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of InterleaveDataset
    */
   public InterleaveDataset interleaveDataset(Operand<? extends TType> inputDataset,
@@ -708,10 +708,10 @@ public InterleaveDataset interleaveDataset(Operand<? extends TType> inputDataset
   /**
    * The IteratorV2 operation
    *
-   * @param sharedName the value of the sharedName property
-   * @param container the value of the container property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param sharedName The value of the sharedName attribute
+   * @param container The value of the container attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of Iterator
    */
   public Iterator iterator(String sharedName, String container,
@@ -722,9 +722,9 @@ public Iterator iterator(String sharedName, String container,
   /**
    * Gets the next output from the given iterator .
    *
-   * @param iterator the iterator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param iterator The iterator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of IteratorGetNext
    */
   public IteratorGetNext iteratorGetNext(Operand<? extends TType> iterator,
@@ -735,9 +735,9 @@ public IteratorGetNext iteratorGetNext(Operand<? extends TType> iterator,
   /**
    * Gets the next output from the given iterator as an Optional variant.
    *
-   * @param iterator the iterator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param iterator The iterator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of IteratorGetNextAsOptional
    */
   public IteratorGetNextAsOptional iteratorGetNextAsOptional(Operand<? extends TType> iterator,
@@ -752,9 +752,9 @@ public IteratorGetNextAsOptional iteratorGetNextAsOptional(Operand<? extends TTy
    *  the calling thread is not a member of the thread pool used to execute parallel
    *  operations (e.g. in eager mode).
    *
-   * @param iterator the iterator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param iterator The iterator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of IteratorGetNextSync
    */
   public IteratorGetNextSync iteratorGetNextSync(Operand<? extends TType> iterator,
@@ -785,8 +785,8 @@ public IteratorToStringHandle iteratorToStringHandle(Operand<? extends TType> re
    *
    * @param filenames A scalar or a vector containing the name(s) of the binary file(s) to be
    *  read.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of LMDBDataset
    */
   public LMDBDataset lMDBDataset(Operand<TString> filenames,
@@ -797,10 +797,10 @@ public LMDBDataset lMDBDataset(Operand<TString> filenames,
   /**
    * Records the latency of producing {@code input_dataset} elements in a StatsAggregator.
    *
-   * @param inputDataset the inputDataset value
-   * @param tag the tag value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param tag The tag value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of LatencyStatsDataset
    */
   public LatencyStatsDataset latencyStatsDataset(Operand<? extends TType> inputDataset,
@@ -817,17 +817,17 @@ public LatencyStatsDataset latencyStatsDataset(Operand<? extends TType> inputDat
    *  allows the training step to proceed so long as some data is available.
    *  <p>!! WARNING !! This dataset is not deterministic!
    *
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param cycleLength the cycleLength value
-   * @param blockLength the blockLength value
-   * @param bufferOutputElements the bufferOutputElements value
-   * @param prefetchInputElements the prefetchInputElements value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param cycleLength The cycleLength value
+   * @param blockLength The blockLength value
+   * @param bufferOutputElements The bufferOutputElements value
+   * @param prefetchInputElements The prefetchInputElements value
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    *  {@code other_arguments}, to a Dataset variant that contains elements matching
    *  {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of LegacyParallelInterleaveDataset
    */
@@ -843,11 +843,11 @@ public LegacyParallelInterleaveDataset legacyParallelInterleaveDataset(
   /**
    * The LoadDataset operation
    *
-   * @param path the path value
-   * @param readerFuncOtherArgs the readerFuncOtherArgs value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
-   * @param readerFunc the value of the readerFunc property
+   * @param path The path value
+   * @param readerFuncOtherArgs The readerFuncOtherArgs value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
+   * @param readerFunc The value of the readerFunc attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadDataset
    */
@@ -862,8 +862,8 @@ public LoadDataset loadDataset(Operand<TString> path, Iterable<Operand<?>> reade
    *  This operation may be executed multiple times. Each execution will reset the
    *  iterator in {@code iterator} to the first element of {@code dataset}.
    *
-   * @param dataset the dataset value
-   * @param iterator the iterator value
+   * @param dataset The dataset value
+   * @param iterator The iterator value
    * @return a new instance of MakeIterator
    */
   public MakeIterator makeIterator(Operand<? extends TType> dataset,
@@ -890,8 +890,8 @@ public MakeIterator makeIterator(Operand<? extends TType> dataset,
    * @param dropRemainder A scalar representing whether the last batch should be dropped in case its size
    *  is smaller than desired.
    * @param f A function to apply to the outputs of {@code input_dataset}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapAndBatchDataset
    */
@@ -906,11 +906,11 @@ public MapAndBatchDataset mapAndBatchDataset(Operand<? extends TType> inputDatas
   /**
    * Creates a dataset that applies {@code f} to the outputs of {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapDataset
    */
@@ -924,7 +924,7 @@ public MapDataset mapDataset(Operand<? extends TType> inputDataset,
   /**
    * The MatchingFilesDataset operation
    *
-   * @param patterns the patterns value
+   * @param patterns The patterns value
    * @return a new instance of MatchingFilesDataset
    */
   public MatchingFilesDataset matchingFilesDataset(Operand<TString> patterns) {
@@ -934,10 +934,10 @@ public MatchingFilesDataset matchingFilesDataset(Operand<TString> patterns) {
   /**
    * Creates a dataset that overrides the maximum intra-op parallelism.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param maxIntraOpParallelism Identifies the maximum intra-op parallelism to use.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of MaxIntraOpParallelismDataset
    */
   public MaxIntraOpParallelismDataset maxIntraOpParallelismDataset(
@@ -951,8 +951,8 @@ public MaxIntraOpParallelismDataset maxIntraOpParallelismDataset(
    *  Identity transformation that models performance.
    *
    * @param inputDataset A variant tensor representing the input dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ModelDataset
    */
@@ -965,9 +965,9 @@ public ModelDataset modelDataset(Operand<? extends TType> inputDataset,
   /**
    * The NonSerializableDataset operation
    *
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of NonSerializableDataset
    */
   public NonSerializableDataset nonSerializableDataset(Operand<? extends TType> inputDataset,
@@ -996,8 +996,8 @@ public NonSerializableDataset nonSerializableDataset(Operand<? extends TType> in
    *
    * @param datasetFactory A function of type {@code () -> DT_VARIANT}, where the returned
    *  DT_VARIANT is a dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of OneShotIterator
    */
@@ -1015,8 +1015,8 @@ public OneShotIterator oneShotIterator(ConcreteFunction datasetFactory,
    * @param optimizationsEnabled A {@code tf.string} vector {@code tf.Tensor} identifying user enabled optimizations.
    * @param optimizationsDisabled A {@code tf.string} vector {@code tf.Tensor} identifying user disabled optimizations.
    * @param optimizationsDefault A {@code tf.string} vector {@code tf.Tensor} identifying optimizations by default.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of OptimizeDataset
    */
@@ -1030,7 +1030,7 @@ public OptimizeDataset optimizeDataset(Operand<? extends TType> inputDataset,
   /**
    * Constructs an Optional variant from a tuple of tensors.
    *
-   * @param components the components value
+   * @param components The components value
    * @return a new instance of OptionalFromValue
    */
   public OptionalFromValue optionalFromValue(Iterable<Operand<?>> components) {
@@ -1040,9 +1040,9 @@ public OptionalFromValue optionalFromValue(Iterable<Operand<?>> components) {
   /**
    * Returns the value stored in an Optional variant or raises an error if none exists.
    *
-   * @param optional the optional value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param optional The optional value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of OptionalGetValue
    */
   public OptionalGetValue optionalGetValue(Operand<? extends TType> optional,
@@ -1053,7 +1053,7 @@ public OptionalGetValue optionalGetValue(Operand<? extends TType> optional,
   /**
    * Returns true if and only if the given Optional variant has a value.
    *
-   * @param optional the optional value
+   * @param optional The optional value
    * @return a new instance of OptionalHasValue
    */
   public OptionalHasValue optionalHasValue(Operand<? extends TType> optional) {
@@ -1074,8 +1074,8 @@ public OptionalNone optionalNone() {
    *
    * @param inputDataset A variant tensor representing the input dataset.
    * @param serializedOptions A {@code tf.string} scalar {@code tf.Tensor} of serialized {@code tf.data.Options} protocol buffer.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of OptionsDataset
    */
   public OptionsDataset optionsDataset(Operand<? extends TType> inputDataset,
@@ -1087,7 +1087,7 @@ public OptionsDataset optionsDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that batches and pads {@code batch_size} elements from the input.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param batchSize A scalar representing the number of elements to accumulate in a
    *  batch.
    * @param paddedShapes A list of int64 tensors representing the desired padded shapes
@@ -1098,7 +1098,7 @@ public OptionsDataset optionsDataset(Operand<? extends TType> inputDataset,
    *  each of the outputs.
    * @param dropRemainder A scalar representing whether the last batch should be dropped in case its size
    *  is smaller than desired.
-   * @param outputShapes the value of the outputShapes property
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of PaddedBatchDataset
    */
@@ -1112,12 +1112,12 @@ public PaddedBatchDataset paddedBatchDataset(Operand<? extends TType> inputDatas
   /**
    * The ParallelBatchDataset operation
    *
-   * @param inputDataset the inputDataset value
-   * @param batchSize the batchSize value
-   * @param numParallelCalls the numParallelCalls value
-   * @param dropRemainder the dropRemainder value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param batchSize The batchSize value
+   * @param numParallelCalls The numParallelCalls value
+   * @param dropRemainder The dropRemainder value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParallelBatchDataset
    */
@@ -1160,8 +1160,8 @@ public ParallelBatchDataset parallelBatchDataset(Operand<? extends TType> inputD
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    *  {@code other_arguments}, to a Dataset variant that contains elements matching
    *  {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParallelInterleaveDataset
    */
@@ -1179,13 +1179,13 @@ public ParallelInterleaveDataset parallelInterleaveDataset(Operand<? extends TTy
    *  Unlike a &quot;MapDataset&quot;, which applies {@code f} sequentially, this dataset invokes up
    *  to {@code num_parallel_calls} copies of {@code f} in parallel.
    *
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
    * @param numParallelCalls The number of concurrent invocations of {@code f} that process
    *  elements from {@code input_dataset} in parallel.
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParallelMapDataset
    */
@@ -1199,8 +1199,8 @@ public ParallelMapDataset parallelMapDataset(Operand<? extends TType> inputDatas
   /**
    * Transforms {@code input_dataset} containing {@code Example} protos as vectors of DT_STRING into a dataset of {@code Tensor} or {@code SparseTensor} objects representing the parsed features.
    *
-   * @param inputDataset the inputDataset value
-   * @param numParallelCalls the numParallelCalls value
+   * @param inputDataset The inputDataset value
+   * @param numParallelCalls The numParallelCalls value
    * @param denseDefaults A dict mapping string keys to {@code Tensor}s.
    *  The keys of the dict must match the dense_keys of the feature.
    * @param sparseKeys A list of string keys in the examples features.
@@ -1221,8 +1221,8 @@ public ParallelMapDataset parallelMapDataset(Operand<? extends TType> inputDatas
    *  given feature along this dimension.
    * @param outputTypes The type list for the return values.
    * @param outputShapes The list of shapes being produced.
-   * @param raggedValueTypes the value of the raggedValueTypes property
-   * @param raggedSplitTypes the value of the raggedSplitTypes property
+   * @param raggedValueTypes The value of the raggedValueTypes attribute
+   * @param raggedSplitTypes The value of the raggedSplitTypes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParseExampleDataset
    */
@@ -1238,11 +1238,11 @@ public ParseExampleDataset parseExampleDataset(Operand<? extends TType> inputDat
   /**
    * Creates a dataset that asynchronously prefetches elements from {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param bufferSize The maximum number of elements to buffer in an iterator over
    *  this dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of PrefetchDataset
    */
@@ -1255,10 +1255,10 @@ public PrefetchDataset prefetchDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that uses a custom thread pool to compute {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param numThreads Identifies the number of threads to use for the private threadpool.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of PrivateThreadPoolDataset
    */
   public PrivateThreadPoolDataset privateThreadPoolDataset(Operand<? extends TType> inputDataset,
@@ -1282,8 +1282,8 @@ public PrivateThreadPoolDataset privateThreadPoolDataset(Operand<? extends TType
    *  seed2 is set to be non-zero, the random number generator is seeded
    *  by the given seed.  Otherwise, a random seed is used.
    * @param seed2 A second scalar seed to avoid seed collision.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RandomDataset
    */
   public RandomDataset randomDataset(Operand<TInt64> seed, Operand<TInt64> seed2,
@@ -1297,8 +1297,8 @@ public RandomDataset randomDataset(Operand<TInt64> seed, Operand<TInt64> seed2,
    * @param start corresponds to start in python's xrange().
    * @param stop corresponds to stop in python's xrange().
    * @param step corresponds to step in python's xrange().
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RangeDataset
    */
   public RangeDataset rangeDataset(Operand<TInt64> start, Operand<TInt64> stop,
@@ -1314,9 +1314,9 @@ public RangeDataset rangeDataset(Operand<TInt64> start, Operand<TInt64> stop,
    * @param inputDataset A variant tensor representing the input dataset.
    * @param batchSizes A vector of integers representing the size of batches to produce. These values
    *  are cycled through in order.
-   * @param dropRemainder the dropRemainder value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param dropRemainder The dropRemainder value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RebatchDatasetV2
    */
   public RebatchDatasetV2 rebatchDatasetV2(Operand<? extends TType> inputDataset,
@@ -1331,12 +1331,12 @@ public RebatchDatasetV2 rebatchDatasetV2(Operand<? extends TType> inputDataset,
    * @param inputDataset A variant tensor representing the input dataset.
    * @param initialState A nested structure of tensors, representing the initial state of the
    *  transformation.
-   * @param otherArguments the otherArguments value
+   * @param otherArguments The otherArguments value
    * @param f A function that maps {@code (old_state, input_element)} to {@code new_state}. It must take
    *  two arguments and return a nested structures of tensors. The structure of
    *  {@code new_state} must match the structure of {@code initial_state}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ReduceDataset
    */
@@ -1350,10 +1350,10 @@ public ReduceDataset reduceDataset(Operand<? extends TType> inputDataset,
   /**
    * Registers a dataset with the tf.data service.
    *
-   * @param dataset the dataset value
-   * @param address the address value
-   * @param protocol the protocol value
-   * @param externalStatePolicy the value of the externalStatePolicy property
+   * @param dataset The dataset value
+   * @param address The address value
+   * @param protocol The protocol value
+   * @param externalStatePolicy The value of the externalStatePolicy attribute
    * @return a new instance of RegisterDataset
    */
   public RegisterDataset registerDataset(Operand<? extends TType> dataset, Operand<TString> address,
@@ -1364,11 +1364,11 @@ public RegisterDataset registerDataset(Operand<? extends TType> dataset, Operand
   /**
    * Creates a dataset that emits the outputs of {@code input_dataset} {@code count} times.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param count A scalar representing the number of times that {@code input_dataset} should
    *  be repeated. A value of {@code -1} indicates that it should be repeated infinitely.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RepeatDataset
    */
   public RepeatDataset repeatDataset(Operand<? extends TType> inputDataset, Operand<TInt64> count,
@@ -1384,13 +1384,13 @@ public RepeatDataset repeatDataset(Operand<? extends TType> inputDataset, Operan
    *  {@code experimental_optimization.filter_with_random_uniform_fusion} option of
    *  {@code tf.data.Options}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param rate A scalar representing the sample rate. Each element of {@code input_dataset} is
    *  retained with this probability, independent of all other elements.
    * @param seed A scalar representing seed of random number generator.
    * @param seed2 A scalar representing seed2 of random number generator.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SamplingDataset
    */
   public SamplingDataset samplingDataset(Operand<? extends TType> inputDataset,
@@ -1402,10 +1402,10 @@ public SamplingDataset samplingDataset(Operand<? extends TType> inputDataset,
   /**
    * The SaveDataset operation
    *
-   * @param inputDataset the inputDataset value
-   * @param path the path value
-   * @param shardFuncOtherArgs the shardFuncOtherArgs value
-   * @param shardFunc the value of the shardFunc property
+   * @param inputDataset The inputDataset value
+   * @param path The path value
+   * @param shardFuncOtherArgs The shardFuncOtherArgs value
+   * @param shardFunc The value of the shardFunc attribute
    * @param options carries optional attribute values
    * @return a new instance of SaveDataset
    */
@@ -1418,12 +1418,12 @@ public SaveDataset saveDataset(Operand<? extends TType> inputDataset, Operand<TS
   /**
    * Creates a dataset successively reduces {@code f} over the elements of {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
-   * @param initialState the initialState value
-   * @param otherArguments the otherArguments value
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param initialState The initialState value
+   * @param otherArguments The otherArguments value
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ScanDataset
    */
@@ -1449,12 +1449,12 @@ public SerializeIterator serializeIterator(Operand<? extends TType> resourceHand
   /**
    * The SetStatsAggregatorDataset operation
    *
-   * @param inputDataset the inputDataset value
-   * @param statsAggregator the statsAggregator value
-   * @param tag the tag value
-   * @param counterPrefix the counterPrefix value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param statsAggregator The statsAggregator value
+   * @param tag The tag value
+   * @param counterPrefix The counterPrefix value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SetStatsAggregatorDataset
    */
   public SetStatsAggregatorDataset setStatsAggregatorDataset(Operand<? extends TType> inputDataset,
@@ -1467,11 +1467,11 @@ public SetStatsAggregatorDataset setStatsAggregatorDataset(Operand<? extends TTy
   /**
    * Creates a {@code Dataset} that includes only 1/{@code num_shards} of this dataset.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param numShards An integer representing the number of shards operating in parallel.
    * @param index An integer representing the current worker index.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ShardDataset
    */
@@ -1484,14 +1484,14 @@ public ShardDataset shardDataset(Operand<? extends TType> inputDataset, Operand<
   /**
    * The ShuffleAndRepeatDatasetV2 operation
    *
-   * @param inputDataset the inputDataset value
-   * @param bufferSize the bufferSize value
-   * @param seed the seed value
-   * @param seed2 the seed2 value
-   * @param count the count value
-   * @param seedGenerator the seedGenerator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param bufferSize The bufferSize value
+   * @param seed The seed value
+   * @param seed2 The seed2 value
+   * @param count The count value
+   * @param seedGenerator The seedGenerator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ShuffleAndRepeatDataset
    */
@@ -1506,13 +1506,13 @@ public ShuffleAndRepeatDataset shuffleAndRepeatDataset(Operand<? extends TType>
   /**
    * The ShuffleDatasetV3 operation
    *
-   * @param inputDataset the inputDataset value
-   * @param bufferSize the bufferSize value
-   * @param seed the seed value
-   * @param seed2 the seed2 value
-   * @param seedGenerator the seedGenerator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param bufferSize The bufferSize value
+   * @param seed The seed value
+   * @param seed2 The seed2 value
+   * @param seedGenerator The seedGenerator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ShuffleDataset
    */
@@ -1526,11 +1526,11 @@ public ShuffleDataset shuffleDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that skips {@code count} elements from the {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param count A scalar representing the number of elements from the {@code input_dataset}
    *  that should be skipped.  If count is -1, skips everything.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SkipDataset
    */
   public SkipDataset skipDataset(Operand<? extends TType> inputDataset, Operand<TInt64> count,
@@ -1541,10 +1541,10 @@ public SkipDataset skipDataset(Operand<? extends TType> inputDataset, Operand<TI
   /**
    * The SleepDataset operation
    *
-   * @param inputDataset the inputDataset value
-   * @param sleepMicroseconds the sleepMicroseconds value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param sleepMicroseconds The sleepMicroseconds value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SleepDataset
    */
   public SleepDataset sleepDataset(Operand<? extends TType> inputDataset,
@@ -1556,15 +1556,15 @@ public SleepDataset sleepDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that passes a sliding window over {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param windowSize A scalar representing the number of elements in the
    *  sliding window.
    * @param windowShift A scalar representing the steps moving the sliding window
    *  forward in one iteration. It must be positive.
    * @param windowStride A scalar representing the stride of the input elements of the sliding window.
    *  It must be positive.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SlidingWindowDataset
    */
   public SlidingWindowDataset slidingWindowDataset(Operand<? extends TType> inputDataset,
@@ -1582,10 +1582,10 @@ public SlidingWindowDataset slidingWindowDataset(Operand<? extends TType> inputD
    *
    * @param inputDataset A variant tensor representing the input dataset.
    * @param path The path we should write snapshots to / read snapshots from.
-   * @param readerFuncOtherArgs the readerFuncOtherArgs value
-   * @param shardFuncOtherArgs the shardFuncOtherArgs value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param readerFuncOtherArgs The readerFuncOtherArgs value
+   * @param shardFuncOtherArgs The shardFuncOtherArgs value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param readerFunc Optional. A function to control how to read data from snapshot shards.
    * @param shardFunc Optional. A function to control how to shard data when writing a snapshot.
    * @param options carries optional attribute values
@@ -1602,9 +1602,9 @@ public SnapshotDataset snapshotDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that splits a SparseTensor into elements row-wise.
    *
-   * @param indices the indices value
-   * @param values the values value
-   * @param denseShape the denseShape value
+   * @param indices The indices value
+   * @param values The values value
+   * @param denseShape The denseShape value
    * @return a new instance of SparseTensorSliceDataset
    */
   public SparseTensorSliceDataset sparseTensorSliceDataset(Operand<TInt64> indices,
@@ -1618,8 +1618,8 @@ public SparseTensorSliceDataset sparseTensorSliceDataset(Operand<TInt64> indices
    * @param driverName The database type. Currently, the only supported type is 'sqlite'.
    * @param dataSourceName A connection string to connect to the database.
    * @param query A SQL query to execute.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SqlDataset
    */
   public SqlDataset sqlDataset(Operand<TString> driverName, Operand<TString> dataSourceName,
@@ -1630,12 +1630,12 @@ public SqlDataset sqlDataset(Operand<TString> driverName, Operand<TString> dataS
   /**
    * Creates a dataset that contains {@code count} elements from the {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param count A scalar representing the number of elements from the {@code input_dataset}
    *  that should be taken. A value of {@code -1} indicates that all of {@code input_dataset}
    *  is taken.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TakeDataset
    */
   public TakeDataset takeDataset(Operand<? extends TType> inputDataset, Operand<TInt64> count,
@@ -1652,12 +1652,12 @@ public TakeDataset takeDataset(Operand<? extends TType> inputDataset, Operand<TI
    *  <li>One tensor for each value in {@code other_arguments}.</li>
    *  </ul>
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param otherArguments A list of tensors, typically values that were captured when
    *  building a closure for {@code predicate}.
    * @param predicate A function returning a scalar boolean.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TakeWhileDataset
    */
   public TakeWhileDataset takeWhileDataset(Operand<? extends TType> inputDataset,
@@ -1669,8 +1669,8 @@ public TakeWhileDataset takeWhileDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that emits {@code components} as a tuple of tensors once.
    *
-   * @param components the components value
-   * @param outputShapes the value of the outputShapes property
+   * @param components The components value
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TensorDataset
    */
   public TensorDataset tensorDataset(Iterable<Operand<?>> components, List<Shape> outputShapes) {
@@ -1680,8 +1680,8 @@ public TensorDataset tensorDataset(Iterable<Operand<?>> components, List<Shape>
   /**
    * Creates a dataset that emits each dim-0 slice of {@code components} once.
    *
-   * @param components the components value
-   * @param outputShapes the value of the outputShapes property
+   * @param components The components value
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TensorSliceDataset
    */
   public TensorSliceDataset tensorSliceDataset(Iterable<Operand<?>> components,
@@ -1723,10 +1723,10 @@ public TfRecordDataset tfRecordDataset(Operand<TString> filenames,
   /**
    * Creates a dataset that uses a custom thread pool to compute {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param threadPool A resource produced by the ThreadPoolHandle op.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ThreadPoolDataset
    */
   public ThreadPoolDataset threadPoolDataset(Operand<? extends TType> inputDataset,
@@ -1738,9 +1738,9 @@ public ThreadPoolDataset threadPoolDataset(Operand<? extends TType> inputDataset
   /**
    * A dataset that splits the elements of its input into multiple elements.
    *
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of UnbatchDataset
    */
   public UnbatchDataset unbatchDataset(Operand<? extends TType> inputDataset,
@@ -1751,9 +1751,9 @@ public UnbatchDataset unbatchDataset(Operand<? extends TType> inputDataset,
   /**
    * Creates a dataset that contains the unique elements of {@code input_dataset}.
    *
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of UniqueDataset
    */
   public UniqueDataset uniqueDataset(Operand<? extends TType> inputDataset,
@@ -1764,7 +1764,7 @@ public UniqueDataset uniqueDataset(Operand<? extends TType> inputDataset,
   /**
    * The UnwrapDatasetVariant operation
    *
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of UnwrapDatasetVariant
    */
   public UnwrapDatasetVariant unwrapDatasetVariant(Operand<? extends TType> inputHandle) {
@@ -1809,7 +1809,7 @@ public UnwrapDatasetVariant unwrapDatasetVariant(Operand<? extends TType> inputH
    *  produces {@code {{"a": {0, 1}}, {"a": {2, 3}}}}</li>
    *  </ul>
    *
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param sizeOutput An integer scalar, representing the number of elements
    *  of the input dataset to combine into a window. Must be positive.
    * @param shift An integer scalar, representing the number of input elements
@@ -1820,8 +1820,8 @@ public UnwrapDatasetVariant unwrapDatasetVariant(Operand<? extends TType> inputH
    *  &quot;retain every input element&quot;.
    * @param dropRemainder A Boolean scalar, representing whether the last window should be
    *  dropped if its size is smaller than {@code window_size}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of WindowDataset
    */
   public WindowDataset windowDataset(Operand<? extends TType> inputDataset,
@@ -1834,7 +1834,7 @@ public WindowDataset windowDataset(Operand<? extends TType> inputDataset,
   /**
    * The WrapDatasetVariant operation
    *
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of WrapDatasetVariant
    */
   public WrapDatasetVariant wrapDatasetVariant(Operand<? extends TType> inputHandle) {
@@ -1849,8 +1849,8 @@ public WrapDatasetVariant wrapDatasetVariant(Operand<? extends TType> inputHandl
    *  dataset, and no error will be raised if input datasets have different sizes.
    *
    * @param inputDatasets List of {@code N} variant Tensors representing datasets to be zipped together.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ZipDataset
    */
   public ZipDataset zipDataset(Iterable<Operand<? extends TType>> inputDatasets,
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java
index 8fa99de450d..1c51c2cd404 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java
@@ -57,7 +57,7 @@ public final class DtypesOps {
    *  </blockquote>
    *  </blockquote>
    *
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @return a new instance of AsString
    */
@@ -69,8 +69,8 @@ public AsString asString(Operand<? extends TType> input, AsString.Options... opt
    * Cast x of type SrcT to y of DstT.
    *
    * @param <U> data type for {@code y} output
-   * @param x the x value
-   * @param DstT the value of the DstT property
+   * @param x The x value
+   * @param DstT The value of the DstT attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code Cast} output and operands
    * @return a new instance of Cast
@@ -95,9 +95,9 @@ public <U extends TType> Cast<U> cast(Operand<? extends TType> x, Class<U> DstT,
    *  </pre>
    *
    * @param <U> data type for {@code out} output
-   * @param real the real value
-   * @param imag the imag value
-   * @param Tout the value of the Tout property
+   * @param real The real value
+   * @param imag The imag value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Complex} output and operands
    * @param <T> data type for {@code Complex} output and operands
    * @return a new instance of Complex
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java
index 94bfe32ace0..e2c10f35c6d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java
@@ -254,7 +254,7 @@ public CropAndResizeGradBoxes cropAndResizeGradBoxes(Operand<TFloat32> grads,
    * @param imageSize A 1-D tensor with value {@code [batch, image_height, image_width, depth]}
    *  containing the original image size. Both {@code image_height} and {@code image_width} need
    *  to be positive.
-   * @param T the value of the T property
+   * @param T The value of the T attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CropAndResizeGradImage} output and operands
    * @return a new instance of CropAndResizeGradImage
@@ -456,7 +456,7 @@ public DecodePng<TUint8> decodePng(Operand<TString> contents, DecodePng.Options[
    *
    * @param <T> data type for {@code image} output
    * @param contents 0-D.  The PNG-encoded image.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DecodePng} output and operands
    * @return a new instance of DecodePng
@@ -710,8 +710,8 @@ public NonMaxSuppressionWithOverlaps nonMaxSuppressionWithOverlaps(Operand<TFloa
    * @param images 4-D with shape {@code [batch, height, width, channels]}.
    * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
    *  new size for the images.
-   * @param min the min value
-   * @param max the max value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizedResizeBilinear} output and operands
    * @return a new instance of QuantizedResizeBilinear
@@ -901,10 +901,10 @@ public <T extends TNumber> SampleDistortedBoundingBox<T> sampleDistortedBounding
   /**
    * The ScaleAndTranslate operation
    *
-   * @param images the images value
-   * @param sizeOutput the sizeOutput value
-   * @param scale the scale value
-   * @param translation the translation value
+   * @param images The images value
+   * @param sizeOutput The sizeOutput value
+   * @param scale The scale value
+   * @param translation The translation value
    * @param options carries optional attribute values
    * @return a new instance of ScaleAndTranslate
    */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java
index 889c234eff1..b31ae7663b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java
@@ -161,7 +161,7 @@ public DecodeJsonExample decodeJsonExample(Operand<TString> jsonExamples) {
    * @param inputBytes Tensor of string to be decoded.
    * @param fixedLength Length in bytes for each element of the decoded output. Must be a multiple
    *  of the size of the output type.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DecodePaddedRaw} output and operands
    * @return a new instance of DecodePaddedRaw
@@ -176,7 +176,7 @@ public <T extends TNumber> DecodePaddedRaw<T> decodePaddedRaw(Operand<TString> i
    *
    * @param <T> data type for {@code output} output
    * @param bytes All the elements must have the same length.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DecodeRaw} output and operands
    * @return a new instance of DecodeRaw
@@ -430,7 +430,7 @@ public ParseExample parseExample(Operand<TString> serialized, Operand<TString> n
    *  DT_INT64 (Int64List), and DT_STRING (BytesList).
    * @param contextRaggedValueTypes RaggedTensor.value dtypes for the ragged context features.
    * @param contextRaggedSplitTypes RaggedTensor.row_split dtypes for the ragged context features.
-   * @param featureListDenseTypes the value of the featureListDenseTypes property
+   * @param featureListDenseTypes The value of the featureListDenseTypes attribute
    * @param featureListSparseTypes A list of Nfeature_list_sparse types; the data types
    *  of data in each FeatureList given in feature_list_sparse_keys.
    *  Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
@@ -534,7 +534,7 @@ public ParseSingleExample parseSingleExample(Operand<TString> serialized,
    *  each context Feature given in context_sparse_keys.
    *  Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
    *  DT_INT64 (Int64List), and DT_STRING (BytesList).
-   * @param featureListDenseTypes the value of the featureListDenseTypes property
+   * @param featureListDenseTypes The value of the featureListDenseTypes attribute
    * @param featureListSparseTypes A list of Nfeature_list_sparse types; the data types
    *  of data in each FeatureList given in feature_list_sparse_keys.
    *  Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
@@ -751,7 +751,7 @@ public RandomShuffleQueue randomShuffleQueue(List<Class<? extends TType>> compon
   /**
    * Reads and outputs the entire contents of the input filename.
    *
-   * @param filename the filename value
+   * @param filename The filename value
    * @return a new instance of ReadFile
    */
   public ReadFile readFile(Operand<TString> filename) {
@@ -938,9 +938,9 @@ public SerializeTensor serializeTensor(Operand<? extends TType> tensor) {
    * Generate a sharded filename. The filename is printf formatted as
    *  %s-%05d-of-%05d, basename, shard, num_shards.
    *
-   * @param basename the basename value
-   * @param shard the shard value
-   * @param numShards the numShards value
+   * @param basename The basename value
+   * @param shard The shard value
+   * @param numShards The numShards value
    * @return a new instance of ShardedFilename
    */
   public ShardedFilename shardedFilename(Operand<TString> basename, Operand<TInt32> shard,
@@ -951,8 +951,8 @@ public ShardedFilename shardedFilename(Operand<TString> basename, Operand<TInt32
   /**
    * Generate a glob pattern matching all sharded file names.
    *
-   * @param basename the basename value
-   * @param numShards the numShards value
+   * @param basename The basename value
+   * @param numShards The numShards value
    * @return a new instance of ShardedFilespec
    */
   public ShardedFilespec shardedFilespec(Operand<TString> basename, Operand<TInt32> numShards) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java
index 192973c6a32..2d0c1482b6c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java
@@ -135,7 +135,7 @@ public <T extends TType, U extends TNumber> BandPart<T> bandPart(Operand<T> inpu
    * The BatchCholesky operation
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code BatchCholesky} output and operands
    * @return a new instance of BatchCholesky
    */
@@ -147,8 +147,8 @@ public <T extends TNumber> BatchCholesky<T> batchCholesky(Operand<T> input) {
    * The BatchCholeskyGrad operation
    *
    * @param <T> data type for {@code output} output
-   * @param l the l value
-   * @param grad the grad value
+   * @param l The l value
+   * @param grad The grad value
    * @param <T> data type for {@code BatchCholeskyGrad} output and operands
    * @return a new instance of BatchCholeskyGrad
    */
@@ -160,9 +160,9 @@ public <T extends TNumber> BatchCholeskyGrad<T> batchCholeskyGrad(Operand<T> l,
    * The BatchMatrixBandPart operation
    *
    * @param <T> data type for {@code band} output
-   * @param input the input value
-   * @param numLower the numLower value
-   * @param numUpper the numUpper value
+   * @param input The input value
+   * @param numLower The numLower value
+   * @param numUpper The numUpper value
    * @param <T> data type for {@code BatchMatrixBandPart} output and operands
    * @return a new instance of BatchMatrixBandPart
    */
@@ -175,7 +175,7 @@ public <T extends TType> BatchMatrixBandPart<T> batchMatrixBandPart(Operand<T> i
    * The BatchMatrixDeterminant operation
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code BatchMatrixDeterminant} output and operands
    * @return a new instance of BatchMatrixDeterminant
    */
@@ -187,7 +187,7 @@ public <T extends TType> BatchMatrixDeterminant<T> batchMatrixDeterminant(Operan
    * The BatchMatrixDiag operation
    *
    * @param <T> data type for {@code output} output
-   * @param diagonal the diagonal value
+   * @param diagonal The diagonal value
    * @param <T> data type for {@code BatchMatrixDiag} output and operands
    * @return a new instance of BatchMatrixDiag
    */
@@ -199,7 +199,7 @@ public <T extends TType> BatchMatrixDiag<T> batchMatrixDiag(Operand<T> diagonal)
    * The BatchMatrixDiagPart operation
    *
    * @param <T> data type for {@code diagonal} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code BatchMatrixDiagPart} output and operands
    * @return a new instance of BatchMatrixDiagPart
    */
@@ -211,7 +211,7 @@ public <T extends TType> BatchMatrixDiagPart<T> batchMatrixDiagPart(Operand<T> i
    * The BatchMatrixInverse operation
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixInverse} output and operands
    * @return a new instance of BatchMatrixInverse
@@ -225,8 +225,8 @@ public <T extends TNumber> BatchMatrixInverse<T> batchMatrixInverse(Operand<T> i
    * The BatchMatrixSetDiag operation
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param diagonal the diagonal value
+   * @param input The input value
+   * @param diagonal The diagonal value
    * @param <T> data type for {@code BatchMatrixSetDiag} output and operands
    * @return a new instance of BatchMatrixSetDiag
    */
@@ -239,8 +239,8 @@ public <T extends TType> BatchMatrixSetDiag<T> batchMatrixSetDiag(Operand<T> inp
    * The BatchMatrixSolve operation
    *
    * @param <T> data type for {@code output} output
-   * @param matrix the matrix value
-   * @param rhs the rhs value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixSolve} output and operands
    * @return a new instance of BatchMatrixSolve
@@ -254,9 +254,9 @@ public <T extends TNumber> BatchMatrixSolve<T> batchMatrixSolve(Operand<T> matri
    * The BatchMatrixSolveLs operation
    *
    * @param <T> data type for {@code output} output
-   * @param matrix the matrix value
-   * @param rhs the rhs value
-   * @param l2Regularizer the l2Regularizer value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
+   * @param l2Regularizer The l2Regularizer value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixSolveLs} output and operands
    * @return a new instance of BatchMatrixSolveLs
@@ -270,8 +270,8 @@ public <T extends TNumber> BatchMatrixSolveLs<T> batchMatrixSolveLs(Operand<T> m
    * The BatchMatrixTriangularSolve operation
    *
    * @param <T> data type for {@code output} output
-   * @param matrix the matrix value
-   * @param rhs the rhs value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixTriangularSolve} output and operands
    * @return a new instance of BatchMatrixTriangularSolve
@@ -285,7 +285,7 @@ public <T extends TNumber> BatchMatrixTriangularSolve<T> batchMatrixTriangularSo
    * The BatchSelfAdjointEigV2 operation
    *
    * @param <T> data type for {@code e} output
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchSelfAdjointEigV2} output and operands
    * @return a new instance of BatchSelfAdjointEig
@@ -299,7 +299,7 @@ public <T extends TNumber> BatchSelfAdjointEig<T> batchSelfAdjointEig(Operand<T>
    * The BatchSvd operation
    *
    * @param <T> data type for {@code s} output
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchSvd} output and operands
    * @return a new instance of BatchSvd
@@ -356,8 +356,8 @@ public <T extends TNumber> CholeskyGrad<T> choleskyGrad(Operand<T> l, Operand<T>
    *  {@code y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])}
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
-   * @param perm the perm value
+   * @param x The x value
+   * @param perm The perm value
    * @param <T> data type for {@code ConjugateTranspose} output and operands
    * @return a new instance of ConjugateTranspose
    */
@@ -412,7 +412,7 @@ public <T extends TType> Det<T> det(Operand<T> input) {
    *
    * @param <U> data type for {@code e} output
    * @param input {@code Tensor} input of shape {@code [N, N]}.
-   * @param Tout the value of the Tout property
+   * @param Tout The value of the Tout attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code Eig} output and operands
    * @return a new instance of Eig
@@ -662,7 +662,7 @@ public <T extends TType> Lu<T, TInt32> lu(Operand<T> input) {
    * @param <U> data type for {@code p} output
    * @param input A tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions form matrices of
    *  size {@code [M, M]}.
-   * @param outputIdxType the value of the outputIdxType property
+   * @param outputIdxType The value of the outputIdxType attribute
    * @param <T> data type for {@code Lu} output and operands
    * @param <U> data type for {@code Lu} output and operands
    * @return a new instance of Lu
@@ -682,8 +682,8 @@ public <T extends TType, U extends TNumber> Lu<T, U> lu(Operand<T> input,
    *  cublas.
    *
    * @param <T> data type for {@code product} output
-   * @param a the a value
-   * @param b the b value
+   * @param a The a value
+   * @param b The b value
    * @param options carries optional attribute values
    * @param <T> data type for {@code MatMul} output and operands
    * @return a new instance of MatMul
@@ -1326,7 +1326,7 @@ public <T extends TType> Qr<T> qr(Operand<T> input, Qr.Options... options) {
    * @param maxA The float value that the highest quantized {@code a} value represents.
    * @param minB The float value that the lowest quantized {@code b} value represents.
    * @param maxB The float value that the highest quantized {@code b} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param Tactivation The type of output produced by activation function
    *  following this operation.
    * @param options carries optional attribute values
@@ -1491,8 +1491,8 @@ public <T extends TType> TensorDiagPart<T> tensorDiagPart(Operand<T> input) {
    *  {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]}
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
-   * @param perm the perm value
+   * @param x The x value
+   * @param perm The perm value
    * @param <T> data type for {@code Transpose} output and operands
    * @return a new instance of Transpose
    */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java
index 5f76519403f..d0e1f2ca7f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java
@@ -150,7 +150,7 @@ public final class MathOps {
    *  an output element, this operation computes \(y = |x|\).
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Abs} output and operands
    * @return a new instance of Abs
    */
@@ -183,7 +183,7 @@ public <T extends TType> AccumulateN<T> accumulateN(Iterable<Operand<T>> inputs,
    *  <p>Input range is {@code [-1, 1]} and the output has a range of {@code [0, pi]}.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Acos} output and operands
    * @return a new instance of Acos
    */
@@ -201,7 +201,7 @@ public <T extends TType> Acos<T> acos(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Acosh} output and operands
    * @return a new instance of Acosh
    */
@@ -217,8 +217,8 @@ public <T extends TType> Acosh<T> acosh(Operand<T> x) {
    *  <p>Both input and output have a range {@code (-inf, inf)}.
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Add} output and operands
    * @return a new instance of Add
    */
@@ -235,7 +235,7 @@ public <T extends TType> Add<T> add(Operand<T> x, Operand<T> y) {
    *  </pre>
    *
    * @param <T> data type for {@code sum} output
-   * @param inputs the inputs value
+   * @param inputs The inputs value
    * @param <T> data type for {@code AddN} output and operands
    * @return a new instance of AddN
    */
@@ -260,7 +260,7 @@ public <T extends TType> AddN<T> addN(Iterable<Operand<T>> inputs) {
    *  <br>{@literal @}end_compatibility
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Angle, with default output types
    */
   public Angle<TFloat32> angle(Operand<? extends TType> input) {
@@ -284,8 +284,8 @@ public Angle<TFloat32> angle(Operand<? extends TType> input) {
    *  <br>{@literal @}end_compatibility
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Angle} output and operands
    * @return a new instance of Angle
    */
@@ -296,8 +296,8 @@ public <U extends TNumber> Angle<U> angle(Operand<? extends TType> input, Class<
   /**
    * Returns the truth value of abs(x-y) &lt; tolerance element-wise.
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param options carries optional attribute values
    * @param <T> data type for {@code ApproximateEqual} output and operands
    * @return a new instance of ApproximateEqual
@@ -321,7 +321,7 @@ public <T extends TType> ApproximateEqual approximateEqual(Operand<T> x, Operand
    *  </pre>
    *
    * @param <V> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    *  Describes which dimension of the input Tensor to reduce across. For vectors,
    *  use dimension = 0.
@@ -346,11 +346,11 @@ public ArgMax<TInt64> argMax(Operand<? extends TType> input,
    *  </pre>
    *
    * @param <V> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    *  Describes which dimension of the input Tensor to reduce across. For vectors,
    *  use dimension = 0.
-   * @param outputType the value of the outputType property
+   * @param outputType The value of the outputType attribute
    * @param <V> data type for {@code ArgMax} output and operands
    * @return a new instance of ArgMax
    */
@@ -373,7 +373,7 @@ public <V extends TNumber> ArgMax<V> argMax(Operand<? extends TType> input,
    *  </pre>
    *
    * @param <V> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    *  Describes which dimension of the input Tensor to reduce across. For vectors,
    *  use dimension = 0.
@@ -398,11 +398,11 @@ public ArgMin<TInt64> argMin(Operand<? extends TType> input,
    *  </pre>
    *
    * @param <V> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    *  Describes which dimension of the input Tensor to reduce across. For vectors,
    *  use dimension = 0.
-   * @param outputType the value of the outputType property
+   * @param outputType The value of the outputType attribute
    * @param <V> data type for {@code ArgMin} output and operands
    * @return a new instance of ArgMin
    */
@@ -427,7 +427,7 @@ public <V extends TNumber> ArgMin<V> argMin(Operand<? extends TType> input,
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Asin} output and operands
    * @return a new instance of Asin
    */
@@ -446,7 +446,7 @@ public <T extends TType> Asin<T> asin(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Asinh} output and operands
    * @return a new instance of Asinh
    */
@@ -470,7 +470,7 @@ public <T extends TType> Asinh<T> asinh(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Atan} output and operands
    * @return a new instance of Atan
    */
@@ -498,8 +498,8 @@ public <T extends TType> Atan<T> atan(Operand<T> x) {
    *  </blockquote>
    *
    * @param <T> data type for {@code z} output
-   * @param y the y value
-   * @param x the x value
+   * @param y The y value
+   * @param x The x value
    * @param <T> data type for {@code Atan2} output and operands
    * @return a new instance of Atan2
    */
@@ -520,7 +520,7 @@ public <T extends TNumber> Atan2<T> atan2(Operand<T> y, Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Atanh} output and operands
    * @return a new instance of Atanh
    */
@@ -538,9 +538,9 @@ public <T extends TType> Atanh<T> atanh(Operand<T> x) {
    *  beta function.
    *
    * @param <T> data type for {@code z} output
-   * @param a the a value
-   * @param b the b value
-   * @param x the x value
+   * @param a The a value
+   * @param b The b value
+   * @param x The x value
    * @param <T> data type for {@code Betainc} output and operands
    * @return a new instance of Betainc
    */
@@ -575,7 +575,7 @@ public <T extends TNumber> Bincount<T> bincount(Operand<TInt32> arr, Operand<TIn
    * Returns element-wise smallest integer not less than x.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Ceil} output and operands
    * @return a new instance of Ceil
    */
@@ -601,7 +601,7 @@ public <T extends TNumber> Ceil<T> ceil(Operand<T> x) {
    *  </blockquote>
    *
    * @param <U> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of ComplexAbs, with default output types
    */
   public ComplexAbs<TFloat32> complexAbs(Operand<? extends TType> x) {
@@ -626,8 +626,8 @@ public ComplexAbs<TFloat32> complexAbs(Operand<? extends TType> x) {
    *  </blockquote>
    *
    * @param <U> data type for {@code y} output
-   * @param x the x value
-   * @param Tout the value of the Tout property
+   * @param x The x value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code ComplexAbs} output and operands
    * @return a new instance of ComplexAbs
    */
@@ -649,7 +649,7 @@ public <U extends TNumber> ComplexAbs<U> complexAbs(Operand<? extends TType> x,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code Conj} output and operands
    * @return a new instance of Conj
    */
@@ -669,7 +669,7 @@ public <T extends TType> Conj<T> conj(Operand<T> input) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Cos} output and operands
    * @return a new instance of Cos
    */
@@ -688,7 +688,7 @@ public <T extends TType> Cos<T> cos(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Cosh} output and operands
    * @return a new instance of Cosh
    */
@@ -802,7 +802,7 @@ public <U extends TNumber, T extends TNumber> DenseBincount<U> denseBincount(Ope
    *  {@code Gamma(x)}), element-wise.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Digamma} output and operands
    * @return a new instance of Digamma
    */
@@ -816,8 +816,8 @@ public <T extends TNumber> Digamma<T> digamma(Operand<T> x) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Div} output and operands
    * @return a new instance of Div
    */
@@ -831,8 +831,8 @@ public <T extends TType> Div<T> div(Operand<T> x, Operand<T> y) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code DivNoNan} output and operands
    * @return a new instance of DivNoNan
    */
@@ -854,8 +854,8 @@ public <T extends TType> DivNoNan<T> divNoNan(Operand<T> x, Operand<T> y) {
    *  tf.math.equal(x, y) ==&gt; array([True,  True])
    *  </pre>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param options carries optional attribute values
    * @param <T> data type for {@code Equal} output and operands
    * @return a new instance of Equal
@@ -868,7 +868,7 @@ public <T extends TType> Equal equal(Operand<T> x, Operand<T> y, Equal.Options..
    * Computes the  <a href="https://en.wikipedia.org/wiki/Error_function">Gauss error function</a>  of {@code x} element-wise. In statistics, for non-negative values of $x$, the error function has the following interpretation: for a random variable $Y$ that is normally distributed with mean 0 and variance $1/\sqrt{2}$, $erf(x)$ is the probability that $Y$ falls in the range $[−x, x]$.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Erf} output and operands
    * @return a new instance of Erf
    */
@@ -880,7 +880,7 @@ public <T extends TNumber> Erf<T> erf(Operand<T> x) {
    * Computes the complementary error function of {@code x} element-wise.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Erfc} output and operands
    * @return a new instance of Erfc
    */
@@ -892,7 +892,7 @@ public <T extends TNumber> Erfc<T> erfc(Operand<T> x) {
    * The Erfinv operation
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Erfinv} output and operands
    * @return a new instance of erfinv
    */
@@ -925,7 +925,7 @@ public <T extends TNumber> erfinv<T> erfinv(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Exp} output and operands
    * @return a new instance of Exp
    */
@@ -949,7 +949,7 @@ public <T extends TType> Exp<T> exp(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Expm1} output and operands
    * @return a new instance of Expm1
    */
@@ -970,7 +970,7 @@ public Fact fact() {
    * Returns element-wise largest integer not greater than x.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Floor} output and operands
    * @return a new instance of Floor
    */
@@ -984,8 +984,8 @@ public <T extends TNumber> Floor<T> floor(Operand<T> x) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code FloorDiv} output and operands
    * @return a new instance of FloorDiv
    */
@@ -1001,8 +1001,8 @@ public <T extends TType> FloorDiv<T> floorDiv(Operand<T> x, Operand<T> y) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code FloorMod} output and operands
    * @return a new instance of FloorMod
    */
@@ -1025,8 +1025,8 @@ public <T extends TNumber> FloorMod<T> floorMod(Operand<T> x, Operand<T> y) {
    *  tf.math.greater(x, y) ==&gt; [False, False, True]
    *  </pre>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Greater} output and operands
    * @return a new instance of Greater
    */
@@ -1049,8 +1049,8 @@ public <T extends TNumber> Greater greater(Operand<T> x, Operand<T> y) {
    *  tf.math.greater_equal(x, y) ==&gt; [True, False, True, True]
    *  </pre>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code GreaterEqual} output and operands
    * @return a new instance of GreaterEqual
    */
@@ -1069,8 +1069,8 @@ public <T extends TNumber> GreaterEqual greaterEqual(Operand<T> x, Operand<T> y)
    *  Gamma function.
    *
    * @param <T> data type for {@code z} output
-   * @param a the a value
-   * @param x the x value
+   * @param a The a value
+   * @param x The x value
    * @param <T> data type for {@code Igamma} output and operands
    * @return a new instance of Igamma
    */
@@ -1089,8 +1089,8 @@ public <T extends TNumber> Igamma<T> igamma(Operand<T> a, Operand<T> x) {
    *  Gamma function.
    *
    * @param <T> data type for {@code z} output
-   * @param a the a value
-   * @param x the x value
+   * @param a The a value
+   * @param x The x value
    * @param <T> data type for {@code Igammac} output and operands
    * @return a new instance of Igammac
    */
@@ -1111,7 +1111,7 @@ public <T extends TNumber> Igammac<T> igammac(Operand<T> a, Operand<T> x) {
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Imag, with default output types
    */
   public Imag<TFloat32> imag(Operand<? extends TType> input) {
@@ -1131,8 +1131,8 @@ public Imag<TFloat32> imag(Operand<? extends TType> input) {
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Imag} output and operands
    * @return a new instance of Imag
    */
@@ -1174,7 +1174,7 @@ public <T extends TNumber> InvertPermutation<T> invertPermutation(Operand<T> x)
    *  tf.math.is_finite(x) ==&gt; [True, True, True, False, False]
    *  </pre>
    *
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of IsFinite
    */
   public IsFinite isFinite(Operand<? extends TNumber> x) {
@@ -1192,7 +1192,7 @@ public IsFinite isFinite(Operand<? extends TNumber> x) {
    *  tf.math.is_inf(x) ==&gt; [False, True, False, True]
    *  </pre>
    *
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of IsInf
    */
   public IsInf isInf(Operand<? extends TNumber> x) {
@@ -1210,7 +1210,7 @@ public IsInf isInf(Operand<? extends TNumber> x) {
    *  tf.math.is_nan(x) ==&gt; [False, True, False, True, False]
    *  </pre>
    *
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of IsNan
    */
   public IsNan isNan(Operand<? extends TNumber> x) {
@@ -1232,8 +1232,8 @@ public IsNan isNan(Operand<? extends TNumber> x) {
    *  tf.math.less(x, y) ==&gt; [False, True, True]
    *  </pre>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Less} output and operands
    * @return a new instance of Less
    */
@@ -1256,8 +1256,8 @@ public <T extends TNumber> Less less(Operand<T> x, Operand<T> y) {
    *  tf.math.less_equal(x, y) ==&gt; [True, True, True]
    *  </pre>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code LessEqual} output and operands
    * @return a new instance of LessEqual
    */
@@ -1276,7 +1276,7 @@ public <T extends TNumber> LessEqual lessEqual(Operand<T> x, Operand<T> y) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Lgamma} output and operands
    * @return a new instance of Lgamma
    */
@@ -1294,7 +1294,7 @@ public <T extends TNumber> Lgamma<T> lgamma(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Log} output and operands
    * @return a new instance of Log
    */
@@ -1312,7 +1312,7 @@ public <T extends TType> Log<T> log(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Log1p} output and operands
    * @return a new instance of Log1p
    */
@@ -1325,8 +1325,8 @@ public <T extends TType> Log1p<T> log1p(Operand<T> x) {
    *  <em>NOTE</em>: {@code math.LogicalAnd} supports broadcasting. More about broadcasting
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @return a new instance of LogicalAnd
    */
   public LogicalAnd logicalAnd(Operand<TBool> x, Operand<TBool> y) {
@@ -1348,8 +1348,8 @@ public LogicalNot logicalNot(Operand<TBool> x) {
    *  <em>NOTE</em>: {@code math.LogicalOr} supports broadcasting. More about broadcasting
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @return a new instance of LogicalOr
    */
   public LogicalOr logicalOr(Operand<TBool> x, Operand<TBool> y) {
@@ -1362,8 +1362,8 @@ public LogicalOr logicalOr(Operand<TBool> x, Operand<TBool> y) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Maximum} output and operands
    * @return a new instance of Maximum
    */
@@ -1397,8 +1397,8 @@ public <T extends TType> Mean<T> mean(Operand<T> input, Operand<? extends TNumbe
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Minimum} output and operands
    * @return a new instance of Minimum
    */
@@ -1414,8 +1414,8 @@ public <T extends TNumber> Minimum<T> minimum(Operand<T> x, Operand<T> y) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Mod} output and operands
    * @return a new instance of Mod
    */
@@ -1429,8 +1429,8 @@ public <T extends TNumber> Mod<T> mod(Operand<T> x, Operand<T> y) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Mul} output and operands
    * @return a new instance of Mul
    */
@@ -1444,8 +1444,8 @@ public <T extends TType> Mul<T> mul(Operand<T> x, Operand<T> y) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code MulNoNan} output and operands
    * @return a new instance of MulNoNan
    */
@@ -1457,7 +1457,7 @@ public <T extends TType> MulNoNan<T> mulNoNan(Operand<T> x, Operand<T> y) {
    * The Ndtri operation
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Ndtri} output and operands
    * @return a new instance of Ndtri
    */
@@ -1470,7 +1470,7 @@ public <T extends TNumber> Ndtri<T> ndtri(Operand<T> x) {
    *  I.e., \(y = -x\).
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Neg} output and operands
    * @return a new instance of Neg
    */
@@ -1487,8 +1487,8 @@ public <T extends TType> Neg<T> neg(Operand<T> x) {
    *  <br>{@literal @}end_compatibility
    *
    * @param <T> data type for {@code output} output
-   * @param x1 the x1 value
-   * @param x2 the x2 value
+   * @param x1 The x1 value
+   * @param x2 The x2 value
    * @param <T> data type for {@code NextAfter} output and operands
    * @return a new instance of NextAfter
    */
@@ -1501,8 +1501,8 @@ public <T extends TNumber> NextAfter<T> nextAfter(Operand<T> x1, Operand<T> x2)
    *  <em>NOTE</em>: {@code math.NotEqual} supports broadcasting. More about broadcasting
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param options carries optional attribute values
    * @param <T> data type for {@code NotEqual} output and operands
    * @return a new instance of NotEqual
@@ -1520,8 +1520,8 @@ public <T extends TType> NotEqual notEqual(Operand<T> x, Operand<T> y,
    *  The polygamma function is defined only for non-negative integer orders \a\.
    *
    * @param <T> data type for {@code z} output
-   * @param a the a value
-   * @param x the x value
+   * @param a The a value
+   * @param x The x value
    * @param <T> data type for {@code Polygamma} output and operands
    * @return a new instance of Polygamma
    */
@@ -1537,7 +1537,7 @@ public <T extends TNumber> Polygamma<T> polygamma(Operand<T> a, Operand<T> x) {
    *  {@code int32} or {@code int64} and perform the bitcount on the result, than to feed in
    *  8- or 16-bit inputs and then aggregate the resulting counts.
    *
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of PopulationCount
    */
   public PopulationCount populationCount(Operand<? extends TNumber> x) {
@@ -1555,8 +1555,8 @@ public PopulationCount populationCount(Operand<? extends TNumber> x) {
    *  </pre>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Pow} output and operands
    * @return a new instance of Pow
    */
@@ -1568,13 +1568,13 @@ public <T extends TType> Pow<T> pow(Operand<T> x, Operand<T> y) {
    * Returns x + y element-wise, working on quantized buffers.
    *
    * @param <V> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param minX The float value that the lowest quantized {@code x} value represents.
    * @param maxX The float value that the highest quantized {@code x} value represents.
    * @param minY The float value that the lowest quantized {@code y} value represents.
    * @param maxY The float value that the highest quantized {@code y} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param <V> data type for {@code QuantizedAdd} output and operands
    * @return a new instance of QuantizedAdd
    */
@@ -1588,13 +1588,13 @@ public <V extends TNumber> QuantizedAdd<V> quantizedAdd(Operand<? extends TNumbe
    * Returns x * y element-wise, working on quantized buffers.
    *
    * @param <V> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param minX The float value that the lowest quantized {@code x} value represents.
    * @param maxX The float value that the highest quantized {@code x} value represents.
    * @param minY The float value that the lowest quantized {@code y} value represents.
    * @param maxY The float value that the highest quantized {@code y} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param <V> data type for {@code QuantizedMul} output and operands
    * @return a new instance of QuantizedMul
    */
@@ -1617,7 +1617,7 @@ public <V extends TNumber> QuantizedMul<V> quantizedMul(Operand<? extends TNumbe
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Real, with default output types
    */
   public Real<TFloat32> real(Operand<? extends TType> input) {
@@ -1637,8 +1637,8 @@ public Real<TFloat32> real(Operand<? extends TType> input) {
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Real} output and operands
    * @return a new instance of Real
    */
@@ -1653,8 +1653,8 @@ public <U extends TNumber> Real<U> real(Operand<? extends TType> input, Class<U>
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RealDiv} output and operands
    * @return a new instance of RealDiv
    */
@@ -1667,7 +1667,7 @@ public <T extends TType> RealDiv<T> realDiv(Operand<T> x, Operand<T> y) {
    *  I.e., \(y = 1 / x\).
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Reciprocal} output and operands
    * @return a new instance of Reciprocal
    */
@@ -1687,7 +1687,7 @@ public <T extends TType> Reciprocal<T> reciprocal(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Rint} output and operands
    * @return a new instance of Rint
    */
@@ -1701,7 +1701,7 @@ public <T extends TNumber> Rint<T> rint(Operand<T> x) {
    *  according to the current system rounding mode use std::cint.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Round} output and operands
    * @return a new instance of Round
    */
@@ -1714,7 +1714,7 @@ public <T extends TType> Round<T> round(Operand<T> x) {
    *  I.e., \(y = 1 / \sqrt{x}\).
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Rsqrt} output and operands
    * @return a new instance of Rsqrt
    */
@@ -1743,7 +1743,7 @@ public <T extends TType> Rsqrt<T> rsqrt(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    *  first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentMax} output and operands
@@ -1776,7 +1776,7 @@ public <T extends TNumber> SegmentMax<T> segmentMax(Operand<T> data,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    *  first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentMean} output and operands
@@ -1808,7 +1808,7 @@ public <T extends TType> SegmentMean<T> segmentMean(Operand<T> data,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    *  first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentMin} output and operands
@@ -1840,7 +1840,7 @@ public <T extends TNumber> SegmentMin<T> segmentMin(Operand<T> data,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    *  first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentProd} output and operands
@@ -1872,7 +1872,7 @@ public <T extends TType> SegmentProd<T> segmentProd(Operand<T> data,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    *  first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentSum} output and operands
@@ -1888,7 +1888,7 @@ public <T extends TType> SegmentSum<T> segmentSum(Operand<T> data,
    *  Specifically, {@code y = 1 / (1 + exp(-x))}.
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sigmoid} output and operands
    * @return a new instance of Sigmoid
    */
@@ -1911,7 +1911,7 @@ public <T extends TType> Sigmoid<T> sigmoid(Operand<T> x) {
    *  </blockquote>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sign} output and operands
    * @return a new instance of Sign
    */
@@ -1930,7 +1930,7 @@ public <T extends TType> Sign<T> sign(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sin} output and operands
    * @return a new instance of Sin
    */
@@ -1949,7 +1949,7 @@ public <T extends TType> Sin<T> sin(Operand<T> x) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sinh} output and operands
    * @return a new instance of Sinh
    */
@@ -1961,7 +1961,7 @@ public <T extends TType> Sinh<T> sinh(Operand<T> x) {
    * The Softplus operation
    *
    * @param <T> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Softplus} output and operands
    * @return a new instance of Softplus
    */
@@ -1974,7 +1974,7 @@ public <T extends TNumber> Softplus<T> softplus(Operand<T> features) {
    *  I.e., \(y = \sqrt{x} = x^{1/2}\).
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sqrt} output and operands
    * @return a new instance of Sqrt
    */
@@ -1987,7 +1987,7 @@ public <T extends TType> Sqrt<T> sqrt(Operand<T> x) {
    *  I.e., \(y = x * x = x^2\).
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Square} output and operands
    * @return a new instance of Square
    */
@@ -2001,8 +2001,8 @@ public <T extends TType> Square<T> square(Operand<T> x) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code SquaredDifference} output and operands
    * @return a new instance of SquaredDifference
    */
@@ -2016,8 +2016,8 @@ public <T extends TType> SquaredDifference<T> squaredDifference(Operand<T> x, Op
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Sub} output and operands
    * @return a new instance of Sub
    */
@@ -2037,7 +2037,7 @@ public <T extends TType> Sub<T> sub(Operand<T> x, Operand<T> y) {
    *  </pre>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Tan} output and operands
    * @return a new instance of Tan
    */
@@ -2063,7 +2063,7 @@ public <T extends TType> Tan<T> tan(Operand<T> x) {
    *  </blockquote>
    *
    * @param <T> data type for {@code y} output
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Tanh} output and operands
    * @return a new instance of Tanh
    */
@@ -2081,8 +2081,8 @@ public <T extends TType> Tanh<T> tanh(Operand<T> x) {
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code TruncateDiv} output and operands
    * @return a new instance of TruncateDiv
    */
@@ -2097,8 +2097,8 @@ public <T extends TType> TruncateDiv<T> truncateDiv(Operand<T> x, Operand<T> y)
    *   <a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a>
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code TruncateMod} output and operands
    * @return a new instance of TruncateMod
    */
@@ -2133,9 +2133,9 @@ public <T extends TNumber> TruncateMod<T> truncateMod(Operand<T> x, Operand<T> y
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentMax} output and operands
    * @return a new instance of UnsortedSegmentMax
    */
@@ -2168,9 +2168,9 @@ public <T extends TNumber> UnsortedSegmentMax<T> unsortedSegmentMax(Operand<T> d
    *  dropped, and will not be included in the result.
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentMin} output and operands
    * @return a new instance of UnsortedSegmentMin
    */
@@ -2202,9 +2202,9 @@ public <T extends TNumber> UnsortedSegmentMin<T> unsortedSegmentMin(Operand<T> d
    *  dropped, and will not be included in the result.
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentProd} output and operands
    * @return a new instance of UnsortedSegmentProd
    */
@@ -2238,9 +2238,9 @@ public <T extends TType> UnsortedSegmentProd<T> unsortedSegmentProd(Operand<T> d
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentSum} output and operands
    * @return a new instance of UnsortedSegmentSum
    */
@@ -2253,8 +2253,8 @@ public <T extends TType> UnsortedSegmentSum<T> unsortedSegmentSum(Operand<T> dat
    * Returns 0 if x == 0, and x / y otherwise, elementwise.
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Xdivy} output and operands
    * @return a new instance of Xdivy
    */
@@ -2266,8 +2266,8 @@ public <T extends TType> Xdivy<T> xdivy(Operand<T> x, Operand<T> y) {
    * Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise.
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Xlog1py} output and operands
    * @return a new instance of Xlog1py
    */
@@ -2279,8 +2279,8 @@ public <T extends TType> Xlog1py<T> xlog1py(Operand<T> x, Operand<T> y) {
    * Returns 0 if x == 0, and x * log(y) otherwise, elementwise.
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Xlogy} output and operands
    * @return a new instance of Xlogy
    */
@@ -2294,8 +2294,8 @@ public <T extends TType> Xlogy<T> xlogy(Operand<T> x, Operand<T> y) {
    *  <p>\(\zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x}\)
    *
    * @param <T> data type for {@code z} output
-   * @param x the x value
-   * @param q the q value
+   * @param x The x value
+   * @param q The q value
    * @param <T> data type for {@code Zeta} output and operands
    * @return a new instance of Zeta
    */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java
index 9ec8edfb8c1..00d3283e0f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java
@@ -537,11 +537,11 @@ public <T extends TNumber> CtcLoss<T> ctcLoss(Operand<T> inputs, Operand<TInt64>
    *  no projection is performed.
    *
    * @param <T> data type for {@code params} output
-   * @param numLayers the numLayers value
-   * @param numUnits the numUnits value
-   * @param inputSize the inputSize value
-   * @param weights the weights value
-   * @param biases the biases value
+   * @param numLayers The numLayers value
+   * @param numUnits The numUnits value
+   * @param inputSize The inputSize value
+   * @param weights The weights value
+   * @param biases The biases value
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNCanonicalToParamsV2} output and operands
    * @return a new instance of CudnnRNNCanonicalToParams
@@ -585,12 +585,12 @@ public <T extends TNumber> CudnnRNNCanonicalToParams<T> cudnnRNNCanonicalToParam
    *  no projection is performed.
    *
    * @param <T> data type for {@code weights} output
-   * @param numLayers the numLayers value
-   * @param numUnits the numUnits value
-   * @param inputSize the inputSize value
-   * @param params the params value
-   * @param numParamsWeights the value of the numParamsWeights property
-   * @param numParamsBiases the value of the numParamsBiases property
+   * @param numLayers The numLayers value
+   * @param numUnits The numUnits value
+   * @param inputSize The inputSize value
+   * @param params The params value
+   * @param numParamsWeights The value of the numParamsWeights attribute
+   * @param numParamsBiases The value of the numParamsBiases attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNParamsToCanonicalV2} output and operands
    * @return a new instance of CudnnRNNParamsToCanonical
@@ -626,11 +626,11 @@ public <T extends TNumber> CudnnRNNParamsToCanonical<T> cudnnRNNParamsToCanonica
    *  across different runs.
    *
    * @param <T> data type for {@code params_size} output
-   * @param numLayers the numLayers value
-   * @param numUnits the numUnits value
-   * @param inputSize the inputSize value
-   * @param T the value of the T property
-   * @param S the value of the S property
+   * @param numLayers The numLayers value
+   * @param numUnits The numUnits value
+   * @param inputSize The inputSize value
+   * @param T The value of the T attribute
+   * @param S The value of the S attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNParamsSize} output and operands
    * @param <U> data type for {@code CudnnRNNParamsSize} output and operands
@@ -769,7 +769,7 @@ public <T extends TNumber> DataFormatVecPermute<T> dataFormatVecPermute(Operand<
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param blockSize The size of the spatial block, same as in Space2Depth.
    * @param options carries optional attribute values
    * @param <T> data type for {@code DepthToSpace} output and operands
@@ -800,8 +800,8 @@ public <T extends TType> DepthToSpace<T> depthToSpace(Operand<T> input, Long blo
    *  horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param filter the filter value
+   * @param input The input value
+   * @param filter The filter value
    * @param strides 1-D of length 4.  The stride of the sliding window for each dimension
    *  of {@code input}.
    * @param padding The type of padding algorithm to use.
@@ -973,7 +973,7 @@ public <T extends TNumber> Dilation2dBackpropInput<T> dilation2dBackpropInput(Op
    *  </a>
    *
    * @param <T> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Elu} output and operands
    * @return a new instance of Elu
    */
@@ -1160,7 +1160,7 @@ public <T extends TNumber, U extends TNumber> FusedBatchNormGrad<T, U> fusedBatc
    *  rows must be the same as the rank of {@code input}.
    * @param filter 4-D with shape
    *  {@code [filter_height, filter_width, in_channels, out_channels]}.
-   * @param mode the value of the mode property
+   * @param mode The value of the mode attribute
    * @param strides 1-D of length 4.  The stride of the sliding window for each dimension
    *  of {@code input}. Must be in the same order as the dimension specified with format.
    * @param padding The type of padding algorithm to use.
@@ -1194,7 +1194,7 @@ public <T extends TNumber> FusedPadConv2d<T> fusedPadConv2d(Operand<T> input,
    *  rows must be the same as the rank of {@code input}.
    * @param filter 4-D with shape
    *  {@code [filter_height, filter_width, in_channels, out_channels]}.
-   * @param mode the value of the mode property
+   * @param mode The value of the mode attribute
    * @param strides 1-D of length 4.  The stride of the sliding window for each dimension
    *  of {@code input}. Must be in the same order as the dimension specified with format.
    * @param padding The type of padding algorithm to use.
@@ -1253,7 +1253,7 @@ public <T extends TNumber> L2Loss<T> l2Loss(Operand<T> t) {
    * Computes rectified linear: {@code max(features, features * alpha)}.
    *
    * @param <T> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param options carries optional attribute values
    * @param <T> data type for {@code LeakyRelu} output and operands
    * @return a new instance of LeakyRelu
@@ -1521,7 +1521,7 @@ public <T extends TNumber> MaxPoolWithArgmax<T, TInt64> maxPoolWithArgmax(Operan
    * @param ksize The size of the window for each dimension of the input tensor.
    * @param strides The stride of the sliding window for each dimension of the
    *  input tensor.
-   * @param Targmax the value of the Targmax property
+   * @param Targmax The value of the Targmax attribute
    * @param padding The type of padding algorithm to use.
    * @param options carries optional attribute values
    * @param <T> data type for {@code MaxPoolWithArgmax} output and operands
@@ -1606,7 +1606,7 @@ public <T extends TNumber> QuantizedAvgPool<T> quantizedAvgPool(Operand<T> input
    *  with the normalized tensor.
    * @param gammaMin The value represented by the lowest quantized gamma.
    * @param gammaMax The value represented by the highest quantized gamma.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param varianceEpsilon A small float number to avoid dividing by 0.
    * @param scaleAfterNormalization A bool indicating whether the resulted tensor
    *  needs to be multiplied with gamma.
@@ -1628,13 +1628,13 @@ public <U extends TNumber, T extends TNumber> QuantizedBatchNormWithGlobalNormal
    *  Broadcasts the values of bias on dimensions 0..N-2 of 'input'.
    *
    * @param <V> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param bias A 1D bias Tensor with size matching the last dimension of 'input'.
    * @param minInput The float value that the lowest quantized input value represents.
    * @param maxInput The float value that the highest quantized input value represents.
    * @param minBias The float value that the lowest quantized bias value represents.
    * @param maxBias The float value that the highest quantized bias value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <V> data type for {@code QuantizedBiasAdd} output and operands
    * @return a new instance of QuantizedBiasAdd
    */
@@ -1652,13 +1652,13 @@ public <V extends TNumber> QuantizedBiasAdd<V> quantizedBiasAdd(Operand<? extend
    *  taking the returned minimum and maximum values into account.
    *
    * @param <V> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param filter filter's input_depth dimension must match input's depth dimensions.
    * @param minInput The float value that the lowest quantized input value represents.
    * @param maxInput The float value that the highest quantized input value represents.
    * @param minFilter The float value that the lowest quantized filter value represents.
    * @param maxFilter The float value that the highest quantized filter value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param strides The stride of the sliding window for each dimension of the input
    *  tensor.
    * @param padding The type of padding algorithm to use.
@@ -1714,10 +1714,10 @@ public <T extends TNumber> QuantizedMaxPool<T> quantizedMaxPool(Operand<T> input
    * Computes Quantized Rectified Linear: {@code max(features, 0)}
    *
    * @param <U> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param minFeatures The float value that the lowest quantized value represents.
    * @param maxFeatures The float value that the highest quantized value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code QuantizedRelu} output and operands
    * @return a new instance of QuantizedRelu
    */
@@ -1730,10 +1730,10 @@ public <U extends TNumber> QuantizedRelu<U> quantizedRelu(Operand<? extends TNum
    * Computes Quantized Rectified Linear 6: {@code min(max(features, 0), 6)}
    *
    * @param <U> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param minFeatures The float value that the lowest quantized value represents.
    * @param maxFeatures The float value that the highest quantized value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code QuantizedRelu6} output and operands
    * @return a new instance of QuantizedRelu6
    */
@@ -1746,11 +1746,11 @@ public <U extends TNumber> QuantizedRelu6<U> quantizedRelu6(Operand<? extends TN
    * Computes Quantized Rectified Linear X: {@code min(max(features, 0), max_value)}
    *
    * @param <U> data type for {@code activations} output
-   * @param features the features value
-   * @param maxValue the maxValue value
+   * @param features The features value
+   * @param maxValue The maxValue value
    * @param minFeatures The float value that the lowest quantized value represents.
    * @param maxFeatures The float value that the highest quantized value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code QuantizedReluX} output and operands
    * @return a new instance of QuantizedReluX
    */
@@ -1774,7 +1774,7 @@ public <U extends TNumber> QuantizedReluX<U> quantizedReluX(Operand<? extends TN
    *  </blockquote>
    *
    * @param <T> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Relu} output and operands
    * @return a new instance of Relu
    */
@@ -1786,7 +1786,7 @@ public <T extends TNumber> Relu<T> relu(Operand<T> features) {
    * Computes rectified linear 6: {@code min(max(features, 0), 6)}.
    *
    * @param <T> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Relu6} output and operands
    * @return a new instance of Relu6
    */
@@ -1803,7 +1803,7 @@ public <T extends TNumber> Relu6<T> relu6(Operand<T> features) {
    *  <p>See  <a href="https://arxiv.org/abs/1706.02515">Self-Normalizing Neural Networks</a>
    *
    * @param <T> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Selu} output and operands
    * @return a new instance of Selu
    */
@@ -1848,7 +1848,7 @@ public <T extends TNumber> SoftmaxCrossEntropyWithLogits<T> softmaxCrossEntropyW
    * Computes softsign: {@code features / (abs(features) + 1)}.
    *
    * @param <T> data type for {@code activations} output
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Softsign} output and operands
    * @return a new instance of Softsign
    */
@@ -1935,7 +1935,7 @@ public <T extends TNumber> Softsign<T> softsign(Operand<T> features) {
    *    height_pad = pad_top + height + pad_bottom
    *    width_pad = pad_left + width + pad_right
    *  </pre>
-   * @param blockSize the value of the blockSize property
+   * @param blockSize The value of the blockSize attribute
    * @param <T> data type for {@code SpaceToBatch} output and operands
    * @return a new instance of SpaceToBatch
    */
@@ -2016,7 +2016,7 @@ public <T extends TType> SpaceToBatch<T> spaceToBatch(Operand<T> input,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param blockSize The size of the spatial block.
    * @param options carries optional attribute values
    * @param <T> data type for {@code SpaceToDepth} output and operands
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
index b4ab7753142..8da481a6c72 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
@@ -773,11 +773,11 @@ public BarrierTakeMany barrierTakeMany(Operand<TString> handle, Operand<TInt32>
    *  empty, the op name will be used as the shared name.
    *  T: the types of tensors to be batched.
    *
-   * @param inTensors the inTensors value
-   * @param numBatchThreads the value of the numBatchThreads property
-   * @param maxBatchSize the value of the maxBatchSize property
-   * @param batchTimeoutMicros the value of the batchTimeoutMicros property
-   * @param gradTimeoutMicros the value of the gradTimeoutMicros property
+   * @param inTensors The inTensors value
+   * @param numBatchThreads The value of the numBatchThreads attribute
+   * @param maxBatchSize The value of the maxBatchSize attribute
+   * @param batchTimeoutMicros The value of the batchTimeoutMicros attribute
+   * @param gradTimeoutMicros The value of the gradTimeoutMicros attribute
    * @param options carries optional attribute values
    * @return a new instance of Batch
    */
@@ -824,7 +824,7 @@ public Batch batch(Iterable<Operand<?>> inTensors, Long numBatchThreads, Long ma
    * @param inTensors The tensors to be batched.
    * @param capturedTensors The tensors which are captured in the function, and don't need
    *  to be batched.
-   * @param f the value of the f property
+   * @param f The value of the f attribute
    * @param numBatchThreads Number of scheduling threads for processing batches of work.
    *  Determines the number of batches processed in parallel.
    * @param maxBatchSize Batch sizes will never be bigger than this.
@@ -860,7 +860,7 @@ public BatchFunction batchFunction(Iterable<Operand<?>> inTensors,
    *  <pre>
    *  crops = [[crop_top, crop_bottom], [crop_left, crop_right]]
    *  </pre>
-   * @param blockSize the value of the blockSize property
+   * @param blockSize The value of the blockSize attribute
    * @param <T> data type for {@code BatchToSpace} output and operands
    * @return a new instance of BatchToSpace
    */
@@ -1043,8 +1043,8 @@ public <T extends TType> BatchToSpaceNd<T> batchToSpaceNd(Operand<T> input,
    *  endian orderings will give different results.
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
-   * @param type the value of the type property
+   * @param input The input value
+   * @param type The value of the type attribute
    * @param <U> data type for {@code Bitcast} output and operands
    * @return a new instance of Bitcast
    */
@@ -1112,8 +1112,8 @@ public <T extends TType> Operand<T> booleanMaskUpdate(Operand<T> tensor, Operand
    *  broadcasted shape. {@code s0}, {@code s1} and {@code r0} are all integer vectors.
    *
    * @param <T> data type for {@code r0} output
-   * @param s0 the s0 value
-   * @param s1 the s1 value
+   * @param s0 The s0 value
+   * @param s1 The s1 value
    * @param <T> data type for {@code BroadcastArgs} output and operands
    * @return a new instance of BroadcastDynamicShape
    */
@@ -2224,7 +2224,7 @@ public <T extends TType> DestroyTemporaryVariable<T> destroyTemporaryVariable(Op
    *  </div>
    *
    * @param <T> data type for {@code outputs} output
-   * @param data the data value
+   * @param data The data value
    * @param partitions Any shape.  Indices in the range {@code [0, num_partitions)}.
    * @param numPartitions The number of partitions to output.
    * @param <T> data type for {@code DynamicPartition} output and operands
@@ -2292,8 +2292,8 @@ public <T extends TType> DynamicPartition<T> dynamicPartition(Operand<T> data,
    *  </div>
    *
    * @param <T> data type for {@code merged} output
-   * @param indices the indices value
-   * @param data the data value
+   * @param indices The indices value
+   * @param data The data value
    * @param <T> data type for {@code DynamicStitch} output and operands
    * @return a new instance of DynamicStitch
    */
@@ -2337,7 +2337,7 @@ public <T extends TType> EditDistance editDistance(Operand<TInt64> hypothesisInd
    *
    * @param <T> data type for {@code output} output
    * @param shape 1-D. Represents the shape of the output tensor.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code Empty} output and operands
    * @return a new instance of Empty
@@ -2355,9 +2355,9 @@ public <T extends TType> Empty<T> empty(Operand<TInt32> shape, Class<T> dtype,
    *  element_dtype: the type of elements in the list.
    *  element_shape: a shape compatible with that of elements in the list.
    *
-   * @param elementShape the elementShape value
-   * @param maxNumElements the maxNumElements value
-   * @param elementDtype the value of the elementDtype property
+   * @param elementShape The elementShape value
+   * @param maxNumElements The maxNumElements value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <U> data type for {@code EmptyTensorList} output and operands
    * @return a new instance of EmptyTensorList
    */
@@ -2478,7 +2478,7 @@ public <T extends TType> EnsureShape<T> ensureShape(Operand<T> input, Shape shap
    *  size 1.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param axis 0-D (scalar). Specifies the dimension index at which to
    *  expand the shape of {@code input}. Must be in the range
    *  {@code [-rank(input) - 1, rank(input)]}.
@@ -2822,7 +2822,7 @@ public Gradients gradients(Operand<?> y, Iterable<? extends Operand<?>> x,
    *  <p>Returns the input tensor without modification.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code GuaranteeConst} output and operands
    * @return a new instance of GuaranteeConst
    */
@@ -2902,7 +2902,7 @@ public <T extends TNumber> HistogramFixedWidth<TInt32> histogramFixedWidth(Opera
    *  values &lt;= value_range[0] will be mapped to hist[0],
    *  values &gt;= value_range[1] will be mapped to hist[-1].
    * @param nbins Scalar {@code int32 Tensor}.  Number of histogram bins.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param <U> data type for {@code HistogramFixedWidth} output and operands
    * @param <T> data type for {@code HistogramFixedWidth} output and operands
    * @return a new instance of HistogramFixedWidth
@@ -2916,7 +2916,7 @@ public <U extends TNumber, T extends TNumber> HistogramFixedWidth<U> histogramFi
    * Return a tensor with the same shape and contents as the input tensor or value.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code Identity} output and operands
    * @return a new instance of Identity
    */
@@ -2940,7 +2940,7 @@ public <T extends TType> Identity<T> identity(Operand<T> input) {
    *    return [None, g(dy)]  # Do not backprop to f(x).
    *  </pre>
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of IdentityN
    */
   public IdentityN identityN(Iterable<Operand<?>> input) {
@@ -3118,8 +3118,8 @@ public IsVariableInitialized isVariableInitialized(Operand<? extends TType> ref)
    *  equal to the Kth order statistic. The semantics are not the same as
    *  top_k_unique.
    *
-   * @param input the input value
-   * @param k the value of the k property
+   * @param input The input value
+   * @param k The value of the k attribute
    * @return a new instance of KthOrderStatistic
    */
   public KthOrderStatistic kthOrderStatistic(Operand<TFloat32> input, Long k) {
@@ -3132,8 +3132,8 @@ public KthOrderStatistic kthOrderStatistic(Operand<TFloat32> input, Long k) {
    * @param <T> data type for {@code keys} output
    * @param <U> data type for {@code values} output
    * @param tableHandle Handle to the table.
-   * @param Tkeys the value of the Tkeys property
-   * @param Tvalues the value of the Tvalues property
+   * @param Tkeys The value of the Tkeys attribute
+   * @param Tvalues The value of the Tvalues attribute
    * @param <T> data type for {@code LookupTableExportV2} output and operands
    * @param <U> data type for {@code LookupTableExportV2} output and operands
    * @return a new instance of LookupTableExport
@@ -3153,7 +3153,7 @@ public <T extends TType, U extends TType> LookupTableExport<T, U> lookupTableExp
    * @param <U> data type for {@code values} output
    * @param tableHandle Handle to the table.
    * @param keys Any shape.  Keys to look up.
-   * @param defaultValue the defaultValue value
+   * @param defaultValue The defaultValue value
    * @param <U> data type for {@code LookupTableFindV2} output and operands
    * @return a new instance of LookupTableFind
    */
@@ -3221,7 +3221,7 @@ public LoopCond loopCond(Operand<TBool> input) {
    *  of the corresponding output element. Behavior for infinite elements is
    *  undefined. Behavior for subnormal elements is undefined.
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of MakeUnique
    */
   public MakeUnique makeUnique(Operand<TFloat32> input) {
@@ -3231,7 +3231,7 @@ public MakeUnique makeUnique(Operand<TFloat32> input) {
   /**
    * Op removes all elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapClear
    */
@@ -3242,7 +3242,7 @@ public MapClear mapClear(List<Class<? extends TType>> dtypes, MapClear.Options..
   /**
    * Op returns the number of incomplete elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapIncompleteSize
    */
@@ -3256,9 +3256,9 @@ public MapIncompleteSize mapIncompleteSize(List<Class<? extends TType>> dtypes,
    *  underlying container does not contain this key
    *  this op will block until it does.
    *
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapPeek
    */
@@ -3270,7 +3270,7 @@ public MapPeek mapPeek(Operand<TInt64> key, Operand<TInt32> indices,
   /**
    * Op returns the number of elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapSize
    */
@@ -3282,10 +3282,10 @@ public MapSize mapSize(List<Class<? extends TType>> dtypes, MapSize.Options... o
    * Stage (key, values) in the underlying container which behaves like a hashtable.
    *
    * @param key int64
-   * @param indices the indices value
+   * @param indices The indices value
    * @param values a list of tensors
    *  dtypes A list of data types that inserted values should adhere to.
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapStage
    */
@@ -3300,9 +3300,9 @@ public MapStage mapStage(Operand<TInt64> key, Operand<TInt32> indices,
    *  from the underlying container.   If the underlying container
    *  does not contain this key, the op will block until it does.
    *
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapUnstage
    */
@@ -3316,8 +3316,8 @@ public MapUnstage mapUnstage(Operand<TInt64> key, Operand<TInt32> indices,
    *  from the underlying container.   If the underlying container
    *  does not contain elements, the op will block until it does.
    *
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapUnstageNoKey
    */
@@ -3454,9 +3454,9 @@ public <T extends TType> MirrorPad<T> mirrorPad(Operand<T> input,
    *  graph_def = foo.get_concrete_function(tf.TensorSpec([10], tf.float32), tf.TensorSpec([10], tf.float32)).graph.as_graph_def()
    *  </pre>
    *
-   * @param inputs the inputs value
-   * @param mlirModule the value of the mlirModule property
-   * @param Toutputs the value of the Toutputs property
+   * @param inputs The inputs value
+   * @param mlirModule The value of the mlirModule attribute
+   * @param Toutputs The value of the Toutputs attribute
    * @return a new instance of MlirPassthroughOp
    */
   public MlirPassthroughOp mlirPassthroughOp(Iterable<Operand<?>> inputs, String mlirModule,
@@ -3474,7 +3474,7 @@ public MlirPassthroughOp mlirPassthroughOp(Iterable<Operand<?>> inputs, String m
    *
    * @param emptyKey The key used to represent empty key buckets internally. Must not
    *  be used in insert or lookup operations.
-   * @param deletedKey the deletedKey value
+   * @param deletedKey The deletedKey value
    * @param valueDtype Type of the table values.
    * @param options carries optional attribute values
    * @param <T> data type for {@code MutableDenseHashTableV2} output and operands
@@ -3715,7 +3715,7 @@ public <T extends TType> OnesLike<T> onesLike(Operand<T> x) {
   /**
    * Op removes all elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapClear
    */
@@ -3727,7 +3727,7 @@ public OrderedMapClear orderedMapClear(List<Class<? extends TType>> dtypes,
   /**
    * Op returns the number of incomplete elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapIncompleteSize
    */
@@ -3742,9 +3742,9 @@ public OrderedMapIncompleteSize orderedMapIncompleteSize(List<Class<? extends TT
    *  this op will block until it does.   This Op is optimized for
    *  performance.
    *
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapPeek
    */
@@ -3756,7 +3756,7 @@ public OrderedMapPeek orderedMapPeek(Operand<TInt64> key, Operand<TInt32> indice
   /**
    * Op returns the number of elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapSize
    */
@@ -3770,10 +3770,10 @@ public OrderedMapSize orderedMapSize(List<Class<? extends TType>> dtypes,
    *  associative container.   Elements are ordered by key.
    *
    * @param key int64
-   * @param indices the indices value
+   * @param indices The indices value
    * @param values a list of tensors
    *  dtypes A list of data types that inserted values should adhere to.
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapStage
    */
@@ -3788,9 +3788,9 @@ public OrderedMapStage orderedMapStage(Operand<TInt64> key, Operand<TInt32> indi
    *  from the underlying container.   If the underlying container
    *  does not contain this key, the op will block until it does.
    *
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapUnstage
    */
@@ -3804,8 +3804,8 @@ public OrderedMapUnstage orderedMapUnstage(Operand<TInt64> key, Operand<TInt32>
    *  key from the underlying container.   If the underlying container
    *  does not contain elements, the op will block until it does.
    *
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapUnstageNoKey
    */
@@ -3838,9 +3838,9 @@ public OrderedMapUnstageNoKey orderedMapUnstageNoKey(Operand<TInt32> indices,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param paddings the paddings value
-   * @param constantValues the constantValues value
+   * @param input The input value
+   * @param paddings The paddings value
+   * @param constantValues The constantValues value
    * @param <T> data type for {@code PadV2} output and operands
    * @return a new instance of Pad
    */
@@ -3934,8 +3934,8 @@ public <T extends TType> ParallelConcat<T> parallelConcat(Iterable<Operand<T>> v
    *  </div>
    *
    * @param <T> data type for {@code merged} output
-   * @param indices the indices value
-   * @param data the data value
+   * @param indices The indices value
+   * @param data The data value
    * @param <T> data type for {@code ParallelDynamicStitch} output and operands
    * @return a new instance of ParallelDynamicStitch
    */
@@ -4033,7 +4033,7 @@ public <T extends TType> Prod<T> prod(Operand<T> input, Operand<? extends TNumbe
    * Reshapes a quantized tensor as per the Reshape op.
    *
    * @param <T> data type for {@code output} output
-   * @param tensor the tensor value
+   * @param tensor The tensor value
    * @param shape Defines the shape of the output tensor.
    * @param inputMin The minimum value of the input.
    * @param inputMax The maximum value of the input.
@@ -4081,7 +4081,7 @@ public <T extends TNumber> Range<T> range(Operand<T> start, Operand<T> limit, Op
    *  of a tensor is the number of indices required to uniquely select each element
    *  of the tensor. Rank is also known as &quot;order&quot;, &quot;degree&quot;, or &quot;ndims.&quot;
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Rank
    */
   public Rank rank(Operand<? extends TType> input) {
@@ -4337,7 +4337,7 @@ public RemoteCall remoteCall(Operand<TString> target, Iterable<Operand<?>> args,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param tensor the tensor value
+   * @param tensor The tensor value
    * @param shape Defines the shape of the output tensor.
    * @param <T> data type for {@code Reshape} output and operands
    * @return a new instance of Reshape
@@ -4353,7 +4353,7 @@ public <T extends TType> Reshape<T> reshape(Operand<T> tensor, Operand<? extends
    * @param resource Should be from a scalar {@code Variable} node.
    * @param limit If incrementing ref would bring it above limit, instead generates an
    *  'OutOfRange' error.
-   * @param T the value of the T property
+   * @param T The value of the T attribute
    * @param <T> data type for {@code ResourceCountUpTo} output and operands
    * @return a new instance of ResourceCountUpTo
    */
@@ -4378,9 +4378,9 @@ public <T extends TNumber> ResourceCountUpTo<T> resourceCountUpTo(
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param resource the resource value
-   * @param indices the indices value
-   * @param dtype the value of the dtype property
+   * @param resource The resource value
+   * @param indices The indices value
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code ResourceGather} output and operands
    * @return a new instance of ResourceGather
@@ -4394,9 +4394,9 @@ public <U extends TType> ResourceGather<U> resourceGather(Operand<? extends TTyp
    * The ResourceGatherNd operation
    *
    * @param <U> data type for {@code output} output
-   * @param resource the resource value
-   * @param indices the indices value
-   * @param dtype the value of the dtype property
+   * @param resource The resource value
+   * @param indices The indices value
+   * @param dtype The value of the dtype attribute
    * @param <U> data type for {@code ResourceGatherNd} output and operands
    * @return a new instance of ResourceGatherNd
    */
@@ -4781,11 +4781,11 @@ public ResourceScatterUpdate resourceScatterUpdate(Operand<? extends TType> reso
    *  <p>NOTE this op currently does not support broadcasting and so {@code value}'s
    *  shape must be exactly the shape produced by the slice of {@code ref}.
    *
-   * @param ref the ref value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param value the value value
+   * @param ref The ref value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param value The value value
    * @param options carries optional attribute values
    * @param <T> data type for {@code ResourceStridedSliceAssign} output and operands
    * @return a new instance of ResourceStridedSliceAssign
@@ -4939,7 +4939,7 @@ public <T extends TType> ReverseSequence<T> reverseSequence(Operand<T> input,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param shift Dimension must be 0-D or 1-D. {@code shift[i]} specifies the number of places by which
    *  elements are shifted positively (towards larger indices) along the dimension
    *  specified by {@code axis[i]}. Negative shifts will roll the elements in the opposite
@@ -5461,9 +5461,9 @@ public <T extends TType> ScatterUpdate<T> scatterUpdate(Operand<T> ref,
    * The SelectV2 operation
    *
    * @param <T> data type for {@code output} output
-   * @param condition the condition value
-   * @param t the t value
-   * @param e the e value
+   * @param condition The condition value
+   * @param t The t value
+   * @param e The e value
    * @param <T> data type for {@code SelectV2} output and operands
    * @return a new instance of Select
    */
@@ -5524,7 +5524,7 @@ public <T extends TType> SetDiff1d<T, TInt32> setDiff1d(Operand<T> x, Operand<T>
    * @param <U> data type for {@code idx} output
    * @param x 1-D. Values to keep.
    * @param y 1-D. Values to remove.
-   * @param outIdx the value of the outIdx property
+   * @param outIdx The value of the outIdx attribute
    * @param <T> data type for {@code ListDiff} output and operands
    * @param <U> data type for {@code ListDiff} output and operands
    * @return a new instance of SetDiff1d
@@ -5563,7 +5563,7 @@ public SetSize setSize(Operand<TInt64> setIndices, Operand<? extends TType> setV
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Shape, with default output types
    */
   public org.tensorflow.op.core.Shape<TInt32> shape(Operand<? extends TType> input) {
@@ -5580,8 +5580,8 @@ public org.tensorflow.op.core.Shape<TInt32> shape(Operand<? extends TType> input
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code Shape} output and operands
    * @return a new instance of Shape
    */
@@ -5595,7 +5595,7 @@ public <U extends TNumber> org.tensorflow.op.core.Shape<U> shape(Operand<? exten
    *  This operation returns N 1-D integer tensors representing shape of {@code input[i]s}.
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of ShapeN, with default output types
    */
   public ShapeN<TInt32> shapeN(Iterable<Operand<? extends TType>> input) {
@@ -5607,8 +5607,8 @@ public ShapeN<TInt32> shapeN(Iterable<Operand<? extends TType>> input) {
    *  This operation returns N 1-D integer tensors representing shape of {@code input[i]s}.
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code ShapeN} output and operands
    * @return a new instance of ShapeN
    */
@@ -5628,7 +5628,7 @@ public <U extends TNumber> ShapeN<U> shapeN(Iterable<Operand<? extends TType>> i
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Size, with default output types
    */
   public Size<TInt32> size(Operand<? extends TType> input) {
@@ -5646,8 +5646,8 @@ public Size<TInt32> size(Operand<? extends TType> input) {
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code Size} output and operands
    * @return a new instance of Size
    */
@@ -5676,7 +5676,7 @@ public Skipgram skipgram(String filename, Long batchSize, Skipgram.Options... op
    *  0 &lt;= begin[i] &lt;= begin[i] + size[i] &lt;= Di  for i in [0, n)
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param begin begin[i] specifies the offset into the 'i'th dimension of
    *  'input' to slice from.
    * @param sizeOutput size[i] specifies the number of elements of the 'i'th dimension
@@ -5696,7 +5696,7 @@ public <T extends TType, U extends TNumber> Slice<T> slice(Operand<T> input, Ope
    * Returns a copy of the input tensor.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code Snapshot} output and operands
    * @return a new instance of Snapshot
    */
@@ -5845,7 +5845,7 @@ public <T extends TType> Split<T> split(Operand<TInt32> axis, Operand<T> value,
    *  Can contain one -1 indicating that dimension is to be inferred.
    * @param axis 0-D.  The dimension along which to split.  Must be in the range
    *  {@code [-rank(value), rank(value))}.
-   * @param numSplit the value of the numSplit property
+   * @param numSplit The value of the numSplit attribute
    * @param <T> data type for {@code SplitV} output and operands
    * @return a new instance of SplitV
    */
@@ -5926,7 +5926,7 @@ public Stage stage(Iterable<Operand<?>> values, Stage.Options... options) {
   /**
    * Op removes all elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of StageClear
    */
@@ -5940,8 +5940,8 @@ public StageClear stageClear(List<Class<? extends TType>> dtypes, StageClear.Opt
    *  this op will block until it does.   This Op is optimized for
    *  performance.
    *
-   * @param index the index value
-   * @param dtypes the value of the dtypes property
+   * @param index The index value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of StagePeek
    */
@@ -5953,7 +5953,7 @@ public StagePeek stagePeek(Operand<TInt32> index, List<Class<? extends TType>> d
   /**
    * Op returns the number of elements in the underlying container.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of StageSize
    */
@@ -6211,7 +6211,7 @@ public StatelessWhile statelessWhile(Iterable<Operand<?>> input, ConcreteFunctio
    *  </ul>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code StopGradient} output and operands
    * @return a new instance of StopGradient
    */
@@ -6369,7 +6369,7 @@ public <T extends TType> StridedSlice<T> stridedSlice(Operand<T> input, Index...
    *  {@code ellipsis_mask must be a power of two (only one ellipsis)}
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param begin {@code begin[k]} specifies the offset into the {@code k}th range specification.
    *  The exact dimension this corresponds to will be determined by context.
    *  Out-of-bounds values will be silently clamped. If the {@code k}th bit of
@@ -6422,11 +6422,11 @@ public <T extends TType> StridedSliceAssign<T> stridedSliceAssign(Operand<T> ref
    *  shape must be exactly the shape produced by the slice of {@code ref}.
    *
    * @param <T> data type for {@code output_ref} output
-   * @param ref the ref value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param value the value value
+   * @param ref The ref value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param value The value value
    * @param options carries optional attribute values
    * @param <T> data type for {@code StridedSliceAssign} output and operands
    * @param <U> data type for {@code StridedSliceAssign} output and operands
@@ -6449,11 +6449,11 @@ public <T extends TType, U extends TNumber> StridedSliceAssign<T> stridedSliceAs
    *  shape of {@code StridedSlice}'s {@code input}.
    *
    * @param <U> data type for {@code output} output
-   * @param shape the shape value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param dy the dy value
+   * @param shape The shape value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param dy The dy value
    * @param options carries optional attribute values
    * @param <U> data type for {@code StridedSliceGrad} output and operands
    * @param <T> data type for {@code StridedSliceGrad} output and operands
@@ -6663,9 +6663,9 @@ public TensorArrayGradWithShape tensorArrayGradWithShape(Operand<? extends TType
    * The TensorArrayPack operation
    *
    * @param <T> data type for {@code value} output
-   * @param handle the handle value
-   * @param flowIn the flowIn value
-   * @param dtype the value of the dtype property
+   * @param handle The handle value
+   * @param flowIn The flowIn value
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code TensorArrayPack} output and operands
    * @return a new instance of TensorArrayPack
@@ -6680,7 +6680,7 @@ public <T extends TType> TensorArrayPack<T> tensorArrayPack(Operand<TString> han
    *
    * @param <T> data type for {@code value} output
    * @param handle The handle to a TensorArray.
-   * @param index the index value
+   * @param index The index value
    * @param flowIn A float scalar that enforces proper chaining of operations.
    * @param dtype The type of the elem that is returned.
    * @param <T> data type for {@code TensorArrayReadV3} output and operands
@@ -6745,9 +6745,9 @@ public TensorArraySplit tensorArraySplit(Operand<? extends TType> handle,
   /**
    * The TensorArrayUnpack operation
    *
-   * @param handle the handle value
-   * @param value the value value
-   * @param flowIn the flowIn value
+   * @param handle The handle value
+   * @param value The value value
+   * @param flowIn The flowIn value
    * @return a new instance of TensorArrayUnpack
    */
   public TensorArrayUnpack tensorArrayUnpack(Operand<TString> handle,
@@ -6783,10 +6783,10 @@ public TensorArrayWrite tensorArrayWrite(Operand<? extends TType> handle, Operan
    *  lengths: Output tensor containing sizes of the 0th dimension of tensors in the list, used for computing the gradient.
    *
    * @param <U> data type for {@code tensor} output
-   * @param inputHandle the inputHandle value
-   * @param elementShape the elementShape value
-   * @param leadingDims the leadingDims value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param elementShape The elementShape value
+   * @param leadingDims The leadingDims value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <U> data type for {@code TensorListConcatV2} output and operands
    * @return a new instance of TensorListConcat
    */
@@ -6799,9 +6799,9 @@ public <U extends TType> TensorListConcat<U> tensorListConcat(
   /**
    * The TensorListConcatLists operation
    *
-   * @param inputA the inputA value
-   * @param inputB the inputB value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputA The inputA value
+   * @param inputB The inputB value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListConcatLists} output and operands
    * @return a new instance of TensorListConcatLists
    */
@@ -6816,8 +6816,8 @@ public <T extends TType> TensorListConcatLists tensorListConcatLists(
    *  element_shape: the shape of elements of the list
    *
    * @param <T> data type for {@code element_shape} output
-   * @param inputHandle the inputHandle value
-   * @param shapeType the value of the shapeType property
+   * @param inputHandle The inputHandle value
+   * @param shapeType The value of the shapeType attribute
    * @param <T> data type for {@code TensorListElementShape} output and operands
    * @return a new instance of TensorListElementShape
    */
@@ -6832,8 +6832,8 @@ public <T extends TNumber> TensorListElementShape<T> tensorListElementShape(
    *  <p>tensor: The input tensor.
    *  output_handle: The list.
    *
-   * @param tensor the tensor value
-   * @param elementShape the elementShape value
+   * @param tensor The tensor value
+   * @param elementShape The elementShape value
    * @return a new instance of TensorListFromTensor
    */
   public TensorListFromTensor tensorListFromTensor(Operand<? extends TType> tensor,
@@ -6850,10 +6850,10 @@ public TensorListFromTensor tensorListFromTensor(Operand<? extends TType> tensor
    *  values: The tensor.
    *
    * @param <T> data type for {@code values} output
-   * @param inputHandle the inputHandle value
-   * @param indices the indices value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param indices The indices value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListGather} output and operands
    * @return a new instance of TensorListGather
    */
@@ -6867,10 +6867,10 @@ public <T extends TType> TensorListGather<T> tensorListGather(
    * The TensorListGetItem operation
    *
    * @param <T> data type for {@code item} output
-   * @param inputHandle the inputHandle value
-   * @param index the index value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param index The index value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListGetItem} output and operands
    * @return a new instance of TensorListGetItem
    */
@@ -6885,7 +6885,7 @@ public <T extends TType> TensorListGetItem<T> tensorListGetItem(
    *  input_handle: the input list
    *  length: the number of tensors in the list
    *
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of TensorListLength
    */
   public TensorListLength tensorListLength(Operand<? extends TType> inputHandle) {
@@ -6901,9 +6901,9 @@ public TensorListLength tensorListLength(Operand<? extends TType> inputHandle) {
    *  element_shape: the shape of the output tensor
    *
    * @param <T> data type for {@code tensor} output
-   * @param inputHandle the inputHandle value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListPopBack} output and operands
    * @return a new instance of TensorListPopBack
    */
@@ -6920,8 +6920,8 @@ public <T extends TType> TensorListPopBack<T> tensorListPopBack(
    *  element_dtype: the type of elements in the list.
    *  element_shape: a shape compatible with that of elements in the list.
    *
-   * @param inputHandle the inputHandle value
-   * @param tensor the tensor value
+   * @param inputHandle The inputHandle value
+   * @param tensor The tensor value
    * @return a new instance of TensorListPushBack
    */
   public TensorListPushBack tensorListPushBack(Operand<? extends TType> inputHandle,
@@ -6932,8 +6932,8 @@ public TensorListPushBack tensorListPushBack(Operand<? extends TType> inputHandl
   /**
    * The TensorListPushBackBatch operation
    *
-   * @param inputHandles the inputHandles value
-   * @param tensor the tensor value
+   * @param inputHandles The inputHandles value
+   * @param tensor The tensor value
    * @return a new instance of TensorListPushBackBatch
    */
   public TensorListPushBackBatch tensorListPushBackBatch(Operand<? extends TType> inputHandles,
@@ -6948,9 +6948,9 @@ public TensorListPushBackBatch tensorListPushBackBatch(Operand<? extends TType>
    *  handle: the output list
    *  element_dtype: the desired type of elements in the list.
    *
-   * @param elementShape the elementShape value
-   * @param numElements the numElements value
-   * @param elementDtype the value of the elementDtype property
+   * @param elementShape The elementShape value
+   * @param numElements The numElements value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <U> data type for {@code TensorListReserve} output and operands
    * @return a new instance of TensorListReserve
    */
@@ -6964,8 +6964,8 @@ public <U extends TType> TensorListReserve tensorListReserve(
    *  input_handle: the input list
    *  size: size of the output list
    *
-   * @param inputHandle the inputHandle value
-   * @param sizeOutput the sizeOutput value
+   * @param inputHandle The inputHandle value
+   * @param sizeOutput The sizeOutput value
    * @return a new instance of TensorListResize
    */
   public TensorListResize tensorListResize(Operand<? extends TType> inputHandle,
@@ -6986,10 +6986,10 @@ public TensorListResize tensorListResize(Operand<? extends TType> inputHandle,
    *  the largest index in indices.
    *  output_handle: The TensorList.
    *
-   * @param tensor the tensor value
-   * @param indices the indices value
-   * @param elementShape the elementShape value
-   * @param numElements the numElements value
+   * @param tensor The tensor value
+   * @param indices The indices value
+   * @param elementShape The elementShape value
+   * @param numElements The numElements value
    * @return a new instance of TensorListScatter
    */
   public TensorListScatter tensorListScatter(Operand<? extends TType> tensor,
@@ -7007,9 +7007,9 @@ public TensorListScatter tensorListScatter(Operand<? extends TType> tensor,
    *  indices: The indices used to index into the list.
    *  output_handle: The TensorList.
    *
-   * @param inputHandle the inputHandle value
-   * @param tensor the tensor value
-   * @param indices the indices value
+   * @param inputHandle The inputHandle value
+   * @param tensor The tensor value
+   * @param indices The indices value
    * @return a new instance of TensorListScatterIntoExistingList
    */
   public TensorListScatterIntoExistingList tensorListScatterIntoExistingList(
@@ -7021,9 +7021,9 @@ public TensorListScatterIntoExistingList tensorListScatterIntoExistingList(
   /**
    * The TensorListSetItem operation
    *
-   * @param inputHandle the inputHandle value
-   * @param index the index value
-   * @param item the item value
+   * @param inputHandle The inputHandle value
+   * @param index The index value
+   * @param item The item value
    * @return a new instance of TensorListSetItem
    */
   public TensorListSetItem tensorListSetItem(Operand<? extends TType> inputHandle,
@@ -7040,9 +7040,9 @@ public TensorListSetItem tensorListSetItem(Operand<? extends TType> inputHandle,
    *  lengths: Vector of sizes of the 0th dimension of tensors in the list.
    *  output_handle: The list.
    *
-   * @param tensor the tensor value
-   * @param elementShape the elementShape value
-   * @param lengths the lengths value
+   * @param tensor The tensor value
+   * @param elementShape The elementShape value
+   * @param lengths The lengths value
    * @return a new instance of TensorListSplit
    */
   public TensorListSplit tensorListSplit(Operand<? extends TType> tensor,
@@ -7058,9 +7058,9 @@ public TensorListSplit tensorListSplit(Operand<? extends TType> tensor,
    *  num_elements: optional. If not -1, the number of elements in the list.
    *
    * @param <T> data type for {@code tensor} output
-   * @param inputHandle the inputHandle value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code TensorListStack} output and operands
    * @return a new instance of TensorListStack
@@ -7076,9 +7076,9 @@ public <T extends TType> TensorListStack<T> tensorListStack(Operand<? extends TT
    *  output_handle: the map with value from given key removed
    *  key: the key of the value to be erased
    *
-   * @param inputHandle the inputHandle value
-   * @param key the key value
-   * @param valueDtype the value of the valueDtype property
+   * @param inputHandle The inputHandle value
+   * @param key The key value
+   * @param valueDtype The value of the valueDtype attribute
    * @param <U> data type for {@code TensorMapErase} output and operands
    * @return a new instance of TensorMapErase
    */
@@ -7093,8 +7093,8 @@ public <U extends TType> TensorMapErase tensorMapErase(Operand<? extends TType>
    *  key: the key to check
    *  has_key: whether the key is already in the map or not
    *
-   * @param inputHandle the inputHandle value
-   * @param key the key value
+   * @param inputHandle The inputHandle value
+   * @param key The key value
    * @return a new instance of TensorMapHasKey
    */
   public TensorMapHasKey tensorMapHasKey(Operand<? extends TType> inputHandle,
@@ -7109,9 +7109,9 @@ public TensorMapHasKey tensorMapHasKey(Operand<? extends TType> inputHandle,
    *  key: the key to be inserted
    *  value: the value to be inserted
    *
-   * @param inputHandle the inputHandle value
-   * @param key the key value
-   * @param value the value value
+   * @param inputHandle The inputHandle value
+   * @param key The key value
+   * @param value The value value
    * @return a new instance of TensorMapInsert
    */
   public TensorMapInsert tensorMapInsert(Operand<? extends TType> inputHandle,
@@ -7126,9 +7126,9 @@ public TensorMapInsert tensorMapInsert(Operand<? extends TType> inputHandle,
    *  value: the value found from the given key
    *
    * @param <U> data type for {@code value} output
-   * @param inputHandle the inputHandle value
-   * @param key the key value
-   * @param valueDtype the value of the valueDtype property
+   * @param inputHandle The inputHandle value
+   * @param key The key value
+   * @param valueDtype The value of the valueDtype attribute
    * @param <U> data type for {@code TensorMapLookup} output and operands
    * @return a new instance of TensorMapLookup
    */
@@ -7142,7 +7142,7 @@ public <U extends TType> TensorMapLookup<U> tensorMapLookup(Operand<? extends TT
    *  input_handle: the input map
    *  size: the number of tensors in the map
    *
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of TensorMapSize
    */
   public TensorMapSize tensorMapSize(Operand<? extends TType> inputHandle) {
@@ -7155,8 +7155,8 @@ public TensorMapSize tensorMapSize(Operand<? extends TType> inputHandle) {
    *  keys: the returned Tensor of all keys in the map
    *
    * @param <T> data type for {@code keys} output
-   * @param inputHandle the inputHandle value
-   * @param keyDtype the value of the keyDtype property
+   * @param inputHandle The inputHandle value
+   * @param keyDtype The value of the keyDtype attribute
    * @param <T> data type for {@code TensorMapStackKeys} output and operands
    * @return a new instance of TensorMapStackKeys
    */
@@ -7389,11 +7389,11 @@ public <T extends TType> TensorScatterNdUpdate<T> tensorScatterNdUpdate(Operand<
    *  must be exactly the shape produced by the slice of {@code input}.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param value the value value
+   * @param input The input value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param value The value value
    * @param options carries optional attribute values
    * @param <T> data type for {@code TensorStridedSliceUpdate} output and operands
    * @param <U> data type for {@code TensorStridedSliceUpdate} output and operands
@@ -7476,8 +7476,8 @@ public Timestamp timestamp() {
    *  padding value will be returned. The semantics are not the same as
    *  kth_order_statistic.
    *
-   * @param input the input value
-   * @param k the value of the k property
+   * @param input The input value
+   * @param k The value of the k attribute
    * @return a new instance of TopKUnique
    */
   public TopKUnique topKUnique(Operand<TFloat32> input, Long k) {
@@ -7492,8 +7492,8 @@ public TopKUnique topKUnique(Operand<TFloat32> input, Long k) {
    *  of K and the input size. NaNs are never returned. Subnormal numbers are flushed
    *  to zero.
    *
-   * @param input the input value
-   * @param k the value of the k property
+   * @param input The input value
+   * @param k The value of the k attribute
    * @return a new instance of TopKWithUnique
    */
   public TopKWithUnique topKWithUnique(Operand<TFloat32> input, Long k) {
@@ -7521,10 +7521,10 @@ public TopKWithUnique topKWithUnique(Operand<TFloat32> input, Long k) {
    *  be used as the shared name.
    *
    * @param <T> data type for {@code unbatched_tensor} output
-   * @param batchedTensor the batchedTensor value
-   * @param batchIndex the batchIndex value
-   * @param id the id value
-   * @param timeoutMicros the value of the timeoutMicros property
+   * @param batchedTensor The batchedTensor value
+   * @param batchIndex The batchIndex value
+   * @param id The id value
+   * @param timeoutMicros The value of the timeoutMicros attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code Unbatch} output and operands
    * @return a new instance of Unbatch
@@ -7551,10 +7551,10 @@ public <T extends TType> Unbatch<T> unbatch(Operand<T> batchedTensor, Operand<TI
    *  will be used as the shared name.
    *
    * @param <T> data type for {@code batched_grad} output
-   * @param originalInput the originalInput value
-   * @param batchIndex the batchIndex value
-   * @param grad the grad value
-   * @param id the id value
+   * @param originalInput The originalInput value
+   * @param batchIndex The batchIndex value
+   * @param grad The grad value
+   * @param id The id value
    * @param options carries optional attribute values
    * @param <T> data type for {@code UnbatchGrad} output and operands
    * @return a new instance of UnbatchGrad
@@ -7660,7 +7660,7 @@ public <T extends TType> Unique<T, TInt32> unique(Operand<T> x, Operand<? extend
    * @param x A {@code Tensor}.
    * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to
    *  find the unique elements.
-   * @param outIdx the value of the outIdx property
+   * @param outIdx The value of the outIdx attribute
    * @param <T> data type for {@code UniqueV2} output and operands
    * @param <V> data type for {@code UniqueV2} output and operands
    * @return a new instance of Unique
@@ -7774,7 +7774,7 @@ public <T extends TType> UniqueWithCounts<T, TInt32> uniqueWithCounts(Operand<T>
    * @param x A {@code Tensor}.
    * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to
    *  find the unique elements.
-   * @param outIdx the value of the outIdx property
+   * @param outIdx The value of the outIdx attribute
    * @param <T> data type for {@code UniqueWithCountsV2} output and operands
    * @param <V> data type for {@code UniqueWithCountsV2} output and operands
    * @return a new instance of UniqueWithCounts
@@ -7830,7 +7830,7 @@ public <T extends TNumber> UnravelIndex<T> unravelIndex(Operand<T> indices, Oper
    *
    * @param <T> data type for {@code output} output
    * @param value 1-D or higher, with {@code axis} dimension size equal to {@code num}.
-   * @param num the value of the num property
+   * @param num The value of the num attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code Unpack} output and operands
    * @return a new instance of Unstack
@@ -7845,7 +7845,7 @@ public <T extends TType> Unstack<T> unstack(Operand<T> value, Long num,
    *  The basic functionality is similar to dequeue with many fewer
    *  capabilities and options.  This Op is optimized for performance.
    *
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of Unstage
    */
@@ -7921,7 +7921,7 @@ public <T extends TType> Variable<T> variable(Shape shape, Class<T> dtype,
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of VariableShape, with default output types
    */
   public VariableShape<TInt32> variableShape(Operand<? extends TType> input) {
@@ -7938,8 +7938,8 @@ public VariableShape<TInt32> variableShape(Operand<? extends TType> input) {
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <T> data type for {@code VariableShape} output and operands
    * @return a new instance of VariableShape
    */
@@ -8008,7 +8008,7 @@ public <T extends TNumber> VariableShape<T> variableShape(Operand<? extends TTyp
    *                    [2, 1, 1]]
    *  </pre>
    *
-   * @param condition the condition value
+   * @param condition The condition value
    * @return a new instance of Where
    */
   public Where where(Operand<? extends TType> condition) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
index fee68e6042d..f4494844717 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
@@ -101,7 +101,7 @@ public final class QuantizationOps {
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param minRange The minimum scalar value possibly produced for the input.
    * @param maxRange The maximum scalar value possibly produced for the input.
    * @param options carries optional attribute values
@@ -159,7 +159,7 @@ public Dequantize<TFloat32> dequantize(Operand<? extends TNumber> input,
    *  </pre>
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param minRange The minimum scalar value possibly produced for the input.
    * @param maxRange The maximum scalar value possibly produced for the input.
    * @param dtype Type of the output tensor. Currently Dequantize supports float and bfloat16.
@@ -197,7 +197,7 @@ public <U extends TNumber> Dequantize<U> dequantize(Operand<? extends TNumber> i
    *  </ul>
    *  <p>Quantization is called fake since the output is still in floating point.
    *
-   * @param inputs the inputs value
+   * @param inputs The inputs value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxArgs
    */
@@ -246,9 +246,9 @@ public FakeQuantWithMinMaxArgsGradient fakeQuantWithMinMaxArgsGradient(
    *  <p>This operation has a gradient and thus allows for training {@code min} and {@code max}
    *  values.
    *
-   * @param inputs the inputs value
-   * @param min the min value
-   * @param max the max value
+   * @param inputs The inputs value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVars
    */
@@ -263,8 +263,8 @@ public FakeQuantWithMinMaxVars fakeQuantWithMinMaxVars(Operand<TFloat32> inputs,
    * @param gradients Backpropagated gradients above the FakeQuantWithMinMaxVars operation.
    * @param inputs Values passed as inputs to the FakeQuantWithMinMaxVars operation.
    *  min, max: Quantization interval, scalar floats.
-   * @param min the min value
-   * @param max the max value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVarsGradient
    */
@@ -301,9 +301,9 @@ public FakeQuantWithMinMaxVarsGradient fakeQuantWithMinMaxVarsGradient(
    *  <p>This operation has a gradient and thus allows for training {@code min} and {@code max}
    *  values.
    *
-   * @param inputs the inputs value
-   * @param min the min value
-   * @param max the max value
+   * @param inputs The inputs value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVarsPerChannel
    */
@@ -321,8 +321,8 @@ public FakeQuantWithMinMaxVarsPerChannel fakeQuantWithMinMaxVarsPerChannel(
    * @param inputs Values passed as inputs to the FakeQuantWithMinMaxVars operation, shape
    *  same as {@code gradients}.
    *  min, max: Quantization interval, floats of shape {@code [d]}.
-   * @param min the min value
-   * @param max the max value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVarsPerChannelGradient
    */
@@ -427,7 +427,7 @@ public FakeQuantWithMinMaxVarsPerChannelGradient fakeQuantWithMinMaxVarsPerChann
    *  set it to 0 for new uses.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param minRange The minimum value of the quantization range. This value may be adjusted by the
    *  op depending on other parameters. The adjusted value is written to {@code output_min}.
    *  If the {@code axis} attribute is specified, this must be a 1-D tensor whose size
@@ -436,7 +436,7 @@ public FakeQuantWithMinMaxVarsPerChannelGradient fakeQuantWithMinMaxVarsPerChann
    *  op depending on other parameters. The adjusted value is written to {@code output_max}.
    *  If the {@code axis} attribute is specified, this must be a 1-D tensor whose size
    *  matches the {@code axis} dimension of the input and output tensors.
-   * @param T the value of the T property
+   * @param T The value of the T attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeV2} output and operands
    * @return a new instance of Quantize
@@ -453,10 +453,10 @@ public <T extends TNumber> Quantize<T> quantize(Operand<TFloat32> input,
    *  tensor, so its value can change during training.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param inputMin the inputMin value
-   * @param inputMax the inputMax value
-   * @param numBits the numBits value
+   * @param input The input value
+   * @param inputMin The inputMin value
+   * @param inputMax The inputMax value
+   * @param numBits The numBits value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeAndDequantizeV3} output and operands
    * @return a new instance of QuantizeAndDequantize
@@ -473,10 +473,10 @@ public <T extends TNumber> QuantizeAndDequantize<T> quantizeAndDequantize(Operan
    *  tensor, so its value can change during training.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param inputMin the inputMin value
-   * @param inputMax the inputMax value
-   * @param numBits the numBits value
+   * @param input The input value
+   * @param inputMin The inputMin value
+   * @param inputMax The inputMax value
+   * @param numBits The numBits value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeAndDequantizeV3} output and operands
    * @return a new instance of QuantizeAndDequantizeV3
@@ -515,10 +515,10 @@ public <T extends TNumber> QuantizeAndDequantizeV4<T> quantizeAndDequantizeV4(Op
    *  or 0 otherwise.
    *
    * @param <T> data type for {@code input_backprop} output
-   * @param gradients the gradients value
-   * @param input the input value
-   * @param inputMin the inputMin value
-   * @param inputMax the inputMax value
+   * @param gradients The gradients value
+   * @param input The input value
+   * @param inputMin The inputMin value
+   * @param inputMax The inputMax value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeAndDequantizeV4Grad} output and operands
    * @return a new instance of QuantizeAndDequantizeV4Grad
@@ -552,7 +552,7 @@ public <T extends TNumber> QuantizeAndDequantizeV4Grad<T> quantizeAndDequantizeV
    *  minimal loss of accuracy.
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param inputMin The float value that the minimum quantized input value represents.
    * @param inputMax The float value that the maximum quantized input value represents.
    * @param outType The type of the output. Should be a lower bit depth than Tinput.
@@ -591,7 +591,7 @@ public <T extends TType> QuantizedConcat<T> quantizedConcat(Operand<TInt32> conc
    *  used to produce the {@code requested_output_min} and {@code requested_output_max} for
    *  {@code Requantize}.
    *
-   * @param input the input value
+   * @param input The input value
    * @param inputMin The float value that the minimum quantized input value represents.
    * @param inputMax The float value that the maximum quantized input value represents.
    * @return a new instance of RequantizationRange
@@ -611,7 +611,7 @@ public RequantizationRange requantizationRange(Operand<? extends TNumber> input,
    *  value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f.
    *
    * @param <U> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param inputMin The float value that the minimum quantized input value represents.
    * @param inputMax The float value that the maximum quantized input value represents.
    * @param requestedOutputMin The float value that the minimum quantized output value represents.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
index 70d2d8995d2..57b8727eb22 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
@@ -132,7 +132,7 @@ public Multinomial<TInt64> multinomial(Operand<? extends TNumber> logits,
    * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}.  Each slice {@code [i, :]}
    *  represents the unnormalized log probabilities for all classes.
    * @param numSamples 0-D.  Number of independent samples to draw for each row slice.
-   * @param outputDtype the value of the outputDtype property
+   * @param outputDtype The value of the outputDtype attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code Multinomial} output and operands
    * @return a new instance of Multinomial
@@ -224,7 +224,7 @@ public RandomPoisson<TInt64> randomPoisson(Operand<? extends TNumber> shape,
    *  distribution described by the shape parameters given in rate.
    * @param rate A tensor in which each scalar is a &quot;rate&quot; parameter describing the
    *  associated poisson distribution.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code RandomPoissonV2} output and operands
    * @return a new instance of RandomPoisson
@@ -326,11 +326,11 @@ public RecordInput recordInput(String filePattern, RecordInput.Options... option
    * The StatefulRandomBinomial operation
    *
    * @param <V> data type for {@code output} output
-   * @param resource the resource value
-   * @param algorithm the algorithm value
-   * @param shape the shape value
-   * @param counts the counts value
-   * @param probs the probs value
+   * @param resource The resource value
+   * @param algorithm The algorithm value
+   * @param shape The shape value
+   * @param counts The counts value
+   * @param probs The probs value
    * @param <U> data type for {@code StatefulRandomBinomial} output and operands
    * @return a new instance of StatefulRandomBinomial, with default output types
    */
@@ -344,12 +344,12 @@ public <U extends TNumber> StatefulRandomBinomial<TInt64> statefulRandomBinomial
    * The StatefulRandomBinomial operation
    *
    * @param <V> data type for {@code output} output
-   * @param resource the resource value
-   * @param algorithm the algorithm value
-   * @param shape the shape value
-   * @param counts the counts value
-   * @param probs the probs value
-   * @param dtype the value of the dtype property
+   * @param resource The resource value
+   * @param algorithm The algorithm value
+   * @param shape The shape value
+   * @param counts The counts value
+   * @param probs The probs value
+   * @param dtype The value of the dtype attribute
    * @param <V> data type for {@code StatefulRandomBinomial} output and operands
    * @param <U> data type for {@code StatefulRandomBinomial} output and operands
    * @return a new instance of StatefulRandomBinomial
@@ -416,7 +416,7 @@ public StatelessMultinomial<TInt64> statelessMultinomial(Operand<? extends TNumb
    *  represents the unnormalized log probabilities for all classes.
    * @param numSamples 0-D.  Number of independent samples to draw for each row slice.
    * @param seed 2 seeds (shape [2]).
-   * @param outputDtype the value of the outputDtype property
+   * @param outputDtype The value of the outputDtype attribute
    * @param <V> data type for {@code StatelessMultinomial} output and operands
    * @return a new instance of StatelessMultinomial
    */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java
index b18247b04eb..934fb0b645a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java
@@ -59,7 +59,7 @@ public final class SignalOps {
   /**
    * The BatchFFT operation
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchFft
    */
   public BatchFft batchFft(Operand<? extends TType> input) {
@@ -69,7 +69,7 @@ public BatchFft batchFft(Operand<? extends TType> input) {
   /**
    * The BatchFFT2D operation
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchFft2d
    */
   public BatchFft2d batchFft2d(Operand<? extends TType> input) {
@@ -79,7 +79,7 @@ public BatchFft2d batchFft2d(Operand<? extends TType> input) {
   /**
    * The BatchFFT3D operation
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchFft3d
    */
   public BatchFft3d batchFft3d(Operand<? extends TType> input) {
@@ -89,7 +89,7 @@ public BatchFft3d batchFft3d(Operand<? extends TType> input) {
   /**
    * The BatchIFFT operation
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchIfft
    */
   public BatchIfft batchIfft(Operand<? extends TType> input) {
@@ -99,7 +99,7 @@ public BatchIfft batchIfft(Operand<? extends TType> input) {
   /**
    * The BatchIFFT2D operation
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchIfft2d
    */
   public BatchIfft2d batchIfft2d(Operand<? extends TType> input) {
@@ -109,7 +109,7 @@ public BatchIfft2d batchIfft2d(Operand<? extends TType> input) {
   /**
    * The BatchIFFT3D operation
    *
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchIfft3d
    */
   public BatchIfft3d batchIfft3d(Operand<? extends TType> input) {
@@ -240,7 +240,7 @@ public Irfft<TFloat32> irfft(Operand<? extends TType> input, Operand<TInt32> fft
    * @param <U> data type for {@code output} output
    * @param input A complex tensor.
    * @param fftLength An int32 tensor of shape [1]. The FFT length.
-   * @param Treal the value of the Treal property
+   * @param Treal The value of the Treal attribute
    * @param <U> data type for {@code IRFFT} output and operands
    * @return a new instance of Irfft
    */
@@ -291,7 +291,7 @@ public Irfft2d<TFloat32> irfft2d(Operand<? extends TType> input, Operand<TInt32>
    * @param <U> data type for {@code output} output
    * @param input A complex tensor.
    * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension.
-   * @param Treal the value of the Treal property
+   * @param Treal The value of the Treal attribute
    * @param <U> data type for {@code IRFFT2D} output and operands
    * @return a new instance of Irfft2d
    */
@@ -342,7 +342,7 @@ public Irfft3d<TFloat32> irfft3d(Operand<? extends TType> input, Operand<TInt32>
    * @param <U> data type for {@code output} output
    * @param input A complex tensor.
    * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension.
-   * @param Treal the value of the Treal property
+   * @param Treal The value of the Treal attribute
    * @param <U> data type for {@code IRFFT3D} output and operands
    * @return a new instance of Irfft3d
    */
@@ -365,7 +365,7 @@ public <U extends TNumber> Irfft3d<U> irfft3d(Operand<? extends TType> input,
    * @param <U> data type for {@code output} output
    * @param input A float32 tensor.
    * @param fftLength An int32 tensor of shape [1]. The FFT length.
-   * @param Tcomplex the value of the Tcomplex property
+   * @param Tcomplex The value of the Tcomplex attribute
    * @param <U> data type for {@code RFFT} output and operands
    * @return a new instance of Rfft
    */
@@ -389,7 +389,7 @@ public <U extends TType> Rfft<U> rfft(Operand<? extends TNumber> input, Operand<
    * @param <U> data type for {@code output} output
    * @param input A float32 tensor.
    * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension.
-   * @param Tcomplex the value of the Tcomplex property
+   * @param Tcomplex The value of the Tcomplex attribute
    * @param <U> data type for {@code RFFT2D} output and operands
    * @return a new instance of Rfft2d
    */
@@ -413,7 +413,7 @@ public <U extends TType> Rfft2d<U> rfft2d(Operand<? extends TNumber> input,
    * @param <U> data type for {@code output} output
    * @param input A float32 tensor.
    * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension.
-   * @param Tcomplex the value of the Tcomplex property
+   * @param Tcomplex The value of the Tcomplex attribute
    * @param <U> data type for {@code RFFT3D} output and operands
    * @return a new instance of Rfft3d
    */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java
index 074cb7119d1..3a528a7dd78 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java
@@ -163,7 +163,7 @@ public AddSparseToTensorsMap addSparseToTensorsMap(Operand<TInt64> sparseIndices
    *  Dimension {@code n} contains values in a set, duplicates are allowed but ignored.
    * @param set2 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set1}.
    *  Dimension {@code n} contains values in a set, duplicates are allowed but ignored.
-   * @param setOperation the value of the setOperation property
+   * @param setOperation The value of the setOperation attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DenseToDenseSetOperation} output and operands
    * @return a new instance of DenseToDenseSetOperation
@@ -198,7 +198,7 @@ public <T extends TType> DenseToDenseSetOperation<T> denseToDenseSetOperation(Op
    * @param set2Shape 1D {@code Tensor}, shape of a {@code SparseTensor}. {@code set2_shape[0...n-1]} must
    *  be the same as the 1st {@code n-1} dimensions of {@code set1}, {@code result_shape[n]} is the
    *  max set size across {@code n-1} dimensions.
-   * @param setOperation the value of the setOperation property
+   * @param setOperation The value of the setOperation attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DenseToSparseSetOperation} output and operands
    * @return a new instance of DenseToSparseSetOperation
@@ -721,8 +721,8 @@ public <T extends TType> SparseFillEmptyRowsGrad<T> sparseFillEmptyRowsGrad(
    *  <p>The gradient computation of this operation will only take advantage of sparsity
    *  in the input gradient when that gradient comes from a Relu.
    *
-   * @param a the a value
-   * @param b the b value
+   * @param a The a value
+   * @param b The b value
    * @param options carries optional attribute values
    * @return a new instance of SparseMatMul
    */
@@ -902,7 +902,7 @@ public SparseReshape sparseReshape(Operand<TInt64> inputIndices, Operand<TInt64>
    *  dimension, selecting a subset of dimension 0, specified by {@code indices}.
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param <T> data type for {@code SparseSegmentMean} output and operands
@@ -941,7 +941,7 @@ public <T extends TNumber> SparseSegmentMeanGrad<T> sparseSegmentMeanGrad(Operan
    *  for an explanation of segments.
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param numSegments Should equal the number of distinct segment IDs.
@@ -960,7 +960,7 @@ public <T extends TNumber> SparseSegmentMeanWithNumSegments<T> sparseSegmentMean
    *  <p>See {@code tf.sparse.segment_sum} for usage examples.
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param <T> data type for {@code SparseSegmentSqrtN} output and operands
@@ -1000,7 +1000,7 @@ public <T extends TNumber> SparseSegmentSqrtNGrad<T> sparseSegmentSqrtNGrad(Oper
    *  for an explanation of segments.
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param numSegments Should equal the number of distinct segment IDs.
@@ -1043,7 +1043,7 @@ public <T extends TNumber> SparseSegmentSqrtNWithNumSegments<T> sparseSegmentSqr
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param <T> data type for {@code SparseSegmentSum} output and operands
@@ -1101,7 +1101,7 @@ public <T extends TNumber> SparseSegmentSumGrad<T> sparseSegmentSumGrad(Operand<
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param numSegments Should equal the number of distinct segment IDs.
@@ -1395,7 +1395,7 @@ public <U extends TType, T extends TNumber> SparseToDense<U> sparseToDense(
    * @param set2Shape 1D {@code Tensor}, shape of a {@code SparseTensor}. {@code set2_shape[0...n-1]} must
    *  be the same as {@code set1_shape[0...n-1]}, {@code set2_shape[n]} is the
    *  max set size across {@code 0...n-1} dimensions.
-   * @param setOperation the value of the setOperation property
+   * @param setOperation The value of the setOperation attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code SparseToSparseSetOperation} output and operands
    * @return a new instance of SparseToSparseSetOperation
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
index 77caa699358..3de4f5f14aa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
@@ -237,7 +237,7 @@ public StringLength stringLength(Operand<TString> input, StringLength.Options...
    *  sequence. Note that padding will never be greater than 'ngram_widths'-1
    *  regardless of this value. If {@code pad_width=-1}, then add {@code max(ngram_widths)-1}
    *  elements.
-   * @param preserveShortSequences the value of the preserveShortSequences property
+   * @param preserveShortSequences The value of the preserveShortSequences attribute
    * @param <T> data type for {@code StringNGrams} output and operands
    * @return a new instance of StringNGrams
    */
@@ -390,7 +390,7 @@ public <T extends TNumber> Substr substr(Operand<TString> input, Operand<T> pos,
    *  This functionality will be deprecated and it's recommended to use
    *  {@code tf.string_to_hash_bucket_fast()} or {@code tf.string_to_hash_bucket_strong()}.
    *
-   * @param stringTensor the stringTensor value
+   * @param stringTensor The stringTensor value
    * @param numBuckets The number of buckets.
    * @return a new instance of ToHashBucket
    */
@@ -474,7 +474,7 @@ public ToHashBucketStrong toHashBucketStrong(Operand<TString> input, Long numBuc
    *  </blockquote>
    *
    * @param <T> data type for {@code output} output
-   * @param stringTensor the stringTensor value
+   * @param stringTensor The stringTensor value
    * @return a new instance of ToNumber, with default output types
    */
   public ToNumber<TFloat32> toNumber(Operand<TString> stringTensor) {
@@ -497,7 +497,7 @@ public ToNumber<TFloat32> toNumber(Operand<TString> stringTensor) {
    *  </blockquote>
    *
    * @param <T> data type for {@code output} output
-   * @param stringTensor the stringTensor value
+   * @param stringTensor The stringTensor value
    * @param outType The numeric type to interpret each string in {@code string_tensor} as.
    * @param <T> data type for {@code StringToNumber} output and operands
    * @return a new instance of ToNumber
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java
index 2bfd21c438e..87f224c65f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java
@@ -62,11 +62,11 @@ public final class TpuOps {
    *  used to look up the program in the compilation cache.
    *  'may_modify_variables' indicates whether variables may be modified.
    *
-   * @param dynamicShapes the dynamicShapes value
-   * @param guaranteedConstants the guaranteedConstants value
-   * @param numComputations the value of the numComputations property
-   * @param function the value of the function property
-   * @param metadata the value of the metadata property
+   * @param dynamicShapes The dynamicShapes value
+   * @param guaranteedConstants The guaranteedConstants value
+   * @param numComputations The value of the numComputations attribute
+   * @param function The value of the function attribute
+   * @param metadata The value of the metadata attribute
    * @return a new instance of Compile
    */
   public Compile compile(Iterable<Operand<TInt64>> dynamicShapes,
@@ -81,7 +81,7 @@ public Compile compile(Iterable<Operand<TInt64>> dynamicShapes,
    *  pending device interactions fail.
    *  <p>'compilation_status' is a serialized CompilationResultProto.
    *
-   * @param compilationStatus the compilationStatus value
+   * @param compilationStatus The compilationStatus value
    * @return a new instance of CompileSucceededAssert
    */
   public CompileSucceededAssert compileSucceededAssert(Operand<TString> compilationStatus) {
@@ -92,9 +92,9 @@ public CompileSucceededAssert compileSucceededAssert(Operand<TString> compilatio
    * Op that loads and executes a TPU program on a TPU device.
    *  For the internal use of the distributed TPU compiler.
    *
-   * @param args the args value
-   * @param key the key value
-   * @param Tresults the value of the Tresults property
+   * @param args The args value
+   * @param key The key value
+   * @param Tresults The value of the Tresults attribute
    * @return a new instance of Execute
    */
   public Execute execute(Iterable<Operand<?>> args, Operand<TString> key,
@@ -112,11 +112,11 @@ public Execute execute(Iterable<Operand<?>> args, Operand<TString> key,
    *  program outputs are consumed by these variables will not appear in the op
    *  output. For the internal use of the distributed TPU compiler.
    *
-   * @param args the args value
-   * @param key the key value
-   * @param Tresults the value of the Tresults property
-   * @param deviceVarReadsIndices the value of the deviceVarReadsIndices property
-   * @param deviceVarUpdatesIndices the value of the deviceVarUpdatesIndices property
+   * @param args The args value
+   * @param key The key value
+   * @param Tresults The value of the Tresults attribute
+   * @param deviceVarReadsIndices The value of the deviceVarReadsIndices attribute
+   * @param deviceVarUpdatesIndices The value of the deviceVarUpdatesIndices attribute
    * @return a new instance of ExecuteAndUpdateVariables
    */
   public ExecuteAndUpdateVariables executeAndUpdateVariables(Iterable<Operand<?>> args,
@@ -145,7 +145,7 @@ public <T extends TType> PartitionedInput<T> partitionedInput(Iterable<Operand<T
    *
    * @param <T> data type for {@code output} output
    * @param inputs A tensor which represents the full shape of partitioned tensors.
-   * @param numSplits the value of the numSplits property
+   * @param numSplits The value of the numSplits attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code TPUPartitionedOutput} output and operands
    * @return a new instance of PartitionedOutput
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java
index d12c25a5ac8..7d610592959 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java
@@ -340,7 +340,7 @@ public <T extends TType> ApplyCenteredRmsProp<T> applyCenteredRmsProp(Operand<T>
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code ApplyFtrlV2} output and operands
@@ -474,7 +474,7 @@ public <T extends TType> ApplyProximalGradientDescent<T> applyProximalGradientDe
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param options carries optional attribute values
@@ -610,7 +610,7 @@ public MergeV2Checkpoints mergeV2Checkpoints(Operand<TString> checkpointPrefixes
    * @param wOut output word embedding.
    * @param examples A vector of word ids.
    * @param labels A vector of word ids.
-   * @param lr the lr value
+   * @param lr The lr value
    * @param vocabCount Count of words in the vocabulary.
    * @param numNegativeSamples Number of negative samples per example.
    * @return a new instance of NegTrain
@@ -825,7 +825,7 @@ public <T extends TType> ResourceApplyCenteredRmsProp resourceApplyCenteredRmsPr
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code ResourceApplyFtrlV2} output and operands
@@ -978,7 +978,7 @@ public <T extends TType> ResourceApplyProximalGradientDescent resourceApplyProxi
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param options carries optional attribute values
@@ -995,7 +995,7 @@ public <T extends TType> ResourceApplyRmsProp resourceApplyRmsProp(Operand<? ext
   /**
    * var: Should be from a Variable().
    *
-   * @param var the var value
+   * @param var The var value
    * @param accum Should be from a Variable().
    * @param accumUpdate : Should be from a Variable().
    * @param lr Learning rate. Must be a scalar.
@@ -1082,7 +1082,7 @@ public <T extends TType> ResourceSparseApplyAdagradDa resourceSparseApplyAdagrad
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -1117,7 +1117,7 @@ public <T extends TType> ResourceSparseApplyCenteredRmsProp resourceSparseApplyC
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code ResourceSparseApplyFtrlV2} output and operands
@@ -1244,7 +1244,7 @@ public <T extends TType> ResourceSparseApplyProximalGradientDescent resourceSpar
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -1396,7 +1396,7 @@ public SdcaShrinkL1 sdcaShrinkL1(Iterable<Operand<TFloat32>> weights, Float l1,
    * var: Should be from a Variable().
    *
    * @param <T> data type for {@code out} output
-   * @param var the var value
+   * @param var The var value
    * @param accum Should be from a Variable().
    * @param accumUpdate : Should be from a Variable().
    * @param lr Learning rate. Must be a scalar.
@@ -1461,7 +1461,7 @@ public <T extends TType> SparseApplyAdagradDa<T> sparseApplyAdagradDa(Operand<T>
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -1496,7 +1496,7 @@ public <T extends TType> SparseApplyCenteredRmsProp<T> sparseApplyCenteredRmsPro
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code SparseApplyFtrlV2} output and operands
@@ -1599,7 +1599,7 @@ public <T extends TType> SparseApplyProximalGradientDescent<T> sparseApplyProxim
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -1646,8 +1646,8 @@ public SymbolicGradient symbolicGradient(Iterable<Operand<?>> input,
    *  each repeated tile of {@code input} into {@code output}.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param multiples the multiples value
+   * @param input The input value
+   * @param multiples The multiples value
    * @param <T> data type for {@code TileGrad} output and operands
    * @return a new instance of TileGrad
    */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
index 9318cd63614..8c087f20307 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
@@ -97,7 +97,7 @@ public <T extends TType> BroadcastHelper<T> broadcastHelper(Operand<T> lhs, Oper
    * Operator that connects the output of an XLA computation to other consumer graph nodes.
    *
    * @param <T> data type for {@code outputs} output
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code XlaClusterOutput} output and operands
    * @return a new instance of ClusterOutput
    */
@@ -184,7 +184,7 @@ public <V extends TType> Dot<V> dot(Operand<? extends TType> lhs, Operand<? exte
    *  dimension. Each value must be strictly greater than zero, and start + size
    *  must be less than or equal to the size of the dimension to avoid
    *  implementation defined behavior.
-   * @param sizeIndices the sizeIndices value
+   * @param sizeIndices The sizeIndices value
    * @param <T> data type for {@code XlaDynamicSlice} output and operands
    * @param <U> data type for {@code XlaDynamicSlice} output and operands
    * @return a new instance of DynamicSlice
@@ -223,9 +223,9 @@ public <T extends TType> DynamicUpdateSlice<T> dynamicUpdateSlice(Operand<T> inp
    *  transpose operations as tf.einsum does.
    *
    * @param <T> data type for {@code product} output
-   * @param a the a value
-   * @param b the b value
-   * @param equation the value of the equation property
+   * @param a The a value
+   * @param b The b value
+   * @param equation The value of the equation attribute
    * @param <T> data type for {@code XlaEinsum} output and operands
    * @return a new instance of Einsum
    */
@@ -262,7 +262,7 @@ public <T extends TType, U extends TNumber> Gather<T> gather(Operand<T> operand,
    *  whose types are the same as what else_branch returns.
    * @param elseBranch A function takes 'inputs' and returns a list of tensors.
    *  whose types are the same as what then_branch returns.
-   * @param Tout the value of the Tout property
+   * @param Tout The value of the Tout attribute
    * @return a new instance of If
    */
   public If ifOp(Operand<? extends TType> cond, Iterable<Operand<?>> inputs,
@@ -355,8 +355,8 @@ public <T extends TType> Reduce<T> reduce(Operand<T> input, Operand<T> initValue
    * @param initValue a scalar representing the initial value for the reduction
    * @param windowDimensions the shape of the window
    * @param windowStrides the inter-window strides
-   * @param baseDilations the baseDilations value
-   * @param windowDilations the windowDilations value
+   * @param baseDilations The baseDilations value
+   * @param windowDilations The windowDilations value
    * @param padding the padding to apply at the start and end of each input dimensions
    * @param computation a reducer function to apply
    * @param <T> data type for {@code XlaReduceWindow} output and operands
@@ -378,8 +378,8 @@ public <T extends TType, U extends TNumber> ReduceWindow<T> reduceWindow(Operand
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param dimIndex the dimIndex value
+   * @param input The input value
+   * @param dimIndex The dimIndex value
    * @param <T> data type for {@code XlaRemoveDynamicDimensionSize} output and operands
    * @return a new instance of RemoveDynamicDimensionSize
    */
@@ -488,9 +488,9 @@ public Send send(Operand<? extends TType> tensor, String tensorName) {
    *  </pre>
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param dimIndex the dimIndex value
-   * @param sizeOutput the sizeOutput value
+   * @param input The input value
+   * @param dimIndex The dimIndex value
+   * @param sizeOutput The sizeOutput value
    * @param <T> data type for {@code XlaSetDynamicDimensionSize} output and operands
    * @return a new instance of SetDynamicDimensionSize
    */
@@ -503,7 +503,7 @@ public <T extends TType> SetDynamicDimensionSize<T> setDynamicDimensionSize(Oper
    * An op which shards the input based on the given sharding attribute.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code XlaSharding} output and operands
    * @return a new instance of Sharding
@@ -535,8 +535,8 @@ public <T extends TType> Sort<T> sort(Operand<T> input) {
    *  shape is not evenly partitionable, the padding region will be masked with 0s.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param manualSharding the value of the manualSharding property
+   * @param input The input value
+   * @param manualSharding The value of the manualSharding attribute
    * @param <T> data type for {@code XlaSpmdFullToShardShape} output and operands
    * @return a new instance of SpmdFullToShardShape
    */
@@ -552,9 +552,9 @@ public <T extends TType> SpmdFullToShardShape<T> spmdFullToShardShape(Operand<T>
    *  used by manual partitioning.
    *
    * @param <T> data type for {@code output} output
-   * @param input the input value
-   * @param manualSharding the value of the manualSharding property
-   * @param fullShape the value of the fullShape property
+   * @param input The input value
+   * @param manualSharding The value of the manualSharding attribute
+   * @param fullShape The value of the fullShape attribute
    * @param <T> data type for {@code XlaSpmdShardToFullShape} output and operands
    * @return a new instance of SpmdShardToFullShape
    */
@@ -627,11 +627,11 @@ public XlaHostCompute xlaHostCompute(Iterable<Operand<?>> inputs,
   /**
    * XLA Launch Op. For use by the XLA JIT only.
    *
-   * @param constants the constants value
-   * @param args the args value
-   * @param resources the resources value
-   * @param Tresults the value of the Tresults property
-   * @param function the value of the function property
+   * @param constants The constants value
+   * @param args The args value
+   * @param resources The resources value
+   * @param Tresults The value of the Tresults attribute
+   * @param function The value of the function attribute
    * @return a new instance of XlaLaunch
    */
   public XlaLaunch xlaLaunch(Iterable<Operand<?>> constants, Iterable<Operand<?>> args,
@@ -648,9 +648,9 @@ public XlaLaunch xlaLaunch(Iterable<Operand<?>> constants, Iterable<Operand<?>>
    *  key: A unique identifier for this region used to match up host transfers.
    *
    * @param <T> data type for {@code output} output
-   * @param Toutput the value of the Toutput property
-   * @param shape the value of the shape property
-   * @param key the value of the key property
+   * @param Toutput The value of the Toutput attribute
+   * @param shape The value of the shape attribute
+   * @param key The value of the key attribute
    * @param <T> data type for {@code XlaRecvFromHost} output and operands
    * @return a new instance of XlaRecvFromHost
    */
@@ -665,8 +665,8 @@ public <T extends TType> XlaRecvFromHost<T> xlaRecvFromHost(Class<T> Toutput, Sh
    *  Tinput: element type for input.
    *  key: A unique identifier for this region used to match up host transfers.
    *
-   * @param input the input value
-   * @param key the value of the key property
+   * @param input The input value
+   * @param key The value of the key attribute
    * @return a new instance of XlaSendToHost
    */
   public XlaSendToHost xlaSendToHost(Operand<? extends TType> input, String key) {
@@ -679,8 +679,8 @@ public XlaSendToHost xlaSendToHost(Operand<? extends TType> input, String key) {
    *      returns the same value.
    *  </pre>
    *
-   * @param input the input value
-   * @param bound the bound value
+   * @param input The input value
+   * @param bound The bound value
    * @return a new instance of XlaSetBound
    */
   public XlaSetBound xlaSetBound(Operand<TInt32> input, Operand<TInt32> bound) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_CancellationManager.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_CancellationManager.java
new file mode 100644
index 00000000000..d98765a5dad
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_CancellationManager.java
@@ -0,0 +1,21 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// -----------------------------------------------------------------------------
+// Cancellation APIs.
+
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_CancellationManager extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_CancellationManager() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_CancellationManager(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_Executor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_Executor.java
new file mode 100644
index 00000000000..cad647e262b
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_Executor.java
@@ -0,0 +1,20 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// -----------------------------------------------------------------------------
+// Eager Executor APIs.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_Executor extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_Executor() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_Executor(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge0.java
new file mode 100644
index 00000000000..70711d9a4d3
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge0.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Bool Gauge without label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringBoolGauge0 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringBoolGauge0() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringBoolGauge0(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge1.java
new file mode 100644
index 00000000000..e29294aae88
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge1.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Bool Gauge with 1 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringBoolGauge1 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringBoolGauge1() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringBoolGauge1(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge2.java
new file mode 100644
index 00000000000..7dbc30d3ecf
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGauge2.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Bool Gauge with 2 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringBoolGauge2 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringBoolGauge2() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringBoolGauge2(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGaugeCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGaugeCell.java
new file mode 100644
index 00000000000..0b2c5005aec
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringBoolGaugeCell.java
@@ -0,0 +1,18 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringBoolGaugeCell extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringBoolGaugeCell() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringBoolGaugeCell(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter0.java
new file mode 100644
index 00000000000..38d10d187e6
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter0.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Counter without label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringCounter0 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringCounter0() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringCounter0(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter1.java
new file mode 100644
index 00000000000..6fd51182aaf
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter1.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Counter with 1 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringCounter1 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringCounter1() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringCounter1(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter2.java
new file mode 100644
index 00000000000..5f6b3cb65d8
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounter2.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Counter with 2 labels.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringCounter2 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringCounter2() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringCounter2(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounterCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounterCell.java
new file mode 100644
index 00000000000..4d06bf772df
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringCounterCell.java
@@ -0,0 +1,23 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// TODO(fishx): Move these monitoring APIs into a separate file.
+// -----------------------------------------------------------------------------
+// Monitoring Counter APIs.
+// These APIs de-templated monitoring Counter for swig.
+
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringCounterCell extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringCounterCell() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringCounterCell(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge0.java
new file mode 100644
index 00000000000..07644a51b23
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge0.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Int Gauge without label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringIntGauge0 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringIntGauge0() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringIntGauge0(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge1.java
new file mode 100644
index 00000000000..8382f6e8ef0
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge1.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Int Gauge with 1 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringIntGauge1 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringIntGauge1() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringIntGauge1(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge2.java
new file mode 100644
index 00000000000..699f99004a4
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGauge2.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Int Gauge with 2 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringIntGauge2 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringIntGauge2() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringIntGauge2(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGaugeCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGaugeCell.java
new file mode 100644
index 00000000000..4aa9d8255b1
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringIntGaugeCell.java
@@ -0,0 +1,22 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// -----------------------------------------------------------------------------
+// Monitoring Gauge APIs.
+// These APIs de-templated monitoring Gauge for swig.
+
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringIntGaugeCell extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringIntGaugeCell() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringIntGaugeCell(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler0.java
new file mode 100644
index 00000000000..d2a07d4729d
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler0.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Sampler without label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringSampler0 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringSampler0() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringSampler0(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler1.java
new file mode 100644
index 00000000000..20480b01d90
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler1.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Sampler with 1 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringSampler1 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringSampler1() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringSampler1(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler2.java
new file mode 100644
index 00000000000..93878dc287c
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSampler2.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for Sampler with 2 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringSampler2 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringSampler2() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringSampler2(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSamplerCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSamplerCell.java
new file mode 100644
index 00000000000..f938c4a2b05
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringSamplerCell.java
@@ -0,0 +1,22 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// -----------------------------------------------------------------------------
+// Monitoring Sampler APIs.
+// These APIs de-templated monitoring Sampler for swig.
+
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringSamplerCell extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringSamplerCell() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringSamplerCell(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge0.java
new file mode 100644
index 00000000000..87828c7df42
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge0.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for String Gauge without label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringStringGauge0 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringStringGauge0() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringStringGauge0(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge1.java
new file mode 100644
index 00000000000..5b462d7d1ab
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge1.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for String Gauge with 1 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringStringGauge1 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringStringGauge1() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringStringGauge1(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge2.java
new file mode 100644
index 00000000000..5098284180f
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGauge2.java
@@ -0,0 +1,19 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for String Gauge with 2 label.
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringStringGauge2 extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringStringGauge2() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringStringGauge2(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGaugeCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGaugeCell.java
new file mode 100644
index 00000000000..ceb811e6da3
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_MonitoringStringGaugeCell.java
@@ -0,0 +1,18 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_MonitoringStringGaugeCell extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_MonitoringStringGaugeCell() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_MonitoringStringGaugeCell(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_OpAttrs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_OpAttrs.java
new file mode 100644
index 00000000000..340dcc8feec
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/TFE_OpAttrs.java
@@ -0,0 +1,26 @@
+// Targeted by JavaCPP version 1.5.4: DO NOT EDIT THIS FILE
+
+package org.tensorflow.internal.c_api;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.*;
+
+
+// APIs for generically dealing with op attributes (e.g. when forwarding them
+// through custom device implementations).
+//
+// TODO(allenl): Currently these are black boxes, but we should have some way to
+// inspect values. This would let people e.g. copy over most attributes and then
+// modify some based on their values.
+
+// A reference to an op's name -> attribute mapping
+@Opaque @Properties(inherit = org.tensorflow.internal.c_api.presets.tensorflow.class)
+public class TFE_OpAttrs extends Pointer {
+    /** Empty constructor. Calls {@code super((Pointer)null)}. */
+    public TFE_OpAttrs() { super((Pointer)null); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public TFE_OpAttrs(Pointer p) { super(p); }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java
index d40163dc22d..d1eefb1a9a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/internal/c_api/global/tensorflow.java
@@ -4744,4 +4744,626 @@ public static native void TFE_ContextExportRunMetadata(TFE_Context ctx,
 // #endif  // TENSORFLOW_C_EAGER_C_API_H_
 
 
+// Parsed from tensorflow/c/eager/c_api_experimental.h
+
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+// #ifndef TENSORFLOW_C_EAGER_C_API_EXPERIMENTAL_H_
+// #define TENSORFLOW_C_EAGER_C_API_EXPERIMENTAL_H_
+
+// #include "tensorflow/c/c_api.h"
+// #include "tensorflow/c/eager/c_api.h"
+
+// #ifdef __cplusplus
+// #endif
+
+// Resets `op_to_reset` with `op_or_function_name` and `raw_device_name`. This
+// is for performance optimization by reusing an exiting unused op rather than
+// creating a new op every time. If `raw_device_name` is `NULL` or empty, it
+// does not set the device name. If it's not `NULL`, then it attempts to parse
+// and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster
+// than separately calling it because if the existing op has the same
+// `raw_device_name`, it skips parsing and just leave as it is.
+public static native void TFE_OpReset(TFE_Op op_to_reset,
+                                       @Cast("const char*") BytePointer op_or_function_name,
+                                       @Cast("const char*") BytePointer raw_device_name,
+                                       TF_Status status);
+public static native void TFE_OpReset(TFE_Op op_to_reset,
+                                       String op_or_function_name,
+                                       String raw_device_name,
+                                       TF_Status status);
+
+// Enables only graph collection in RunMetadata on the functions executed from
+// this context.
+public static native void TFE_ContextEnableGraphCollection(TFE_Context ctx);
+
+// Disables only graph collection in RunMetadata on the functions executed from
+// this context.
+public static native void TFE_ContextDisableGraphCollection(TFE_Context ctx);
+// Targeting ../TFE_MonitoringCounterCell.java
+
+
+
+// Atomically increments the value of the cell. The value must be non-negative.
+public static native void TFE_MonitoringCounterCellIncrementBy(
+    TFE_MonitoringCounterCell cell, @Cast("int64_t") long value);
+
+// Retrieves the current value of the cell.
+public static native @Cast("int64_t") long TFE_MonitoringCounterCellValue(
+    TFE_MonitoringCounterCell cell);
+// Targeting ../TFE_MonitoringCounter0.java
+
+
+// Returns a new Counter metric object. The caller should manage lifetime of
+// the object. Using duplicate metric name will crash the program with fatal
+// error.
+public static native TFE_MonitoringCounter0 TFE_MonitoringNewCounter0(
+    @Cast("const char*") BytePointer name, TF_Status status, @Cast("const char*") BytePointer description);
+public static native TFE_MonitoringCounter0 TFE_MonitoringNewCounter0(
+    String name, TF_Status status, String description);
+// Deletes the Counter object.
+public static native void TFE_MonitoringDeleteCounter0(
+    TFE_MonitoringCounter0 counter);
+// Retrieves the cell from the Counter object. The Counter object will manage
+// lifetime of the cell.
+public static native TFE_MonitoringCounterCell TFE_MonitoringGetCellCounter0(
+    TFE_MonitoringCounter0 counter);
+// Targeting ../TFE_MonitoringCounter1.java
+
+
+public static native TFE_MonitoringCounter1 TFE_MonitoringNewCounter1(
+    @Cast("const char*") BytePointer name, TF_Status status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringCounter1 TFE_MonitoringNewCounter1(
+    String name, TF_Status status, String description,
+    String label1);
+public static native void TFE_MonitoringDeleteCounter1(
+    TFE_MonitoringCounter1 counter);
+public static native TFE_MonitoringCounterCell TFE_MonitoringGetCellCounter1(
+    TFE_MonitoringCounter1 counter, @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringCounterCell TFE_MonitoringGetCellCounter1(
+    TFE_MonitoringCounter1 counter, String label1);
+// Targeting ../TFE_MonitoringCounter2.java
+
+
+public static native TFE_MonitoringCounter2 TFE_MonitoringNewCounter2(
+    @Cast("const char*") BytePointer name, TF_Status status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringCounter2 TFE_MonitoringNewCounter2(
+    String name, TF_Status status, String description,
+    String label1, String label2);
+public static native void TFE_MonitoringDeleteCounter2(
+    TFE_MonitoringCounter2 counter);
+public static native TFE_MonitoringCounterCell TFE_MonitoringGetCellCounter2(
+    TFE_MonitoringCounter2 counter, @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringCounterCell TFE_MonitoringGetCellCounter2(
+    TFE_MonitoringCounter2 counter, String label1, String label2);
+// Targeting ../TFE_MonitoringIntGaugeCell.java
+
+
+
+// Atomically set the value of the cell.
+public static native void TFE_MonitoringIntGaugeCellSet(
+    TFE_MonitoringIntGaugeCell cell, @Cast("int64_t") long value);
+
+// Retrieves the current value of the cell.
+public static native @Cast("int64_t") long TFE_MonitoringIntGaugeCellValue(
+    TFE_MonitoringIntGaugeCell cell);
+// Targeting ../TFE_MonitoringIntGauge0.java
+
+
+public static native TFE_MonitoringIntGauge0 TFE_MonitoringNewIntGauge0(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description);
+public static native TFE_MonitoringIntGauge0 TFE_MonitoringNewIntGauge0(
+    String name, TF_Status out_status, String description);
+public static native void TFE_MonitoringDeleteIntGauge0(
+    TFE_MonitoringIntGauge0 gauge);
+public static native TFE_MonitoringIntGaugeCell TFE_MonitoringGetCellIntGauge0(TFE_MonitoringIntGauge0 gauge);
+// Targeting ../TFE_MonitoringIntGauge1.java
+
+
+public static native TFE_MonitoringIntGauge1 TFE_MonitoringNewIntGauge1(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringIntGauge1 TFE_MonitoringNewIntGauge1(
+    String name, TF_Status out_status, String description,
+    String label1);
+public static native void TFE_MonitoringDeleteIntGauge1(
+    TFE_MonitoringIntGauge1 gauge);
+public static native TFE_MonitoringIntGaugeCell TFE_MonitoringGetCellIntGauge1(TFE_MonitoringIntGauge1 gauge,
+                               @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringIntGaugeCell TFE_MonitoringGetCellIntGauge1(TFE_MonitoringIntGauge1 gauge,
+                               String label1);
+// Targeting ../TFE_MonitoringIntGauge2.java
+
+
+public static native TFE_MonitoringIntGauge2 TFE_MonitoringNewIntGauge2(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringIntGauge2 TFE_MonitoringNewIntGauge2(
+    String name, TF_Status out_status, String description,
+    String label1, String label2);
+public static native void TFE_MonitoringDeleteIntGauge2(
+    TFE_MonitoringIntGauge2 gauge);
+public static native TFE_MonitoringIntGaugeCell TFE_MonitoringGetCellIntGauge2(TFE_MonitoringIntGauge2 gauge,
+                               @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringIntGaugeCell TFE_MonitoringGetCellIntGauge2(TFE_MonitoringIntGauge2 gauge,
+                               String label1, String label2);
+// Targeting ../TFE_MonitoringStringGaugeCell.java
+
+
+public static native void TFE_MonitoringStringGaugeCellSet(
+    TFE_MonitoringStringGaugeCell cell, @Cast("const char*") BytePointer value);
+public static native void TFE_MonitoringStringGaugeCellSet(
+    TFE_MonitoringStringGaugeCell cell, String value);
+// Retrieves the string value and saves it in buffer.
+public static native void TFE_MonitoringStringGaugeCellValue(
+    TFE_MonitoringStringGaugeCell cell, TF_Buffer buf);
+// Targeting ../TFE_MonitoringStringGauge0.java
+
+
+public static native TFE_MonitoringStringGauge0 TFE_MonitoringNewStringGauge0(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description);
+public static native TFE_MonitoringStringGauge0 TFE_MonitoringNewStringGauge0(
+    String name, TF_Status out_status, String description);
+public static native void TFE_MonitoringDeleteStringGauge0(
+    TFE_MonitoringStringGauge0 gauge);
+public static native TFE_MonitoringStringGaugeCell TFE_MonitoringGetCellStringGauge0(TFE_MonitoringStringGauge0 gauge);
+// Targeting ../TFE_MonitoringStringGauge1.java
+
+
+public static native TFE_MonitoringStringGauge1 TFE_MonitoringNewStringGauge1(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringStringGauge1 TFE_MonitoringNewStringGauge1(
+    String name, TF_Status out_status, String description,
+    String label1);
+public static native void TFE_MonitoringDeleteStringGauge1(
+    TFE_MonitoringStringGauge1 gauge);
+public static native TFE_MonitoringStringGaugeCell TFE_MonitoringGetCellStringGauge1(TFE_MonitoringStringGauge1 gauge,
+                                  @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringStringGaugeCell TFE_MonitoringGetCellStringGauge1(TFE_MonitoringStringGauge1 gauge,
+                                  String label1);
+// Targeting ../TFE_MonitoringStringGauge2.java
+
+
+public static native TFE_MonitoringStringGauge2 TFE_MonitoringNewStringGauge2(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringStringGauge2 TFE_MonitoringNewStringGauge2(
+    String name, TF_Status out_status, String description,
+    String label1, String label2);
+public static native void TFE_MonitoringDeleteStringGauge2(
+    TFE_MonitoringStringGauge2 gauge);
+public static native TFE_MonitoringStringGaugeCell TFE_MonitoringGetCellStringGauge2(TFE_MonitoringStringGauge2 gauge,
+                                  @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringStringGaugeCell TFE_MonitoringGetCellStringGauge2(TFE_MonitoringStringGauge2 gauge,
+                                  String label1, String label2);
+// Targeting ../TFE_MonitoringBoolGaugeCell.java
+
+
+public static native void TFE_MonitoringBoolGaugeCellSet(
+    TFE_MonitoringBoolGaugeCell cell, @Cast("bool") boolean value);
+public static native @Cast("bool") boolean TFE_MonitoringBoolGaugeCellValue(
+    TFE_MonitoringBoolGaugeCell cell);
+// Targeting ../TFE_MonitoringBoolGauge0.java
+
+
+public static native TFE_MonitoringBoolGauge0 TFE_MonitoringNewBoolGauge0(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description);
+public static native TFE_MonitoringBoolGauge0 TFE_MonitoringNewBoolGauge0(
+    String name, TF_Status out_status, String description);
+public static native void TFE_MonitoringDeleteBoolGauge0(
+    TFE_MonitoringBoolGauge0 gauge);
+public static native TFE_MonitoringBoolGaugeCell TFE_MonitoringGetCellBoolGauge0(TFE_MonitoringBoolGauge0 gauge);
+// Targeting ../TFE_MonitoringBoolGauge1.java
+
+
+public static native TFE_MonitoringBoolGauge1 TFE_MonitoringNewBoolGauge1(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringBoolGauge1 TFE_MonitoringNewBoolGauge1(
+    String name, TF_Status out_status, String description,
+    String label1);
+public static native void TFE_MonitoringDeleteBoolGauge1(
+    TFE_MonitoringBoolGauge1 gauge);
+public static native TFE_MonitoringBoolGaugeCell TFE_MonitoringGetCellBoolGauge1(TFE_MonitoringBoolGauge1 gauge,
+                                @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringBoolGaugeCell TFE_MonitoringGetCellBoolGauge1(TFE_MonitoringBoolGauge1 gauge,
+                                String label1);
+// Targeting ../TFE_MonitoringBoolGauge2.java
+
+
+public static native TFE_MonitoringBoolGauge2 TFE_MonitoringNewBoolGauge2(
+    @Cast("const char*") BytePointer name, TF_Status out_status, @Cast("const char*") BytePointer description,
+    @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringBoolGauge2 TFE_MonitoringNewBoolGauge2(
+    String name, TF_Status out_status, String description,
+    String label1, String label2);
+public static native void TFE_MonitoringDeleteBoolGauge2(
+    TFE_MonitoringBoolGauge2 gauge);
+public static native TFE_MonitoringBoolGaugeCell TFE_MonitoringGetCellBoolGauge2(TFE_MonitoringBoolGauge2 gauge,
+                                @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringBoolGaugeCell TFE_MonitoringGetCellBoolGauge2(TFE_MonitoringBoolGauge2 gauge,
+                                String label1, String label2);
+// Targeting ../TFE_MonitoringSamplerCell.java
+
+
+
+// Atomically add the value of the cell.
+public static native void TFE_MonitoringSamplerCellAdd(
+    TFE_MonitoringSamplerCell cell, double value);
+
+// Retrieves the current value of the cell. The return value is a HistogramProto
+// saved in buffer.
+public static native void TFE_MonitoringSamplerCellValue(
+    TFE_MonitoringSamplerCell cell, TF_Buffer buf);
+
+// APIs for sampler buckets
+// Targeting ../TFE_MonitoringSampler0.java
+
+
+public static native void TFE_MonitoringDeleteSampler0(
+    TFE_MonitoringSampler0 sampler);
+public static native TFE_MonitoringSamplerCell TFE_MonitoringGetCellSampler0(
+    TFE_MonitoringSampler0 sampler);
+// Targeting ../TFE_MonitoringSampler1.java
+
+
+public static native void TFE_MonitoringDeleteSampler1(
+    TFE_MonitoringSampler1 sampler);
+public static native TFE_MonitoringSamplerCell TFE_MonitoringGetCellSampler1(
+    TFE_MonitoringSampler1 sampler, @Cast("const char*") BytePointer label1);
+public static native TFE_MonitoringSamplerCell TFE_MonitoringGetCellSampler1(
+    TFE_MonitoringSampler1 sampler, String label1);
+// Targeting ../TFE_MonitoringSampler2.java
+
+
+public static native void TFE_MonitoringDeleteSampler2(
+    TFE_MonitoringSampler2 sampler);
+public static native TFE_MonitoringSamplerCell TFE_MonitoringGetCellSampler2(
+    TFE_MonitoringSampler2 sampler, @Cast("const char*") BytePointer label1, @Cast("const char*") BytePointer label2);
+public static native TFE_MonitoringSamplerCell TFE_MonitoringGetCellSampler2(
+    TFE_MonitoringSampler2 sampler, String label1, String label2);
+
+// Sets whether to use TFRT
+public static native void TFE_ContextOptionsSetTfrt(TFE_ContextOptions arg0,
+                                                     @Cast("bool") boolean use_tfrt);
+
+// Returns the context_id from the EagerContext which is used by the
+// EagerService to maintain consistency between client and worker. The
+// context_id is initialized with a dummy value and is later set when the worker
+// is initialized (either locally or remotely). The context_id can change during
+// the process lifetime although this should cause the worker to be
+// reinitialized (e.g. cleared caches) as well.
+public static native @Cast("uint64_t") long TFE_GetContextId(TFE_Context ctx);
+// Targeting ../TFE_CancellationManager.java
+
+
+public static native TFE_CancellationManager TFE_NewCancellationManager();
+public static native @Cast("bool") boolean TFE_CancellationManagerIsCancelled(
+    TFE_CancellationManager arg0);
+public static native void TFE_CancellationManagerStartCancel(
+    TFE_CancellationManager arg0);
+public static native void TFE_DeleteCancellationManager(
+    TFE_CancellationManager arg0);
+
+// Associates the given `cancellation_manager` with `op`, so that invoking
+// `TFE_CancellationManagerStartCancel(cancellation_manager)` will cancel the
+// execution of `op`.
+public static native void TFE_OpSetCancellationManager(
+    TFE_Op op, TFE_CancellationManager cancellation_manager,
+    TF_Status status);
+// Targeting ../TFE_Executor.java
+
+
+
+// Creates a new eager Executor. Nodes in one executor are guaranteed to be
+// executed in sequence. Assigning nodes to different executors allows executing
+// nodes in parallel.
+public static native TFE_Executor TFE_NewExecutor(@Cast("bool") boolean is_async);
+
+// Deletes the eager Executor without waiting for enqueued nodes. Please call
+// TFE_ExecutorWaitForAllPendingNodes before calling this API if you want to
+// make sure all nodes are finished.
+public static native void TFE_DeleteExecutor(TFE_Executor arg0);
+
+// Returns true if the executor is in async mode.
+public static native @Cast("bool") boolean TFE_ExecutorIsAsync(TFE_Executor arg0);
+
+// Causes the calling thread to block till all ops dispatched in this executor
+// have been executed. Note that "execution" here refers to kernel execution /
+// scheduling of copies, etc. Similar to sync execution, it doesn't guarantee
+// that lower level device queues (like GPU streams) have been flushed.
+//
+// This call may not block for execution of ops enqueued concurrently with this
+// call.
+public static native void TFE_ExecutorWaitForAllPendingNodes(
+    TFE_Executor arg0, TF_Status status);
+
+// When an error happens, any pending operations are discarded and newly issued
+// ops return an error. This call clears the error state and re-enables
+// execution of newly issued ops.
+//
+// Note that outputs of discarded ops remain in a corrupt state and should not
+// be used for future calls.
+// TODO(agarwal): mark the affected handles and raise errors if they are used.
+public static native void TFE_ExecutorClearError(TFE_Executor arg0);
+
+// Sets a custom Executor for current thread. All nodes created by this thread
+// will be added to this Executor. It will override current executor.
+public static native void TFE_ContextSetExecutorForThread(TFE_Context arg0,
+                                                           TFE_Executor arg1);
+
+// Returns the Executor for current thread.
+public static native TFE_Executor TFE_ContextGetExecutorForThread(
+    TFE_Context arg0);
+
+// -----------------------------------------------------------------------------
+// Dynamic cluster API.
+
+// Update an existing context with a new set of servers defined in a ServerDef
+// proto. Servers can be added to and removed from the list of remote workers
+// in the context. New set of servers identified by the ServerDef must be up
+// when the context is updated.
+//
+// This API is for experimental usage and may be subject to change.
+public static native void TFE_ContextUpdateServerDef(TFE_Context ctx,
+                                                      int keep_alive_secs,
+                                                      @Const Pointer proto,
+                                                      @Cast("size_t") long proto_len,
+                                                      TF_Status status);
+
+// Checks whether a remote worker is alive or not. This will return true even if
+// the context doesn't exist on the remote worker.
+public static native @Cast("bool") boolean TFE_ContextCheckAlive(TFE_Context ctx,
+                                                 @Cast("const char*") BytePointer worker_name,
+                                                 TF_Status status);
+public static native @Cast("bool") boolean TFE_ContextCheckAlive(TFE_Context ctx,
+                                                 String worker_name,
+                                                 TF_Status status);
+
+// Sync pending nodes in local executors (including the context default executor
+// and thread executors) and streaming requests to remote executors, and get the
+// combined status.
+public static native void TFE_ContextAsyncWait(TFE_Context ctx,
+                                                TF_Status status);
+
+// This function will block till the operation that produces `h` has
+// completed. This is only valid on local TFE_TensorHandles. The pointer
+// returned will be on the device in which the TFE_TensorHandle resides (so e.g.
+// for a GPU tensor this will return a pointer to GPU memory). The pointer is
+// only guaranteed to be valid until TFE_DeleteTensorHandle is called on this
+// TensorHandle. Only supports POD data types.
+public static native Pointer TFE_TensorHandleDevicePointer(TFE_TensorHandle arg0,
+                                                          TF_Status arg1);
+
+// This function will block till the operation that produces `h` has
+// completed. This is only valid on local TFE_TensorHandles. Returns the size in
+// bytes of the memory pointed to by the device pointer returned above.
+public static native @Cast("size_t") long TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle arg0,
+                                                              TF_Status arg1);
+
+// Creates a new TensorHandle from memory residing in the physical device
+// device_name. Takes ownership of the memory, and will call deleter to release
+// it after TF no longer needs it or in case of error.
+//
+// Custom devices must use TFE_NewCustomDeviceTensorHandle instead.
+public static native TFE_TensorHandle TFE_NewTensorHandleFromDeviceMemory(
+    TFE_Context ctx, @Cast("const char*") BytePointer device_name, @Cast("TF_DataType") int arg2, @Cast("const int64_t*") LongPointer dims,
+    int num_dims, Pointer data, @Cast("size_t") long len,
+    Deallocator_Pointer_long_Pointer deallocator,
+    Pointer deallocator_arg, TF_Status status);
+public static native TFE_TensorHandle TFE_NewTensorHandleFromDeviceMemory(
+    TFE_Context ctx, String device_name, @Cast("TF_DataType") int arg2, @Cast("const int64_t*") LongBuffer dims,
+    int num_dims, Pointer data, @Cast("size_t") long len,
+    Deallocator_Pointer_long_Pointer deallocator,
+    Pointer deallocator_arg, TF_Status status);
+public static native TFE_TensorHandle TFE_NewTensorHandleFromDeviceMemory(
+    TFE_Context ctx, @Cast("const char*") BytePointer device_name, @Cast("TF_DataType") int arg2, @Cast("const int64_t*") long[] dims,
+    int num_dims, Pointer data, @Cast("size_t") long len,
+    Deallocator_Pointer_long_Pointer deallocator,
+    Pointer deallocator_arg, TF_Status status);
+public static native TFE_TensorHandle TFE_NewTensorHandleFromDeviceMemory(
+    TFE_Context ctx, String device_name, @Cast("TF_DataType") int arg2, @Cast("const int64_t*") LongPointer dims,
+    int num_dims, Pointer data, @Cast("size_t") long len,
+    Deallocator_Pointer_long_Pointer deallocator,
+    Pointer deallocator_arg, TF_Status status);
+public static native TFE_TensorHandle TFE_NewTensorHandleFromDeviceMemory(
+    TFE_Context ctx, @Cast("const char*") BytePointer device_name, @Cast("TF_DataType") int arg2, @Cast("const int64_t*") LongBuffer dims,
+    int num_dims, Pointer data, @Cast("size_t") long len,
+    Deallocator_Pointer_long_Pointer deallocator,
+    Pointer deallocator_arg, TF_Status status);
+public static native TFE_TensorHandle TFE_NewTensorHandleFromDeviceMemory(
+    TFE_Context ctx, String device_name, @Cast("TF_DataType") int arg2, @Cast("const int64_t*") long[] dims,
+    int num_dims, Pointer data, @Cast("size_t") long len,
+    Deallocator_Pointer_long_Pointer deallocator,
+    Pointer deallocator_arg, TF_Status status);
+
+// Retrieves the address space (i.e. job, replia, task) of the local host and
+// saves it in the buffer.
+public static native void TFE_HostAddressSpace(TFE_Context ctx,
+                                                TF_Buffer buf);
+// Targeting ../TFE_OpAttrs.java
+
+
+
+// Fetch a reference to `op`'s attributes. The returned reference is only valid
+// while `op` is alive.
+public static native @Const TFE_OpAttrs TFE_OpGetAttrs(@Const TFE_Op op);
+// Add attributes in `attrs` to `op`.
+//
+// Does not overwrite or update existing attributes, but adds new ones.
+public static native void TFE_OpAddAttrs(TFE_Op op, @Const TFE_OpAttrs attrs);
+
+// Serialize `attrs` as a tensorflow::NameAttrList protocol buffer (into `buf`),
+// containing the op name and a map of its attributes.
+public static native void TFE_OpAttrsSerialize(@Const TFE_OpAttrs attrs,
+                                                TF_Buffer buf,
+                                                TF_Status status);
+
+// Set an op's attribute from a serialized AttrValue protocol buffer.
+//
+// Analogous to TF_SetAttrValueProto for building graph operations.
+public static native void TFE_OpSetAttrValueProto(@Const TFE_Op op,
+                                                   @Cast("const char*") BytePointer attr_name,
+                                                   @Const Pointer proto,
+                                                   @Cast("size_t") long proto_len,
+                                                   TF_Status status);
+public static native void TFE_OpSetAttrValueProto(@Const TFE_Op op,
+                                                   String attr_name,
+                                                   @Const Pointer proto,
+                                                   @Cast("size_t") long proto_len,
+                                                   TF_Status status);
+
+// TODO(b/166642410): It would be nice, for custom devices and for other users,
+// to have a non-string representation of devices (TF_Device) extracted from
+// tensors/ops/etc. and usable in APIs like OpSetDevice/ResetOp/etc.
+
+public static final int TFE_CUSTOM_DEVICE_VERSION = 4;
+
+// Struct to be filled in. Functions are required except where indicated.
+
+// Registers a custom device for use with eager execution.
+//
+// Eager operations may be placed on this device, e.g.  `with
+// tf.device("CUSTOM"):` from Python if `device_name` for this call is
+// "/job:localhost/replica:0/task:0/device:CUSTOM:0".
+//
+// The custom device defines copy operations for moving TensorHandles on and
+// off, and an execution operation for named operations. Often execution will
+// simply wrap op execution on one or more physical devices.
+//
+// device_info is an opaque caller-defined type stored with the custom device
+// which is passed to the functions referenced in the TFE_CustomDevice struct
+// `device` (execute, delete_device, etc.). It can for example contain the
+// names of wrapped devices.
+//
+// There are currently no graph semantics implemented for registered custom
+// devices, so executing tf.functions which contain operations placed on custom
+// devices will fail.
+//
+// `device_name` must not name an existing physical or custom device. It must
+// follow the format:
+//
+//    /job:<name>/replica:<replica>/task:<task>/device:<type>:<device_num>
+//
+// If the device is successfully registered, `status` is set to TF_OK. Otherwise
+// the device is not usable. In case of a bad status, `device.delete_device` is
+// still called on `device_info` (i.e. the caller does not retain ownership).
+//
+// This API is highly experimental, and in particular is expected to change when
+// it starts supporting operations with attributes and when tf.function support
+// is added.
+
+// Struct to be filled in to define a custom device tensor handle. Fields are
+// required except where indicated.
+
+// Creates a new TensorHandle from memory residing in a custom device. Takes
+// ownership of the memory pointed to by `tensor_handle_data`, and calls
+// `methods.deallocator` to release it after TF no longer needs it or in case of
+// an error.
+//
+// This call is similar to `TFE_NewTensorHandleFromDeviceMemory`, but supports
+// custom devices instead of physical devices and does not require blocking
+// waiting for exact shapes.
+
+public static native void TFE_ContextGetFunctionDef(TFE_Context ctx,
+                                                     @Cast("const char*") BytePointer function_name,
+                                                     TF_Buffer buf,
+                                                     TF_Status status);
+public static native void TFE_ContextGetFunctionDef(TFE_Context ctx,
+                                                     String function_name,
+                                                     TF_Buffer buf,
+                                                     TF_Status status);
+
+// Allocate and return a new Tensor on the host.
+//
+// The caller must set the Tensor values by writing them to the pointer returned
+// by TF_TensorData with length TF_TensorByteSize.
+public static native TF_Tensor TFE_AllocateHostTensor(TFE_Context ctx,
+                                                        @Cast("TF_DataType") int dtype,
+                                                        @Cast("const int64_t*") LongPointer dims,
+                                                        int num_dims,
+                                                        TF_Status status);
+public static native TF_Tensor TFE_AllocateHostTensor(TFE_Context ctx,
+                                                        @Cast("TF_DataType") int dtype,
+                                                        @Cast("const int64_t*") LongBuffer dims,
+                                                        int num_dims,
+                                                        TF_Status status);
+public static native TF_Tensor TFE_AllocateHostTensor(TFE_Context ctx,
+                                                        @Cast("TF_DataType") int dtype,
+                                                        @Cast("const int64_t*") long[] dims,
+                                                        int num_dims,
+                                                        TF_Status status);
+
+// Given a Tensor, wrap it with a TensorHandle
+//
+// Similar to TFE_NewTensorHandle, but includes a pointer to the TFE_Context.
+// The context should be identical to that of the Tensor.
+public static native TFE_TensorHandle TFE_NewTensorHandleFromTensor(
+    TFE_Context ctx, TF_Tensor t, TF_Status status);
+
+// Create a packed TensorHandle with the given list of TensorHandles.
+// If `handles` are on the same device, assign the same device to the packed
+// handle; if `handles` are on different deivces, assign a CompositeDevice to
+// it.
+public static native TFE_TensorHandle TFE_CreatePackedTensorHandle(
+    TFE_Context ctx, @Cast("TFE_TensorHandle**") PointerPointer handles, IntPointer num_handles,
+    TF_Status status);
+public static native TFE_TensorHandle TFE_CreatePackedTensorHandle(
+    TFE_Context ctx, @ByPtrPtr TFE_TensorHandle handles, IntPointer num_handles,
+    TF_Status status);
+public static native TFE_TensorHandle TFE_CreatePackedTensorHandle(
+    TFE_Context ctx, @ByPtrPtr TFE_TensorHandle handles, IntBuffer num_handles,
+    TF_Status status);
+public static native TFE_TensorHandle TFE_CreatePackedTensorHandle(
+    TFE_Context ctx, @ByPtrPtr TFE_TensorHandle handles, int[] num_handles,
+    TF_Status status);
+
+// Configure soft device placement policy for the eager executor. Note this
+// policy is applied to any subsequent op executions.
+public static native void TFE_ContextSetSoftDevicePlacement(TFE_Context ctx,
+                                                      @Cast("unsigned char") byte enable,
+                                                      TF_Status status);
+
+// Configure device placement policy logging for the eager executor. Note this
+// policy is applied to any subsequent op executions.
+public static native void TFE_ContextSetLogDevicePlacement(TFE_Context ctx,
+                                                     @Cast("unsigned char") byte enable,
+                                                     TF_Status status);
+
+// Returns the device type of the operation that produced `h`.
+public static native @Cast("const char*") BytePointer TFE_TensorHandleDeviceType(
+    TFE_TensorHandle h, TF_Status status);
+
+// Returns the device ID of the operation that produced `h`.
+public static native int TFE_TensorHandleDeviceID(TFE_TensorHandle h,
+                                                   TF_Status status);
+
+// Get a comma-separated list of op names executed in graph functions dispatched
+// to `ctx`. This feature is currently only enabled for TFRT debug builds, for
+// performance and simplicity reasons.
+public static native void TFE_GetExecutedOpNames(TFE_Context ctx,
+                                                  TF_Buffer buf,
+                                                  TF_Status status);
+
+// #ifdef __cplusplus /* end extern "C" */
+// #endif
+
+// #endif  // TENSORFLOW_C_EAGER_C_API_EXPERIMENTAL_H_
+
+
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/AudioSpectrogram.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/AudioSpectrogram.java
index e8fa2db9789..12fca67165e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/AudioSpectrogram.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/AudioSpectrogram.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.audio;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -144,4 +147,37 @@ public Options magnitudeSquared(Boolean magnitudeSquared) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AudioSpectrogram> {
+    /**
+     * Float representation of audio data.
+     */
+    public final Operand<TFloat32> input;
+
+    /**
+     * How wide the input window is in samples. For the highest efficiency
+     * this should be a power of two, but other values are accepted.
+     */
+    public final long windowSize;
+
+    /**
+     * How widely apart the center of adjacent sample windows should be.
+     */
+    public final long stride;
+
+    /**
+     * Whether to return the squared magnitude or just the
+     * magnitude. Using squared magnitude can avoid extra calculations.
+     */
+    public final boolean magnitudeSquared;
+
+    public Inputs(GraphOperation op) {
+      super(new AudioSpectrogram(op), op, Arrays.asList("window_size", "stride", "magnitude_squared"));
+      int inputIndex = 0;
+      input = (Operand<TFloat32>) op.input(inputIndex++);
+      windowSize = op.attributes().getAttrInt("window_size");
+      stride = op.attributes().getAttrInt("stride");
+      magnitudeSquared = op.attributes().getAttrBool("magnitude_squared");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/DecodeWav.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/DecodeWav.java
index ed0fbc78f59..0caa473a0db 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/DecodeWav.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/DecodeWav.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.audio;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -161,4 +164,29 @@ public Options desiredSamples(Long desiredSamples) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeWav> {
+    /**
+     * The WAV-encoded audio, usually from a file.
+     */
+    public final Operand<TString> contents;
+
+    /**
+     * Number of sample channels wanted.
+     */
+    public final long desiredChannels;
+
+    /**
+     * Length of audio requested.
+     */
+    public final long desiredSamples;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeWav(op), op, Arrays.asList("desired_channels", "desired_samples"));
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+      desiredChannels = op.attributes().getAttrInt("desired_channels");
+      desiredSamples = op.attributes().getAttrInt("desired_samples");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/EncodeWav.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/EncodeWav.java
index 242dac20819..8e535d1d48b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/EncodeWav.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/EncodeWav.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.audio;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -86,4 +89,23 @@ public Output<TString> contents() {
   public Output<TString> asOutput() {
     return contents;
   }
+
+  public static class Inputs extends RawOpInputs<EncodeWav> {
+    /**
+     * 2-D with shape {@code [length, channels]}.
+     */
+    public final Operand<TFloat32> audio;
+
+    /**
+     * Scalar containing the sample frequency.
+     */
+    public final Operand<TInt32> sampleRate;
+
+    public Inputs(GraphOperation op) {
+      super(new EncodeWav(op), op, Arrays.asList());
+      int inputIndex = 0;
+      audio = (Operand<TFloat32>) op.input(inputIndex++);
+      sampleRate = (Operand<TInt32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/Mfcc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/Mfcc.java
index bc76f03920f..b75d638879c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/Mfcc.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/audio/Mfcc.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.audio;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -208,4 +211,50 @@ public Options dctCoefficientCount(Long dctCoefficientCount) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Mfcc> {
+    /**
+     * Typically produced by the Spectrogram op, with magnitude_squared
+     * set to true.
+     */
+    public final Operand<TFloat32> spectrogram;
+
+    /**
+     * How many samples per second the source audio used.
+     */
+    public final Operand<TInt32> sampleRate;
+
+    /**
+     * The highest frequency to use when calculating the
+     * ceptstrum.
+     */
+    public final float upperFrequencyLimit;
+
+    /**
+     * The lowest frequency to use when calculating the
+     * ceptstrum.
+     */
+    public final float lowerFrequencyLimit;
+
+    /**
+     * Resolution of the Mel bank used internally.
+     */
+    public final long filterbankChannelCount;
+
+    /**
+     * How many output channels to produce per time slice.
+     */
+    public final long dctCoefficientCount;
+
+    public Inputs(GraphOperation op) {
+      super(new Mfcc(op), op, Arrays.asList("upper_frequency_limit", "lower_frequency_limit", "filterbank_channel_count", "dct_coefficient_count"));
+      int inputIndex = 0;
+      spectrogram = (Operand<TFloat32>) op.input(inputIndex++);
+      sampleRate = (Operand<TInt32>) op.input(inputIndex++);
+      upperFrequencyLimit = op.attributes().getAttrFloat("upper_frequency_limit");
+      lowerFrequencyLimit = op.attributes().getAttrFloat("lower_frequency_limit");
+      filterbankChannelCount = op.attributes().getAttrInt("filterbank_channel_count");
+      dctCoefficientCount = op.attributes().getAttrInt("dct_coefficient_count");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java
index a4723f1eca5..0a208566534 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.bitwise;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -70,8 +74,8 @@ private BitwiseAnd(Operation operation) {
    * Factory method to create a class wrapping a new BitwiseAnd operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code BitwiseAnd} output and operands
    * @return a new instance of BitwiseAnd
    */
@@ -98,4 +102,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BitwiseAnd<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BitwiseAnd<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java
index a69cd3e282d..ba212ec5596 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.bitwise;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -70,8 +74,8 @@ private BitwiseOr(Operation operation) {
    * Factory method to create a class wrapping a new BitwiseOr operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code BitwiseOr} output and operands
    * @return a new instance of BitwiseOr
    */
@@ -98,4 +102,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BitwiseOr<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BitwiseOr<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java
index 98123299b7e..57248c5cc6d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.bitwise;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -70,8 +74,8 @@ private BitwiseXor(Operation operation) {
    * Factory method to create a class wrapping a new BitwiseXor operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code BitwiseXor} output and operands
    * @return a new instance of BitwiseXor
    */
@@ -98,4 +102,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BitwiseXor<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BitwiseXor<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java
index cf052eb2235..f5f2765eb33 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.bitwise;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -91,7 +95,7 @@ private Invert(Operation operation) {
    * Factory method to create a class wrapping a new Invert operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Invert} output and operands
    * @return a new instance of Invert
    */
@@ -117,4 +121,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Invert<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Invert<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java
index bad49a692a4..6420dcc7f65 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.bitwise;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -81,8 +85,8 @@ private LeftShift(Operation operation) {
    * Factory method to create a class wrapping a new LeftShift operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code LeftShift} output and operands
    * @return a new instance of LeftShift
    */
@@ -109,4 +113,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LeftShift<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LeftShift<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java
index b633e0c4d0f..5fa84781682 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.bitwise;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -83,8 +87,8 @@ private RightShift(Operation operation) {
    * Factory method to create a class wrapping a new RightShift operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RightShift} output and operands
    * @return a new instance of RightShift
    */
@@ -111,4 +115,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RightShift<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RightShift<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KMC2ChainInitialization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KMC2ChainInitialization.java
index 76ed4d0228e..39eb7f70ce5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KMC2ChainInitialization.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KMC2ChainInitialization.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.cluster;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -81,4 +84,24 @@ public Output<TInt64> index() {
   public Output<TInt64> asOutput() {
     return index;
   }
+
+  public static class Inputs extends RawOpInputs<KMC2ChainInitialization> {
+    /**
+     * Vector with squared distances to the closest previously sampled cluster center
+     * for each candidate point.
+     */
+    public final Operand<TFloat32> distances;
+
+    /**
+     * Scalar. Seed for initializing the random number generator.
+     */
+    public final Operand<TInt64> seed;
+
+    public Inputs(GraphOperation op) {
+      super(new KMC2ChainInitialization(op), op, Arrays.asList());
+      int inputIndex = 0;
+      distances = (Operand<TFloat32>) op.input(inputIndex++);
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KmeansPlusPlusInitialization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KmeansPlusPlusInitialization.java
index b73162109f7..65058cc1268 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KmeansPlusPlusInitialization.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/cluster/KmeansPlusPlusInitialization.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.cluster;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -87,4 +90,38 @@ public Output<TFloat32> samples() {
   public Output<TFloat32> asOutput() {
     return samples;
   }
+
+  public static class Inputs extends RawOpInputs<KmeansPlusPlusInitialization> {
+    /**
+     * Matrix of shape (n, d). Rows are assumed to be input points.
+     */
+    public final Operand<TFloat32> points;
+
+    /**
+     * Scalar. The number of rows to sample. This value must not be larger than n.
+     */
+    public final Operand<TInt64> numToSample;
+
+    /**
+     * Scalar. Seed for initializing the random number generator.
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * Scalar. For each row that is sampled, this parameter
+     * specifies the number of additional points to draw from the current
+     * distribution before selecting the best. If a negative value is specified, a
+     * heuristic is used to sample O(log(num_to_sample)) additional points.
+     */
+    public final Operand<TInt64> numRetriesPerSample;
+
+    public Inputs(GraphOperation op) {
+      super(new KmeansPlusPlusInitialization(op), op, Arrays.asList());
+      int inputIndex = 0;
+      points = (Operand<TFloat32>) op.input(inputIndex++);
+      numToSample = (Operand<TInt64>) op.input(inputIndex++);
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      numRetriesPerSample = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java
index 5404521a40f..e338973185a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -54,13 +57,13 @@ private AllReduce(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveReduce operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the value of the groupSize property
-   * @param groupKey the value of the groupKey property
-   * @param instanceKey the value of the instanceKey property
-   * @param mergeOp the value of the mergeOp property
-   * @param finalOp the value of the finalOp property
-   * @param subdivOffsets the value of the subdivOffsets property
+   * @param input The input value
+   * @param groupSize The value of the groupSize attribute
+   * @param groupKey The value of the groupKey attribute
+   * @param instanceKey The value of the instanceKey attribute
+   * @param mergeOp The value of the mergeOp attribute
+   * @param finalOp The value of the finalOp attribute
+   * @param subdivOffsets The value of the subdivOffsets attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveReduce} output and operands
    * @return a new instance of AllReduce
@@ -119,7 +122,7 @@ public static Options waitFor(List<Long> waitFor) {
    * @param waitFor the waitFor option
    * @return this Options instance.
    */
-  public static Options waitFor(Long[] waitFor) {
+  public static Options waitFor(Long... waitFor) {
     return new Options().waitFor(waitFor);
   }
 
@@ -214,4 +217,77 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AllReduce<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The groupSize attribute
+     */
+    public final long groupSize;
+
+    /**
+     * The groupKey attribute
+     */
+    public final long groupKey;
+
+    /**
+     * The instanceKey attribute
+     */
+    public final long instanceKey;
+
+    /**
+     * The mergeOp attribute
+     */
+    public final String mergeOp;
+
+    /**
+     * The finalOp attribute
+     */
+    public final String finalOp;
+
+    /**
+     * The subdivOffsets attribute
+     */
+    public final long[] subdivOffsets;
+
+    /**
+     * The waitFor attribute
+     */
+    public final long[] waitFor;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new AllReduce<>(op), op, Arrays.asList("T", "group_size", "group_key", "instance_key", "merge_op", "final_op", "subdiv_offsets", "wait_for", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      groupSize = op.attributes().getAttrInt("group_size");
+      groupKey = op.attributes().getAttrInt("group_key");
+      instanceKey = op.attributes().getAttrInt("instance_key");
+      mergeOp = op.attributes().getAttrString("merge_op");
+      finalOp = op.attributes().getAttrString("final_op");
+      subdivOffsets = op.attributes().getAttrIntList("subdiv_offsets");
+      waitFor = op.attributes().getAttrIntList("wait_for");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java
index 2db3893987d..76cdc37a0c4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.collective;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,8 +26,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,11 +55,11 @@ private BroadcastRecv(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveBcastRecv operation.
    *
    * @param scope current scope
-   * @param T the value of the T property
-   * @param groupSize the value of the groupSize property
-   * @param groupKey the value of the groupKey property
-   * @param instanceKey the value of the instanceKey property
-   * @param shape the value of the shape property
+   * @param T The value of the T attribute
+   * @param groupSize The value of the groupSize attribute
+   * @param groupKey The value of the groupKey attribute
+   * @param instanceKey The value of the instanceKey attribute
+   * @param shape The value of the shape attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveBcastRecv} output and operands
    * @return a new instance of BroadcastRecv
@@ -151,4 +155,53 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BroadcastRecv<?>> {
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The groupSize attribute
+     */
+    public final long groupSize;
+
+    /**
+     * The groupKey attribute
+     */
+    public final long groupKey;
+
+    /**
+     * The instanceKey attribute
+     */
+    public final long instanceKey;
+
+    /**
+     * The shape attribute
+     */
+    public final Shape shape;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new BroadcastRecv<>(op), op, Arrays.asList("T", "group_size", "group_key", "instance_key", "shape", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      T = op.attributes().getAttrType("T");
+      groupSize = op.attributes().getAttrInt("group_size");
+      groupKey = op.attributes().getAttrInt("group_key");
+      instanceKey = op.attributes().getAttrInt("instance_key");
+      shape = op.attributes().getAttrShape("shape");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastSend.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastSend.java
index fb6edd95351..707032af259 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastSend.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastSend.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.collective;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -50,11 +54,11 @@ private BroadcastSend(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveBcastSend operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the value of the groupSize property
-   * @param groupKey the value of the groupKey property
-   * @param instanceKey the value of the instanceKey property
-   * @param shape the value of the shape property
+   * @param input The input value
+   * @param groupSize The value of the groupSize attribute
+   * @param groupKey The value of the groupKey attribute
+   * @param instanceKey The value of the instanceKey attribute
+   * @param shape The value of the shape attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveBcastSend} output and operands
    * @return a new instance of BroadcastSend
@@ -150,4 +154,59 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BroadcastSend<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The groupSize attribute
+     */
+    public final long groupSize;
+
+    /**
+     * The groupKey attribute
+     */
+    public final long groupKey;
+
+    /**
+     * The instanceKey attribute
+     */
+    public final long instanceKey;
+
+    /**
+     * The shape attribute
+     */
+    public final Shape shape;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new BroadcastSend<>(op), op, Arrays.asList("T", "group_size", "group_key", "instance_key", "shape", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      groupSize = op.attributes().getAttrInt("group_size");
+      groupKey = op.attributes().getAttrInt("group_key");
+      instanceKey = op.attributes().getAttrInt("instance_key");
+      shape = op.attributes().getAttrShape("shape");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Gather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Gather.java
index 2a1a3b7b41f..b058a53afea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Gather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Gather.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.collective;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -50,11 +54,11 @@ private Gather(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveGather operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the value of the groupSize property
-   * @param groupKey the value of the groupKey property
-   * @param instanceKey the value of the instanceKey property
-   * @param shape the value of the shape property
+   * @param input The input value
+   * @param groupSize The value of the groupSize attribute
+   * @param groupKey The value of the groupKey attribute
+   * @param instanceKey The value of the instanceKey attribute
+   * @param shape The value of the shape attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveGather} output and operands
    * @return a new instance of Gather
@@ -150,4 +154,59 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Gather<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The groupSize attribute
+     */
+    public final long groupSize;
+
+    /**
+     * The groupKey attribute
+     */
+    public final long groupKey;
+
+    /**
+     * The instanceKey attribute
+     */
+    public final long instanceKey;
+
+    /**
+     * The shape attribute
+     */
+    public final Shape shape;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new Gather<>(op), op, Arrays.asList("T", "group_size", "group_key", "instance_key", "shape", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      groupSize = op.attributes().getAttrInt("group_size");
+      groupKey = op.attributes().getAttrInt("group_key");
+      instanceKey = op.attributes().getAttrInt("instance_key");
+      shape = op.attributes().getAttrShape("shape");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/GatherV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/GatherV2.java
index 2900c31041e..77e32799164 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/GatherV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/GatherV2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.collective;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -52,11 +56,11 @@ private GatherV2(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveGatherV2 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the groupSize value
-   * @param groupKey the groupKey value
-   * @param instanceKey the instanceKey value
-   * @param orderingToken the orderingToken value
+   * @param input The input value
+   * @param groupSize The groupSize value
+   * @param groupKey The groupKey value
+   * @param instanceKey The instanceKey value
+   * @param orderingToken The orderingToken value
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveGatherV2} output and operands
    * @return a new instance of GatherV2
@@ -179,4 +183,61 @@ public Options NorderingToken(Long NorderingToken) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<GatherV2<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The groupSize input
+     */
+    public final Operand<TInt32> groupSize;
+
+    /**
+     * The groupKey input
+     */
+    public final Operand<TInt32> groupKey;
+
+    /**
+     * The instanceKey input
+     */
+    public final Operand<TInt32> instanceKey;
+
+    /**
+     * The orderingToken input
+     */
+    public final Iterable<Operand<? extends TType>> orderingToken;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new GatherV2<>(op), op, Arrays.asList("T", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      groupSize = (Operand<TInt32>) op.input(inputIndex++);
+      groupKey = (Operand<TInt32>) op.input(inputIndex++);
+      instanceKey = (Operand<TInt32>) op.input(inputIndex++);
+      int orderingTokenLength = op.inputListLength("ordering_token");
+      orderingToken = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, orderingTokenLength));
+      inputIndex += orderingTokenLength;
+      T = op.attributes().getAttrType("T");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Reduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Reduce.java
index cf4bc4328c1..3b86c960d1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Reduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/Reduce.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -51,13 +54,13 @@ private Reduce(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveReduce operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the value of the groupSize property
-   * @param groupKey the value of the groupKey property
-   * @param instanceKey the value of the instanceKey property
-   * @param mergeOp the value of the mergeOp property
-   * @param finalOp the value of the finalOp property
-   * @param subdivOffsets the value of the subdivOffsets property
+   * @param input The input value
+   * @param groupSize The value of the groupSize attribute
+   * @param groupKey The value of the groupKey attribute
+   * @param instanceKey The value of the instanceKey attribute
+   * @param mergeOp The value of the mergeOp attribute
+   * @param finalOp The value of the finalOp attribute
+   * @param subdivOffsets The value of the subdivOffsets attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveReduce} output and operands
    * @return a new instance of Reduce
@@ -116,7 +119,7 @@ public static Options waitFor(List<Long> waitFor) {
    * @param waitFor the waitFor option
    * @return this Options instance.
    */
-  public static Options waitFor(Long[] waitFor) {
+  public static Options waitFor(Long... waitFor) {
     return new Options().waitFor(waitFor);
   }
 
@@ -211,4 +214,77 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Reduce<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The groupSize attribute
+     */
+    public final long groupSize;
+
+    /**
+     * The groupKey attribute
+     */
+    public final long groupKey;
+
+    /**
+     * The instanceKey attribute
+     */
+    public final long instanceKey;
+
+    /**
+     * The mergeOp attribute
+     */
+    public final String mergeOp;
+
+    /**
+     * The finalOp attribute
+     */
+    public final String finalOp;
+
+    /**
+     * The subdivOffsets attribute
+     */
+    public final long[] subdivOffsets;
+
+    /**
+     * The waitFor attribute
+     */
+    public final long[] waitFor;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new Reduce<>(op), op, Arrays.asList("T", "group_size", "group_key", "instance_key", "merge_op", "final_op", "subdiv_offsets", "wait_for", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      groupSize = op.attributes().getAttrInt("group_size");
+      groupKey = op.attributes().getAttrInt("group_key");
+      instanceKey = op.attributes().getAttrInt("instance_key");
+      mergeOp = op.attributes().getAttrString("merge_op");
+      finalOp = op.attributes().getAttrString("final_op");
+      subdivOffsets = op.attributes().getAttrIntList("subdiv_offsets");
+      waitFor = op.attributes().getAttrIntList("wait_for");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/ReduceV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/ReduceV2.java
index 77a5b8eade4..da55ef12535 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/ReduceV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/ReduceV2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.collective;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -52,13 +56,13 @@ private ReduceV2(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveReduceV2 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the groupSize value
-   * @param groupKey the groupKey value
-   * @param instanceKey the instanceKey value
-   * @param orderingToken the orderingToken value
-   * @param mergeOp the value of the mergeOp property
-   * @param finalOp the value of the finalOp property
+   * @param input The input value
+   * @param groupSize The groupSize value
+   * @param groupKey The groupKey value
+   * @param instanceKey The instanceKey value
+   * @param orderingToken The orderingToken value
+   * @param mergeOp The value of the mergeOp attribute
+   * @param finalOp The value of the finalOp attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveReduceV2} output and operands
    * @return a new instance of ReduceV2
@@ -210,4 +214,79 @@ public Options maxSubdivsPerDevice(Long maxSubdivsPerDevice) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ReduceV2<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The groupSize input
+     */
+    public final Operand<TInt32> groupSize;
+
+    /**
+     * The groupKey input
+     */
+    public final Operand<TInt32> groupKey;
+
+    /**
+     * The instanceKey input
+     */
+    public final Operand<TInt32> instanceKey;
+
+    /**
+     * The orderingToken input
+     */
+    public final Iterable<Operand<? extends TType>> orderingToken;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The mergeOp attribute
+     */
+    public final String mergeOp;
+
+    /**
+     * The finalOp attribute
+     */
+    public final String finalOp;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    /**
+     * The maxSubdivsPerDevice attribute
+     */
+    public final long maxSubdivsPerDevice;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceV2<>(op), op, Arrays.asList("T", "merge_op", "final_op", "communication_hint", "timeout_seconds", "max_subdivs_per_device"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      groupSize = (Operand<TInt32>) op.input(inputIndex++);
+      groupKey = (Operand<TInt32>) op.input(inputIndex++);
+      instanceKey = (Operand<TInt32>) op.input(inputIndex++);
+      int orderingTokenLength = op.inputListLength("ordering_token");
+      orderingToken = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, orderingTokenLength));
+      inputIndex += orderingTokenLength;
+      T = op.attributes().getAttrType("T");
+      mergeOp = op.attributes().getAttrString("merge_op");
+      finalOp = op.attributes().getAttrString("final_op");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+      maxSubdivsPerDevice = op.attributes().getAttrInt("max_subdivs_per_device");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Abort.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Abort.java
index 850854a9523..455cb214124 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Abort.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Abort.java
@@ -17,9 +17,12 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -119,4 +122,23 @@ public Options exitWithoutError(Boolean exitWithoutError) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Abort> {
+    /**
+     * A string which is the message associated with the exception.
+     */
+    public final String errorMsg;
+
+    /**
+     * The exitWithoutError attribute
+     */
+    public final boolean exitWithoutError;
+
+    public Inputs(GraphOperation op) {
+      super(new Abort(op), op, Arrays.asList("error_msg", "exit_without_error"));
+      int inputIndex = 0;
+      errorMsg = op.attributes().getAttrString("error_msg");
+      exitWithoutError = op.attributes().getAttrBool("exit_without_error");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java
index 58a16e2306b..ca17e9a1ba0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -122,4 +126,36 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<All> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<TBool> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new All(op), op, Arrays.asList("keep_dims", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<TBool>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java
index a629c8d4895..c853cf365ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -122,4 +126,36 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Any> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<TBool> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Any(op), op, Arrays.asList("keep_dims", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<TBool>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssertThat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssertThat.java
index 58afa56676c..fdd9f9628c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssertThat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssertThat.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 
 /**
@@ -100,4 +104,37 @@ public Options summarize(Long summarize) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AssertThat> {
+    /**
+     * The condition to evaluate.
+     */
+    public final Operand<TBool> condition;
+
+    /**
+     * The tensors to print out when condition is false.
+     */
+    public final Iterable<Operand<?>> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    /**
+     * Print this many entries of each tensor.
+     */
+    public final long summarize;
+
+    public Inputs(GraphOperation op) {
+      super(new AssertThat(op), op, Arrays.asList("T", "summarize"));
+      int inputIndex = 0;
+      condition = (Operand<TBool>) op.input(inputIndex++);
+      int dataLength = op.inputListLength("data");
+      data = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, dataLength));
+      inputIndex += dataLength;
+      T = op.attributes().getAttrTypeList("T");
+      summarize = op.attributes().getAttrInt("summarize");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java
index 4ad9ca40e03..9af134e388e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -154,4 +158,44 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Assign<T>> {
+    /**
+     * Should be from a {@code Variable} node. May be uninitialized.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * The value to be assigned to the variable.
+     */
+    public final Operand<T> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the operation will validate that the shape
+     * of 'value' matches the shape of the Tensor being assigned to.  If false,
+     * 'ref' will take on the shape of 'value'.
+     */
+    public final boolean validateShape;
+
+    /**
+     * If True, the assignment will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new Assign<>(op), op, Arrays.asList("T", "validate_shape", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      value = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      validateShape = op.attributes().getAttrBool("validate_shape");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java
index fd8b3bcc793..b863c0aed92 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -124,4 +128,36 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<AssignAdd<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * The value to be added to the variable.
+     */
+    public final Operand<T> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, the addition will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new AssignAdd<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      value = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAddVariableOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAddVariableOp.java
index 10e0c5cd327..618f646be84 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAddVariableOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAddVariableOp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,4 +64,29 @@ public static AssignAddVariableOp create(Scope scope, Operand<? extends TType> r
     opBuilder.addInput(value.asOutput());
     return new AssignAddVariableOp(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<AssignAddVariableOp> {
+    /**
+     * handle to the resource in which to store the variable.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * the value by which the variable will be incremented.
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * the dtype of the value.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new AssignAddVariableOp(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java
index dbba967ad2f..a1d6c5bfb3a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -124,4 +128,36 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<AssignSub<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * The value to be subtracted to the variable.
+     */
+    public final Operand<T> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new AssignSub<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      value = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSubVariableOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSubVariableOp.java
index 2821427195c..ddd83dc834e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSubVariableOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSubVariableOp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,4 +64,29 @@ public static AssignSubVariableOp create(Scope scope, Operand<? extends TType> r
     opBuilder.addInput(value.asOutput());
     return new AssignSubVariableOp(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<AssignSubVariableOp> {
+    /**
+     * handle to the resource in which to store the variable.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * the value by which the variable will be incremented.
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * the dtype of the value.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new AssignSubVariableOp(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignVariableOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignVariableOp.java
index a8d89c838c9..98dd0682d0d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignVariableOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignVariableOp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,4 +64,29 @@ public static AssignVariableOp create(Scope scope, Operand<? extends TType> reso
     opBuilder.addInput(value.asOutput());
     return new AssignVariableOp(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<AssignVariableOp> {
+    /**
+     * handle to the resource in which to store the variable.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * the value to set the new tensor to use.
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * the dtype of the value.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new AssignVariableOp(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java
index eb042cce417..a722c116dd7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -115,7 +118,7 @@ public static Options shapes(List<Shape> shapes) {
    * component_types.
    * @return this Options instance.
    */
-  public static Options shapes(Shape[] shapes) {
+  public static Options shapes(Shape... shapes) {
     return new Options().shapes(shapes);
   }
 
@@ -243,4 +246,46 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Barrier> {
+    /**
+     * The type of each component in a value.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * The shape of each component in a value. Each shape must be 1 in the
+     * first dimension. The length of this attr must be the same as the length of
+     * component_types.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * The capacity of the barrier.  The default capacity is MAX_INT32,
+     * which is the largest capacity of the underlying queue.
+     */
+    public final long capacity;
+
+    /**
+     * If non-empty, this barrier is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this barrier will be shared under the given name
+     * across multiple sessions.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new Barrier(op), op, Arrays.asList("component_types", "shapes", "capacity", "container", "shared_name"));
+      int inputIndex = 0;
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      capacity = op.attributes().getAttrInt("capacity");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierClose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierClose.java
index 6d2a912722c..509f714fb88 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierClose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierClose.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -104,4 +107,25 @@ public Options cancelPendingEnqueues(Boolean cancelPendingEnqueues) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BarrierClose> {
+    /**
+     * The handle to a barrier.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * If true, all pending enqueue requests that are
+     * blocked on the barrier's queue will be canceled. InsertMany will fail, even
+     * if no new key is introduced.
+     */
+    public final boolean cancelPendingEnqueues;
+
+    public Inputs(GraphOperation op) {
+      super(new BarrierClose(op), op, Arrays.asList("cancel_pending_enqueues"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      cancelPendingEnqueues = op.attributes().getAttrBool("cancel_pending_enqueues");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierIncompleteSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierIncompleteSize.java
index 4b4e7f1f3e5..1fe4a2be77e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierIncompleteSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierIncompleteSize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -76,4 +79,17 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<BarrierIncompleteSize> {
+    /**
+     * The handle to a barrier.
+     */
+    public final Operand<TString> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new BarrierIncompleteSize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierInsertMany.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierInsertMany.java
index 371cc0b7c16..b5d28bdc4da 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierInsertMany.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierInsertMany.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -68,4 +72,42 @@ public static BarrierInsertMany create(Scope scope, Operand<TString> handle,
     opBuilder.setAttr("component_index", componentIndex);
     return new BarrierInsertMany(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<BarrierInsertMany> {
+    /**
+     * The handle to a barrier.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * A one-dimensional tensor of keys, with length n.
+     */
+    public final Operand<TString> keys;
+
+    /**
+     * An any-dimensional tensor of values, which are associated with the
+     * respective keys. The 0th dimension must have length n.
+     */
+    public final Operand<? extends TType> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The component of the barrier elements that is being assigned.
+     */
+    public final long componentIndex;
+
+    public Inputs(GraphOperation op) {
+      super(new BarrierInsertMany(op), op, Arrays.asList("T", "component_index"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      keys = (Operand<TString>) op.input(inputIndex++);
+      values = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      componentIndex = op.attributes().getAttrInt("component_index");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierReadySize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierReadySize.java
index df7cf5cc40e..f38db0fd368 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierReadySize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierReadySize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -76,4 +79,17 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<BarrierReadySize> {
+    /**
+     * The handle to a barrier.
+     */
+    public final Operand<TString> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new BarrierReadySize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java
index 72ee2fcc356..baf77154ae3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java
@@ -19,15 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -215,4 +218,51 @@ public Options timeoutMs(Long timeoutMs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BarrierTakeMany> {
+    /**
+     * The handle to a barrier.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * A single-element tensor containing the number of elements to
+     * take.
+     */
+    public final Operand<TInt32> numElements;
+
+    /**
+     * The type of each component in a value.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * Allow to return less than num_elements items if barrier is
+     * already closed.
+     */
+    public final boolean allowSmallBatch;
+
+    /**
+     * The waitForIncomplete attribute
+     */
+    public final boolean waitForIncomplete;
+
+    /**
+     * If the queue is empty, this operation will block for up to
+     * timeout_ms milliseconds.
+     * Note: This option is not supported yet.
+     */
+    public final long timeoutMs;
+
+    public Inputs(GraphOperation op) {
+      super(new BarrierTakeMany(op), op, Arrays.asList("component_types", "allow_small_batch", "wait_for_incomplete", "timeout_ms"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      numElements = (Operand<TInt32>) op.input(inputIndex++);
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      allowSmallBatch = op.attributes().getAttrBool("allow_small_batch");
+      waitForIncomplete = op.attributes().getAttrBool("wait_for_incomplete");
+      timeoutMs = op.attributes().getAttrInt("timeout_ms");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Batch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Batch.java
index af01b21cadf..ce2a30e4fce 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Batch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Batch.java
@@ -19,15 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 
 /**
@@ -92,11 +95,11 @@ private Batch(Operation operation) {
    * Factory method to create a class wrapping a new Batch operation.
    *
    * @param scope current scope
-   * @param inTensors the inTensors value
-   * @param numBatchThreads the value of the numBatchThreads property
-   * @param maxBatchSize the value of the maxBatchSize property
-   * @param batchTimeoutMicros the value of the batchTimeoutMicros property
-   * @param gradTimeoutMicros the value of the gradTimeoutMicros property
+   * @param inTensors The inTensors value
+   * @param numBatchThreads The value of the numBatchThreads attribute
+   * @param maxBatchSize The value of the maxBatchSize attribute
+   * @param batchTimeoutMicros The value of the batchTimeoutMicros attribute
+   * @param gradTimeoutMicros The value of the gradTimeoutMicros attribute
    * @param options carries optional attribute values
    * @return a new instance of Batch
    */
@@ -163,7 +166,7 @@ public static Options allowedBatchSizes(List<Long> allowedBatchSizes) {
    * @param allowedBatchSizes the allowedBatchSizes option
    * @return this Options instance.
    */
-  public static Options allowedBatchSizes(Long[] allowedBatchSizes) {
+  public static Options allowedBatchSizes(Long... allowedBatchSizes) {
     return new Options().allowedBatchSizes(allowedBatchSizes);
   }
 
@@ -307,4 +310,79 @@ public Options batchingQueue(String batchingQueue) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Batch> {
+    /**
+     * The inTensors input
+     */
+    public final Iterable<Operand<?>> inTensors;
+
+    /**
+     * The numBatchThreads attribute
+     */
+    public final long numBatchThreads;
+
+    /**
+     * The maxBatchSize attribute
+     */
+    public final long maxBatchSize;
+
+    /**
+     * The maxEnqueuedBatches attribute
+     */
+    public final long maxEnqueuedBatches;
+
+    /**
+     * The batchTimeoutMicros attribute
+     */
+    public final long batchTimeoutMicros;
+
+    /**
+     * The allowedBatchSizes attribute
+     */
+    public final long[] allowedBatchSizes;
+
+    /**
+     * The gradTimeoutMicros attribute
+     */
+    public final long gradTimeoutMicros;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    /**
+     * The batchingQueue attribute
+     */
+    public final String batchingQueue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    public Inputs(GraphOperation op) {
+      super(new Batch(op), op, Arrays.asList("num_batch_threads", "max_batch_size", "max_enqueued_batches", "batch_timeout_micros", "allowed_batch_sizes", "grad_timeout_micros", "container", "shared_name", "batching_queue", "T"));
+      int inputIndex = 0;
+      int inTensorsLength = op.inputListLength("in_tensors");
+      inTensors = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inTensorsLength));
+      inputIndex += inTensorsLength;
+      numBatchThreads = op.attributes().getAttrInt("num_batch_threads");
+      maxBatchSize = op.attributes().getAttrInt("max_batch_size");
+      maxEnqueuedBatches = op.attributes().getAttrInt("max_enqueued_batches");
+      batchTimeoutMicros = op.attributes().getAttrInt("batch_timeout_micros");
+      allowedBatchSizes = op.attributes().getAttrIntList("allowed_batch_sizes");
+      gradTimeoutMicros = op.attributes().getAttrInt("grad_timeout_micros");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      batchingQueue = op.attributes().getAttrString("batching_queue");
+      T = op.attributes().getAttrTypeList("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java
index f59367caae1..25cba54989e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -92,7 +95,7 @@ private BatchFunction(Operation operation) {
    * @param inTensors The tensors to be batched.
    * @param capturedTensors The tensors which are captured in the function, and don't need
    * to be batched.
-   * @param f the value of the f property
+   * @param f The value of the f attribute
    * @param numBatchThreads Number of scheduling threads for processing batches of work.
    * Determines the number of batches processed in parallel.
    * @param maxBatchSize Batch sizes will never be bigger than this.
@@ -180,7 +183,7 @@ public static Options allowedBatchSizes(List<Long> allowedBatchSizes) {
    * enabled) the final entry must equal max_batch_size.
    * @return this Options instance.
    */
-  public static Options allowedBatchSizes(Long[] allowedBatchSizes) {
+  public static Options allowedBatchSizes(Long... allowedBatchSizes) {
     return new Options().allowedBatchSizes(allowedBatchSizes);
   }
 
@@ -349,4 +352,109 @@ public Options enableLargeBatchSplitting(Boolean enableLargeBatchSplitting) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BatchFunction> {
+    /**
+     * The tensors to be batched.
+     */
+    public final Iterable<Operand<?>> inTensors;
+
+    /**
+     * The tensors which are captured in the function, and don't need
+     * to be batched.
+     */
+    public final Iterable<Operand<?>> capturedTensors;
+
+    /**
+     * Number of scheduling threads for processing batches of work.
+     * Determines the number of batches processed in parallel.
+     */
+    public final long numBatchThreads;
+
+    /**
+     * Batch sizes will never be bigger than this.
+     */
+    public final long maxBatchSize;
+
+    /**
+     * Maximum number of microseconds to wait before outputting
+     * an incomplete batch.
+     */
+    public final long batchTimeoutMicros;
+
+    /**
+     * Maximum number of batches enqueued. Default: 10.
+     */
+    public final long maxEnqueuedBatches;
+
+    /**
+     * Optional list of allowed batch sizes. If left empty, does
+     * nothing. Otherwise, supplies a list of batch sizes, causing the op to pad
+     * batches up to one of those sizes. The entries must increase monotonically.
+     * If enable_large_batch_splitting is false (i.e., large-input-split is not
+     * enabled) the final entry must equal max_batch_size.
+     */
+    public final long[] allowedBatchSizes;
+
+    /**
+     * Controls the scope of sharing of this batch.
+     */
+    public final String container;
+
+    /**
+     * Concurrently running instances of batch in the same device with the
+     * same container and shared_name will batch their elements together. If left
+     * empty, the op name will be used as the shared name.
+     */
+    public final String sharedName;
+
+    /**
+     * The batchingQueue attribute
+     */
+    public final String batchingQueue;
+
+    /**
+     * the types of tensors to be batched.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * the types of the captured tensors.
+     */
+    public final DataType[] Tcaptured;
+
+    /**
+     * the types of the output tensors.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * input with a large size (i.e., larger than the largest value of
+     * `allowed_batch_sizes`) will be splitted into multiple batches with batch size.
+     */
+    public final boolean enableLargeBatchSplitting;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchFunction(op), op, Arrays.asList("num_batch_threads", "max_batch_size", "batch_timeout_micros", "max_enqueued_batches", "allowed_batch_sizes", "container", "shared_name", "batching_queue", "Tin", "Tcaptured", "Tout", "enable_large_batch_splitting"));
+      int inputIndex = 0;
+      int inTensorsLength = op.inputListLength("in_tensors");
+      inTensors = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inTensorsLength));
+      inputIndex += inTensorsLength;
+      int capturedTensorsLength = op.inputListLength("captured_tensors");
+      capturedTensors = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, capturedTensorsLength));
+      inputIndex += capturedTensorsLength;
+      numBatchThreads = op.attributes().getAttrInt("num_batch_threads");
+      maxBatchSize = op.attributes().getAttrInt("max_batch_size");
+      batchTimeoutMicros = op.attributes().getAttrInt("batch_timeout_micros");
+      maxEnqueuedBatches = op.attributes().getAttrInt("max_enqueued_batches");
+      allowedBatchSizes = op.attributes().getAttrIntList("allowed_batch_sizes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      batchingQueue = op.attributes().getAttrString("batching_queue");
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tcaptured = op.attributes().getAttrTypeList("Tcaptured");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      enableLargeBatchSplitting = op.attributes().getAttrBool("enable_large_batch_splitting");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java
index b465736a7d7..9562debefb7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -67,7 +71,7 @@ private BatchToSpace(Operation operation) {
    * <pre>
    * crops = [[crop_top, crop_bottom], [crop_left, crop_right]]
    * </pre>
-   * @param blockSize the value of the blockSize property
+   * @param blockSize The value of the blockSize attribute
    * @param <T> data type for {@code BatchToSpace} output and operands
    * @return a new instance of BatchToSpace
    */
@@ -145,4 +149,48 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchToSpace<T>> {
+    /**
+     * 4-D tensor with shape
+     * {@code [batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth]}. Note that the batch size of the input tensor must be divisible by
+     * {@code block_size * block_size}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 2-D tensor of non-negative integers with shape {@code [2, 2]}. It specifies
+     * how many elements to crop from the intermediate result across the spatial
+     * dimensions as follows:
+     * <pre>
+     * crops = [[crop_top, crop_bottom], [crop_left, crop_right]]
+     * </pre>
+     */
+    public final Operand<? extends TNumber> crops;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The blockSize attribute
+     */
+    public final long blockSize;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchToSpace<>(op), op, Arrays.asList("T", "block_size", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      crops = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      blockSize = op.attributes().getAttrInt("block_size");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java
index 819550b066d..f197bf88fe1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -180,4 +184,138 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchToSpaceNd<T>> {
+    /**
+     * N-D with shape {@code input_shape = [batch] + spatial_shape + remaining_shape},
+     * where spatial_shape has M dimensions.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 1-D with shape {@code [M]}, all values must be &gt;= 1.
+     */
+    public final Operand<? extends TNumber> blockShape;
+
+    /**
+     * 2-D with shape {@code [M, 2]}, all values must be &gt;= 0.
+     * {@code crops[i] = [crop_start, crop_end]} specifies the amount to crop from input
+     * dimension {@code i + 1}, which corresponds to spatial dimension {@code i}.  It is
+     * required that
+     * {@code crop_start[i] + crop_end[i] <= block_shape[i] * input_shape[i + 1]}.
+     * <p>This operation is equivalent to the following steps:
+     * <ol>
+     * <li>
+     * <p>Reshape {@code input} to {@code reshaped} of shape:
+     * [block_shape[0], ..., block_shape[M-1],
+     * batch / prod(block_shape),
+     * input_shape[1], ..., input_shape[N-1]]
+     * </li>
+     * <li>
+     * <p>Permute dimensions of {@code reshaped} to produce {@code permuted} of shape
+     * [batch / prod(block_shape),
+     * <p>input_shape[1], block_shape[0],
+     * ...,
+     * input_shape[M], block_shape[M-1],
+     * <p>input_shape[M+1], ..., input_shape[N-1]]
+     * </li>
+     * <li>
+     * <p>Reshape {@code permuted} to produce {@code reshaped_permuted} of shape
+     * [batch / prod(block_shape),
+     * <p>input_shape[1] * block_shape[0],
+     * ...,
+     * input_shape[M] * block_shape[M-1],
+     * <p>input_shape[M+1],
+     * ...,
+     * input_shape[N-1]]
+     * </li>
+     * <li>
+     * <p>Crop the start and end of dimensions {@code [1, ..., M]} of
+     * {@code reshaped_permuted} according to {@code crops} to produce the output of shape:
+     * [batch / prod(block_shape),
+     * <p>input_shape[1] * block_shape[0] - crops[0,0] - crops[0,1],
+     * ...,
+     * input_shape[M] * block_shape[M-1] - crops[M-1,0] - crops[M-1,1],
+     * <p>input_shape[M+1], ..., input_shape[N-1]]
+     * </li>
+     * </ol>
+     * <p>Some examples:
+     * <p>(1) For the following input of shape {@code [4, 1, 1, 1]}, {@code block_shape = [2, 2]}, and
+     * {@code crops = [[0, 0], [0, 0]]}:
+     * <pre>
+     * [[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
+     * </pre>
+     * <p>The output tensor has shape {@code [1, 2, 2, 1]} and value:
+     * <pre>
+     * x = [[[[1], [2]], [[3], [4]]]]
+     * </pre>
+     * <p>(2) For the following input of shape {@code [4, 1, 1, 3]}, {@code block_shape = [2, 2]}, and
+     * {@code crops = [[0, 0], [0, 0]]}:
+     * <pre>
+     * [[[[1, 2, 3]]], [[[4, 5, 6]]], [[[7, 8, 9]]], [[[10, 11, 12]]]]
+     * </pre>
+     * <p>The output tensor has shape {@code [1, 2, 2, 3]} and value:
+     * <pre>
+     * x = [[[[1, 2, 3], [4, 5, 6]],
+     *       [[7, 8, 9], [10, 11, 12]]]]
+     * </pre>
+     * <p>(3) For the following input of shape {@code [4, 2, 2, 1]}, {@code block_shape = [2, 2]}, and
+     * {@code crops = [[0, 0], [0, 0]]}:
+     * <pre>
+     * x = [[[[1], [3]], [[9], [11]]],
+     *      [[[2], [4]], [[10], [12]]],
+     *      [[[5], [7]], [[13], [15]]],
+     *      [[[6], [8]], [[14], [16]]]]
+     * </pre>
+     * <p>The output tensor has shape {@code [1, 4, 4, 1]} and value:
+     * <pre>
+     * x = [[[[1],   [2],  [3],  [4]],
+     *      [[5],   [6],  [7],  [8]],
+     *      [[9],  [10], [11],  [12]],
+     *      [[13], [14], [15],  [16]]]]
+     * </pre>
+     * <p>(4) For the following input of shape {@code [8, 1, 3, 1]}, {@code block_shape = [2, 2]}, and
+     * {@code crops = [[0, 0], [2, 0]]}:
+     * <pre>
+     * x = [[[[0], [1], [3]]], [[[0], [9], [11]]],
+     *      [[[0], [2], [4]]], [[[0], [10], [12]]],
+     *      [[[0], [5], [7]]], [[[0], [13], [15]]],
+     *      [[[0], [6], [8]]], [[[0], [14], [16]]]]
+     * </pre>
+     * <p>The output tensor has shape {@code [2, 2, 4, 1]} and value:
+     * <pre>
+     * x = [[[[1],   [2],  [3],  [4]],
+     *       [[5],   [6],  [7],  [8]]],
+     *      [[[9],  [10], [11],  [12]],
+     *       [[13], [14], [15],  [16]]]]
+     * </pre>
+     */
+    public final Operand<? extends TNumber> crops;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The TblockShape attribute
+     */
+    public final DataType TblockShape;
+
+    /**
+     * The Tcrops attribute
+     */
+    public final DataType Tcrops;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchToSpaceNd<>(op), op, Arrays.asList("T", "Tblock_shape", "Tcrops"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      blockShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      crops = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      TblockShape = op.attributes().getAttrType("Tblock_shape");
+      Tcrops = op.attributes().getAttrType("Tcrops");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java
index 027d11b822f..e0982cfbd92 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -110,8 +114,8 @@ private Bitcast(Operation operation) {
    * Factory method to create a class wrapping a new Bitcast operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param type the value of the type property
+   * @param input The input value
+   * @param type The value of the type attribute
    * @param <U> data type for {@code Bitcast} output and operands
    * @return a new instance of Bitcast
    */
@@ -139,4 +143,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Bitcast<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new Bitcast<>(op), op, Arrays.asList("T", "type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java
index 850d7db1a2f..55d084bf691 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,8 +57,8 @@ private BroadcastDynamicShape(Operation operation) {
    * Factory method to create a class wrapping a new BroadcastArgs operation.
    *
    * @param scope current scope
-   * @param s0 the s0 value
-   * @param s1 the s1 value
+   * @param s0 The s0 value
+   * @param s1 The s1 value
    * @param <T> data type for {@code BroadcastArgs} output and operands
    * @return a new instance of BroadcastDynamicShape
    */
@@ -82,4 +86,29 @@ public Output<T> r0() {
   public Output<T> asOutput() {
     return r0;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BroadcastDynamicShape<T>> {
+    /**
+     * The s0 input
+     */
+    public final Operand<T> s0;
+
+    /**
+     * The s1 input
+     */
+    public final Operand<T> s1;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BroadcastDynamicShape<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      s0 = (Operand<T>) op.input(inputIndex++);
+      s1 = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java
index f1b36da9a40..807cf34adb8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,8 +57,8 @@ private BroadcastGradientArgs(Operation operation) {
    * Factory method to create a class wrapping a new BroadcastGradientArgs operation.
    *
    * @param scope current scope
-   * @param s0 the s0 value
-   * @param s1 the s1 value
+   * @param s0 The s0 value
+   * @param s1 The s1 value
    * @param <T> data type for {@code BroadcastGradientArgs} output and operands
    * @return a new instance of BroadcastGradientArgs
    */
@@ -86,4 +90,29 @@ public Output<T> r0() {
   public Output<T> r1() {
     return r1;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BroadcastGradientArgs<T>> {
+    /**
+     * The s0 input
+     */
+    public final Operand<T> s0;
+
+    /**
+     * The s1 input
+     */
+    public final Operand<T> s1;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BroadcastGradientArgs<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      s0 = (Operand<T>) op.input(inputIndex++);
+      s1 = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java
index deb648f6e2f..1761611649e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -109,4 +113,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BroadcastTo<T>> {
+    /**
+     * A Tensor to broadcast.
+     */
+    public final Operand<T> input;
+
+    /**
+     * An 1-D {@code int} Tensor. The shape of the desired output.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new BroadcastTo<>(op), op, Arrays.asList("T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java
index 24fecab9660..9ce50864f2b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -95,4 +99,29 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Bucketize> {
+    /**
+     * Any shape of Tensor contains with int or float type.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A sorted list of floats gives the boundary of the buckets.
+     */
+    public final float[] boundaries;
+
+    public Inputs(GraphOperation op) {
+      super(new Bucketize(op), op, Arrays.asList("T", "boundaries"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      boundaries = op.attributes().getAttrFloatList("boundaries");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Case.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Case.java
index b137e28f283..bf366e56de8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Case.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Case.java
@@ -102,7 +102,7 @@ static Options outputShapes(List<Shape> outputShapes) {
    * @param outputShapes the outputShapes option
    * @return this Options instance.
    */
-  static Options outputShapes(Shape[] outputShapes) {
+  static Options outputShapes(Shape... outputShapes) {
     return new Options().outputShapes(outputShapes);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java
index 938a931b78d..0936dc33ac8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -88,4 +92,37 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ClipByValue<T>> {
+    /**
+     * A {@code Tensor}.
+     */
+    public final Operand<T> t;
+
+    /**
+     * A 0-D (scalar) {@code Tensor}, or a {@code Tensor} with the same shape
+     * as {@code t}. The minimum value to clip by.
+     */
+    public final Operand<T> clipValueMin;
+
+    /**
+     * A 0-D (scalar) {@code Tensor}, or a {@code Tensor} with the same shape
+     * as {@code t}. The maximum value to clip by.
+     */
+    public final Operand<T> clipValueMax;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ClipByValue<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      t = (Operand<T>) op.input(inputIndex++);
+      clipValueMin = (Operand<T>) op.input(inputIndex++);
+      clipValueMax = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java
index 8ab6435aff9..65d455900d6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,11 +57,11 @@ private CollectiveGather(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveGather operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the value of the groupSize property
-   * @param groupKey the value of the groupKey property
-   * @param instanceKey the value of the instanceKey property
-   * @param shape the value of the shape property
+   * @param input The input value
+   * @param groupSize The value of the groupSize attribute
+   * @param groupKey The value of the groupKey attribute
+   * @param instanceKey The value of the instanceKey attribute
+   * @param shape The value of the shape attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveGather} output and operands
    * @return a new instance of CollectiveGather
@@ -153,4 +157,59 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CollectiveGather<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The groupSize attribute
+     */
+    public final long groupSize;
+
+    /**
+     * The groupKey attribute
+     */
+    public final long groupKey;
+
+    /**
+     * The instanceKey attribute
+     */
+    public final long instanceKey;
+
+    /**
+     * The shape attribute
+     */
+    public final Shape shape;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new CollectiveGather<>(op), op, Arrays.asList("T", "group_size", "group_key", "instance_key", "shape", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      groupSize = op.attributes().getAttrInt("group_size");
+      groupKey = op.attributes().getAttrInt("group_key");
+      instanceKey = op.attributes().getAttrInt("instance_key");
+      shape = op.attributes().getAttrShape("shape");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantFromComponents.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantFromComponents.java
index f8afbadb121..863f03c3063 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantFromComponents.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantFromComponents.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -81,4 +85,32 @@ public Output<? extends TType> encoded() {
   public Output<TType> asOutput() {
     return (Output<TType>) encoded;
   }
+
+  public static class Inputs extends RawOpInputs<CompositeTensorVariantFromComponents> {
+    /**
+     * The component tensors for the extension type value.
+     */
+    public final Iterable<Operand<?>> components;
+
+    /**
+     * String serialization for the TypeSpec.  (Note: the encoding for the TypeSpec
+     * may change in future versions of TensorFlow.)
+     */
+    public final String metadata;
+
+    /**
+     * The Tcomponents attribute
+     */
+    public final DataType[] Tcomponents;
+
+    public Inputs(GraphOperation op) {
+      super(new CompositeTensorVariantFromComponents(op), op, Arrays.asList("metadata", "Tcomponents"));
+      int inputIndex = 0;
+      int componentsLength = op.inputListLength("components");
+      components = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, componentsLength));
+      inputIndex += componentsLength;
+      metadata = op.attributes().getAttrString("metadata");
+      Tcomponents = op.attributes().getAttrTypeList("Tcomponents");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java
index 3dbad9c91b7..061ee7bf0be 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java
@@ -20,14 +20,17 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -90,4 +93,31 @@ public List<Output<?>> components() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) components.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<CompositeTensorVariantToComponents> {
+    /**
+     * A scalar {@code variant} Tensor containing an encoded ExtensionType value.
+     */
+    public final Operand<? extends TType> encoded;
+
+    /**
+     * String serialization for the TypeSpec.  Must be compatible with the
+     * `TypeSpec` contained in `encoded`.  (Note: the encoding for the TypeSpec
+     * may change in future versions of TensorFlow.)
+     */
+    public final String metadata;
+
+    /**
+     * Expected dtypes for components.
+     */
+    public final DataType[] Tcomponents;
+
+    public Inputs(GraphOperation op) {
+      super(new CompositeTensorVariantToComponents(op), op, Arrays.asList("metadata", "Tcomponents"));
+      int inputIndex = 0;
+      encoded = (Operand<? extends TType>) op.input(inputIndex++);
+      metadata = op.attributes().getAttrString("metadata");
+      Tcomponents = op.attributes().getAttrTypeList("Tcomponents");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java
index 80e2a2fe207..d4b8127f644 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Concat.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -86,4 +90,39 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Concat<T>> {
+    /**
+     * List of {@code N} Tensors to concatenate. Their ranks and types must match,
+     * and their sizes must match in all dimensions except {@code concat_dim}.
+     */
+    public final Iterable<Operand<T>> values;
+
+    /**
+     * 0-D.  The dimension along which to concatenate.  Must be in the
+     * range [-rank(values), rank(values)).
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Concat<>(op), op, Arrays.asList("T", "Tidx"));
+      int inputIndex = 0;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConsumeMutexLock.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConsumeMutexLock.java
index 9dc127e3d70..3f66976d9c6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConsumeMutexLock.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConsumeMutexLock.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -61,4 +64,17 @@ public static ConsumeMutexLock create(Scope scope, Operand<? extends TType> mute
     opBuilder.addInput(mutexLock.asOutput());
     return new ConsumeMutexLock(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ConsumeMutexLock> {
+    /**
+     * A tensor returned by {@code MutexLock}.
+     */
+    public final Operand<? extends TType> mutexLock;
+
+    public Inputs(GraphOperation op) {
+      super(new ConsumeMutexLock(op), op, Arrays.asList());
+      int inputIndex = 0;
+      mutexLock = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ControlTrigger.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ControlTrigger.java
index b60a6f674b0..03a2c6485d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ControlTrigger.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ControlTrigger.java
@@ -17,9 +17,12 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,4 +55,11 @@ public static ControlTrigger create(Scope scope) {
     OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ControlTrigger");
     return new ControlTrigger(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ControlTrigger> {
+    public Inputs(GraphOperation op) {
+      super(new ControlTrigger(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java
index d8e9700422e..4138011fac8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -121,7 +124,7 @@ public static Options debugOpsSpec(List<String> debugOpsSpec) {
    * &quot;DebugIdentity;file:///tmp/tfdbg_1;0&quot;.
    * @return this Options instance.
    */
-  public static Options debugOpsSpec(String[] debugOpsSpec) {
+  public static Options debugOpsSpec(String... debugOpsSpec) {
     return new Options().debugOpsSpec(debugOpsSpec);
   }
 
@@ -191,4 +194,39 @@ public Options debugOpsSpec(String... debugOpsSpec) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Copy<T>> {
+    /**
+     * Input tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The name of the input tensor.
+     */
+    public final String tensorName;
+
+    /**
+     * A list of debug op spec (op, url, gated_grpc) for attached debug
+     * ops. Each element of the list has the format
+     * <debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented
+     * as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1",
+     * "DebugIdentity;file:///tmp/tfdbg_1;0".
+     */
+    public final String[] debugOpsSpec;
+
+    public Inputs(GraphOperation op) {
+      super(new Copy<>(op), op, Arrays.asList("T", "tensor_name", "debug_ops_spec"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      tensorName = op.attributes().getAttrString("tensor_name");
+      debugOpsSpec = op.attributes().getAttrStringList("debug_ops_spec");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java
index 3c348d13929..d35bd8e9b81 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -119,7 +122,7 @@ public static Options debugOpsSpec(List<String> debugOpsSpec) {
    * &quot;DebugIdentity;file:///tmp/tfdbg_1;0&quot;.
    * @return this Options instance.
    */
-  public static Options debugOpsSpec(String[] debugOpsSpec) {
+  public static Options debugOpsSpec(String... debugOpsSpec) {
     return new Options().debugOpsSpec(debugOpsSpec);
   }
 
@@ -189,4 +192,39 @@ public Options debugOpsSpec(String... debugOpsSpec) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<CopyHost<T>> {
+    /**
+     * Input tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The name of the input tensor.
+     */
+    public final String tensorName;
+
+    /**
+     * A list of debug op spec (op, url, gated_grpc) for attached debug
+     * ops. Each element of the list has the format
+     * <debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented
+     * as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1",
+     * "DebugIdentity;file:///tmp/tfdbg_1;0".
+     */
+    public final String[] debugOpsSpec;
+
+    public Inputs(GraphOperation op) {
+      super(new CopyHost<>(op), op, Arrays.asList("T", "tensor_name", "debug_ops_spec"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      tensorName = op.attributes().getAttrString("tensor_name");
+      debugOpsSpec = op.attributes().getAttrStringList("debug_ops_spec");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java
index d84ead6e789..94ca8305dd7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -81,4 +85,30 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CountUpTo<T>> {
+    /**
+     * Should be from a scalar {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * If incrementing ref would bring it above limit, instead generates an
+     * 'OutOfRange' error.
+     */
+    public final long limit;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new CountUpTo<>(op), op, Arrays.asList("limit", "T"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      limit = op.attributes().getAttrInt("limit");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java
index 1668fc15c89..1011cac53b7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java
@@ -19,15 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -249,4 +252,55 @@ public Options sanitize(Boolean sanitize) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeProto> {
+    /**
+     * Tensor of serialized protos with shape {@code batch_shape}.
+     */
+    public final Operand<TString> bytes;
+
+    /**
+     * Name of the proto message type to decode.
+     */
+    public final String messageType;
+
+    /**
+     * List of strings containing proto field names. An extension field can be decoded
+     * by using its full name, e.g. EXT_PACKAGE.EXT_FIELD_NAME.
+     */
+    public final String[] fieldNames;
+
+    /**
+     * List of TF types to use for the respective field in field_names.
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * Either the special value `local://` or a path to a file containing
+     * a serialized `FileDescriptorSet`.
+     */
+    public final String descriptorSource;
+
+    /**
+     * Either `binary` or `text`.
+     */
+    public final String messageFormat;
+
+    /**
+     * Whether to sanitize the result or not.
+     */
+    public final boolean sanitize;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeProto(op), op, Arrays.asList("message_type", "field_names", "output_types", "descriptor_source", "message_format", "sanitize"));
+      int inputIndex = 0;
+      bytes = (Operand<TString>) op.input(inputIndex++);
+      messageType = op.attributes().getAttrString("message_type");
+      fieldNames = op.attributes().getAttrStringList("field_names");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      descriptorSource = op.attributes().getAttrString("descriptor_source");
+      messageFormat = op.attributes().getAttrString("message_format");
+      sanitize = op.attributes().getAttrBool("sanitize");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java
index 8826f1d4a67..ea55c769019 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DeepCopy<T>> {
+    /**
+     * The source tensor of type {@code T}.
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DeepCopy<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeleteSessionTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeleteSessionTensor.java
index e2438b7d763..47e499eba70 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeleteSessionTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeleteSessionTensor.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -55,4 +58,17 @@ public static DeleteSessionTensor create(Scope scope, Operand<TString> handle) {
     opBuilder.addInput(handle.asOutput());
     return new DeleteSessionTensor(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DeleteSessionTensor> {
+    /**
+     * The handle for a tensor stored in the session state.
+     */
+    public final Operand<TString> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new DeleteSessionTensor(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyResourceOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyResourceOp.java
index 712a226b7f9..040c054f085 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyResourceOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyResourceOp.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -99,4 +102,24 @@ public Options ignoreLookupError(Boolean ignoreLookupError) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DestroyResourceOp> {
+    /**
+     * handle to the resource to delete.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * whether to ignore the error when the resource
+     * doesn't exist.
+     */
+    public final boolean ignoreLookupError;
+
+    public Inputs(GraphOperation op) {
+      super(new DestroyResourceOp(op), op, Arrays.asList("ignore_lookup_error"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      ignoreLookupError = op.attributes().getAttrBool("ignore_lookup_error");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java
index 7fb5b12b2c5..7d828ee733b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -87,4 +91,30 @@ public Output<T> value() {
   public Output<T> asOutput() {
     return value;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DestroyTemporaryVariable<T>> {
+    /**
+     * A reference to the temporary variable tensor.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Name of the temporary variable, usually the name of the matching
+     * 'TemporaryVariable' op.
+     */
+    public final String varName;
+
+    public Inputs(GraphOperation op) {
+      super(new DestroyTemporaryVariable<>(op), op, Arrays.asList("T", "var_name"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      varName = op.attributes().getAttrString("var_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeviceIndex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeviceIndex.java
index de834ee3fb4..a06f456040c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeviceIndex.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeviceIndex.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -52,7 +55,7 @@ private DeviceIndex(Operation operation) {
    * Factory method to create a class wrapping a new DeviceIndex operation.
    *
    * @param scope current scope
-   * @param deviceNames the value of the deviceNames property
+   * @param deviceNames The value of the deviceNames attribute
    * @return a new instance of DeviceIndex
    */
   @Endpoint(
@@ -81,4 +84,17 @@ public Output<TInt32> index() {
   public Output<TInt32> asOutput() {
     return index;
   }
+
+  public static class Inputs extends RawOpInputs<DeviceIndex> {
+    /**
+     * The deviceNames attribute
+     */
+    public final String[] deviceNames;
+
+    public Inputs(GraphOperation op) {
+      super(new DeviceIndex(op), op, Arrays.asList("device_names"));
+      int inputIndex = 0;
+      deviceNames = op.attributes().getAttrStringList("device_names");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DummyMemoryCache.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DummyMemoryCache.java
index dd24b4a64af..3415b800196 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DummyMemoryCache.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DummyMemoryCache.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -72,4 +75,11 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<DummyMemoryCache> {
+    public Inputs(GraphOperation op) {
+      super(new DummyMemoryCache(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java
index f777b6b2f70..5c65adef756 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java
@@ -20,14 +20,17 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -89,7 +92,7 @@ private DynamicPartition(Operation operation) {
    * Factory method to create a class wrapping a new DynamicPartition operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param partitions Any shape.  Indices in the range {@code [0, num_partitions)}.
    * @param numPartitions The number of partitions to output.
    * @param <T> data type for {@code DynamicPartition} output and operands
@@ -121,4 +124,29 @@ public List<Output<T>> outputs() {
   public Iterator<Operand<T>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DynamicPartition<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * Any shape.  Indices in the range {@code [0, num_partitions)}.
+     */
+    public final Operand<TInt32> partitions;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DynamicPartition<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      partitions = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java
index 5cbf9e59a1d..da206083909 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -106,8 +110,8 @@ private DynamicStitch(Operation operation) {
    * Factory method to create a class wrapping a new DynamicStitch operation.
    *
    * @param scope current scope
-   * @param indices the indices value
-   * @param data the data value
+   * @param indices The indices value
+   * @param data The data value
    * @param <T> data type for {@code DynamicStitch} output and operands
    * @return a new instance of DynamicStitch
    */
@@ -135,4 +139,33 @@ public Output<T> merged() {
   public Output<T> asOutput() {
     return merged;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DynamicStitch<T>> {
+    /**
+     * The indices input
+     */
+    public final Iterable<Operand<TInt32>> indices;
+
+    /**
+     * The data input
+     */
+    public final Iterable<Operand<T>> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DynamicStitch<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      int indicesLength = op.inputListLength("indices");
+      indices = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, indicesLength));
+      inputIndex += indicesLength;
+      int dataLength = op.inputListLength("data");
+      data = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, dataLength));
+      inputIndex += dataLength;
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java
index 266d2c3c6c6..63ab6da64a9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -170,4 +174,66 @@ public Options normalize(Boolean normalize) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<EditDistance> {
+    /**
+     * The indices of the hypothesis list SparseTensor.
+     * This is an N x R int64 matrix.
+     */
+    public final Operand<TInt64> hypothesisIndices;
+
+    /**
+     * The values of the hypothesis list SparseTensor.
+     * This is an N-length vector.
+     */
+    public final Operand<T> hypothesisValues;
+
+    /**
+     * The shape of the hypothesis list SparseTensor.
+     * This is an R-length vector.
+     */
+    public final Operand<TInt64> hypothesisShape;
+
+    /**
+     * The indices of the truth list SparseTensor.
+     * This is an M x R int64 matrix.
+     */
+    public final Operand<TInt64> truthIndices;
+
+    /**
+     * The values of the truth list SparseTensor.
+     * This is an M-length vector.
+     */
+    public final Operand<T> truthValues;
+
+    /**
+     * truth indices, vector.
+     */
+    public final Operand<TInt64> truthShape;
+
+    /**
+     * boolean (if true, edit distances are normalized by length of truth).
+     *
+     * The output is:
+     */
+    public final boolean normalize;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new EditDistance(op), op, Arrays.asList("normalize", "T"));
+      int inputIndex = 0;
+      hypothesisIndices = (Operand<TInt64>) op.input(inputIndex++);
+      hypothesisValues = (Operand<T>) op.input(inputIndex++);
+      hypothesisShape = (Operand<TInt64>) op.input(inputIndex++);
+      truthIndices = (Operand<TInt64>) op.input(inputIndex++);
+      truthValues = (Operand<T>) op.input(inputIndex++);
+      truthShape = (Operand<TInt64>) op.input(inputIndex++);
+      normalize = op.attributes().getAttrBool("normalize");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java
index e83fc532726..0a06df36054 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -55,7 +59,7 @@ private Empty(Operation operation) {
    *
    * @param scope current scope
    * @param shape 1-D. Represents the shape of the output tensor.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code Empty} output and operands
    * @return a new instance of Empty
@@ -122,4 +126,29 @@ public Options init(Boolean init) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Empty<?>> {
+    /**
+     * 1-D. Represents the shape of the output tensor.
+     */
+    public final Operand<TInt32> shape;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * If True, initialize the returned tensor with the default value of dtype.  Otherwise, the implementation is free not to initializethe tensor's content.
+     */
+    public final boolean init;
+
+    public Inputs(GraphOperation op) {
+      super(new Empty<>(op), op, Arrays.asList("dtype", "init"));
+      int inputIndex = 0;
+      shape = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      init = op.attributes().getAttrBool("init");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java
index 5d96174e298..25fc298a92a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -58,9 +62,9 @@ private EmptyTensorList(Operation operation) {
    * Factory method to create a class wrapping a new EmptyTensorList operation.
    *
    * @param scope current scope
-   * @param elementShape the elementShape value
-   * @param maxNumElements the maxNumElements value
-   * @param elementDtype the value of the elementDtype property
+   * @param elementShape The elementShape value
+   * @param maxNumElements The maxNumElements value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <U> data type for {@code EmptyTensorList} output and operands
    * @return a new instance of EmptyTensorList
    */
@@ -91,4 +95,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<EmptyTensorList> {
+    /**
+     * The elementShape input
+     */
+    public final Operand<? extends TNumber> elementShape;
+
+    /**
+     * The maxNumElements input
+     */
+    public final Operand<TInt32> maxNumElements;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    /**
+     * The shapeType attribute
+     */
+    public final DataType shapeType;
+
+    public Inputs(GraphOperation op) {
+      super(new EmptyTensorList(op), op, Arrays.asList("element_dtype", "shape_type"));
+      int inputIndex = 0;
+      elementShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      maxNumElements = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+      shapeType = op.attributes().getAttrType("shape_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorMap.java
index 7bb4274e2b5..ffdf712e26e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorMap.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorMap.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -75,4 +78,11 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<EmptyTensorMap> {
+    public Inputs(GraphOperation op) {
+      super(new EmptyTensorMap(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EncodeProto.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EncodeProto.java
index 14ea6f4a3a1..3beb517b637 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EncodeProto.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EncodeProto.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 
@@ -172,4 +176,49 @@ public Options descriptorSource(String descriptorSource) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EncodeProto> {
+    /**
+     * Tensor of int32 with shape {@code [batch_shape, len(field_names)]}.
+     */
+    public final Operand<TInt32> sizes;
+
+    /**
+     * List of tensors containing values for the corresponding field.
+     */
+    public final Iterable<Operand<?>> values;
+
+    /**
+     * List of strings containing proto field names.
+     */
+    public final String[] fieldNames;
+
+    /**
+     * Name of the proto message type to decode.
+     */
+    public final String messageType;
+
+    /**
+     * The descriptorSource attribute
+     */
+    public final String descriptorSource;
+
+    /**
+     * The input types.
+     */
+    public final DataType[] TinputTypes;
+
+    public Inputs(GraphOperation op) {
+      super(new EncodeProto(op), op, Arrays.asList("field_names", "message_type", "descriptor_source", "Tinput_types"));
+      int inputIndex = 0;
+      sizes = (Operand<TInt32>) op.input(inputIndex++);
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      fieldNames = op.attributes().getAttrStringList("field_names");
+      messageType = op.attributes().getAttrString("message_type");
+      descriptorSource = op.attributes().getAttrString("descriptor_source");
+      TinputTypes = op.attributes().getAttrTypeList("Tinput_types");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java
index 26575671b80..3c7443c40b7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -83,4 +87,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<EnsureShape<T>> {
+    /**
+     * A tensor, whose shape is to be validated.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The expected (possibly partially specified) shape of the input tensor.
+     */
+    public final Shape shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new EnsureShape<>(op), op, Arrays.asList("shape", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      shape = op.attributes().getAttrShape("shape");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java
index 6451e8e8c5a..17562be32ee 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -148,4 +152,41 @@ public Options parallelIterations(Long parallelIterations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Enter<T>> {
+    /**
+     * The tensor to be made available to the child frame.
+     */
+    public final Operand<T> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The name of the child frame.
+     */
+    public final String frameName;
+
+    /**
+     * If true, the output is constant within the child frame.
+     */
+    public final boolean isConstant;
+
+    /**
+     * The number of iterations allowed to run in parallel.
+     */
+    public final long parallelIterations;
+
+    public Inputs(GraphOperation op) {
+      super(new Enter<>(op), op, Arrays.asList("T", "frame_name", "is_constant", "parallel_iterations"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      frameName = op.attributes().getAttrString("frame_name");
+      isConstant = op.attributes().getAttrBool("is_constant");
+      parallelIterations = op.attributes().getAttrInt("parallel_iterations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java
index d9cc8f881bd..2942db758b4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -76,4 +80,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Exit<T>> {
+    /**
+     * The tensor to be made available to the parent frame.
+     */
+    public final Operand<T> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Exit<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java
index b5382bba07f..0086c4259b3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -75,7 +79,7 @@ private ExpandDims(Operation operation) {
    * Factory method to create a class wrapping a new ExpandDims operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param axis 0-D (scalar). Specifies the dimension index at which to
    * expand the shape of {@code input}. Must be in the range
    * {@code [-rank(input) - 1, rank(input)]}.
@@ -107,4 +111,37 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ExpandDims<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * 0-D (scalar). Specifies the dimension index at which to
+     * expand the shape of {@code input}. Must be in the range
+     * {@code [-rank(input) - 1, rank(input)]}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tdim attribute
+     */
+    public final DataType Tdim;
+
+    public Inputs(GraphOperation op) {
+      super(new ExpandDims<>(op), op, Arrays.asList("T", "Tdim"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tdim = op.attributes().getAttrType("Tdim");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java
index 9326536a87b..9db29df2224 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -102,4 +106,49 @@ public Output<T> patches() {
   public Output<T> asOutput() {
     return patches;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ExtractVolumePatches<T>> {
+    /**
+     * 5-D Tensor with shape {@code [batch, in_planes, in_rows, in_cols, depth]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The size of the sliding window for each dimension of `input`.
+     */
+    public final long[] ksizes;
+
+    /**
+     * 1-D of length 5. How far the centers of two consecutive patches are in
+     * `input`. Must be: `[1, stride_planes, stride_rows, stride_cols, 1]`.
+     */
+    public final long[] strides;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The type of padding algorithm to use.
+     *
+     * The size-related attributes are specified as follows:
+     *
+     * ```python
+     * ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]
+     * strides = [1, stride_planes, strides_rows, strides_cols, 1]
+     * ```
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new ExtractVolumePatches<>(op), op, Arrays.asList("ksizes", "strides", "T", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      ksizes = op.attributes().getAttrIntList("ksizes");
+      strides = op.attributes().getAttrIntList("strides");
+      T = op.attributes().getAttrType("T");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java
index c4f7cd0e435..1df3bb32e39 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -101,4 +105,38 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<U extends TType> extends RawOpInputs<Fill<U>> {
+    /**
+     * 1-D. Represents the shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> dims;
+
+    /**
+     * 0-D (scalar). Value to fill the returned tensor.
+     * <p>{@literal @}compatibility(numpy)<br>
+     * Equivalent to np.full
+     * <br>{@literal @}end_compatibility
+     */
+    public final Operand<U> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The indexType attribute
+     */
+    public final DataType indexType;
+
+    public Inputs(GraphOperation op) {
+      super(new Fill<>(op), op, Arrays.asList("T", "index_type"));
+      int inputIndex = 0;
+      dims = (Operand<? extends TNumber>) op.input(inputIndex++);
+      value = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      indexType = op.attributes().getAttrType("index_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fingerprint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fingerprint.java
index ed232337e3f..805a0ad1025 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fingerprint.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fingerprint.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.TUint8;
 import org.tensorflow.types.family.TType;
@@ -105,4 +109,30 @@ public Output<TUint8> fingerprint() {
   public Output<TUint8> asOutput() {
     return fingerprint;
   }
+
+  public static class Inputs extends RawOpInputs<Fingerprint> {
+    /**
+     * Must have rank 1 or higher.
+     */
+    public final Operand<? extends TType> data;
+
+    /**
+     * Fingerprint method used by this op. Currently available method is
+     * {@code farmhash::fingerprint64}.
+     */
+    public final Operand<TString> method;
+
+    /**
+     * This can be a POD-type or string type.
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Fingerprint(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<? extends TType>) op.input(inputIndex++);
+      method = (Operand<TString>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/For.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/For.java
index 5cd95205c5e..8089e05d434 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/For.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/For.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -101,4 +104,43 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<For> {
+    /**
+     * The lower bound. An int32
+     */
+    public final Operand<TInt32> start;
+
+    /**
+     * The upper bound. An int32
+     */
+    public final Operand<TInt32> limit;
+
+    /**
+     * The increment. An int32
+     */
+    public final Operand<TInt32> delta;
+
+    /**
+     * A list of input tensors whose types are T.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * A list of dtypes.
+     */
+    public final DataType[] T;
+
+    public Inputs(GraphOperation op) {
+      super(new For(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      start = (Operand<TInt32>) op.input(inputIndex++);
+      limit = (Operand<TInt32>) op.input(inputIndex++);
+      delta = (Operand<TInt32>) op.input(inputIndex++);
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      T = op.attributes().getAttrTypeList("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java
index 62b2184b690..1507b1ca9ca 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -147,4 +151,55 @@ public Options batchDims(Long batchDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Gather<T>> {
+    /**
+     * The tensor from which to gather values. Must be at least rank
+     * {@code axis + 1}.
+     */
+    public final Operand<T> params;
+
+    /**
+     * Index tensor. Must be in range {@code [0, params.shape[axis])}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The axis in {@code params} to gather {@code indices} from. Defaults to the first
+     * dimension. Supports negative indexes.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The batchDims attribute
+     */
+    public final long batchDims;
+
+    /**
+     * The Tparams attribute
+     */
+    public final DataType Tparams;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Taxis attribute
+     */
+    public final DataType Taxis;
+
+    public Inputs(GraphOperation op) {
+      super(new Gather<>(op), op, Arrays.asList("batch_dims", "Tparams", "Tindices", "Taxis"));
+      int inputIndex = 0;
+      params = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      batchDims = op.attributes().getAttrInt("batch_dims");
+      Tparams = op.attributes().getAttrType("Tparams");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Taxis = op.attributes().getAttrType("Taxis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java
index 3d0b72d0985..0b4ee538a18 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -171,4 +175,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<GatherNd<T>> {
+    /**
+     * The tensor from which to gather values.
+     */
+    public final Operand<T> params;
+
+    /**
+     * Index tensor.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The Tparams attribute
+     */
+    public final DataType Tparams;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new GatherNd<>(op), op, Arrays.asList("Tparams", "Tindices"));
+      int inputIndex = 0;
+      params = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Tparams = op.attributes().getAttrType("Tparams");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionHandle.java
index ddc417fe239..60a52b39aaa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionHandle.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -77,4 +81,23 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<GetSessionHandle> {
+    /**
+     * The tensor to be stored.
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new GetSessionHandle(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java
index f49527c73eb..c8a85d0b714 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -82,4 +86,23 @@ public Output<T> value() {
   public Output<T> asOutput() {
     return value;
   }
+
+  public static class Inputs extends RawOpInputs<GetSessionTensor<?>> {
+    /**
+     * The handle for a tensor stored in the session state.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * The type of the output value.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new GetSessionTensor<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java
index 12869e0b856..2f6e8c9dda2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,7 +59,7 @@ private GuaranteeConst(Operation operation) {
    * Factory method to create a class wrapping a new GuaranteeConst operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code GuaranteeConst} output and operands
    * @return a new instance of GuaranteeConst
    */
@@ -81,4 +85,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<GuaranteeConst<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new GuaranteeConst<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java
index e29387af1b8..f81970293ed 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -182,4 +186,44 @@ public Options useNodeNameSharing(Boolean useNodeNameSharing) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<HashTable> {
+    /**
+     * If non-empty, this table is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this table is shared under the given name across
+     * multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * If true and shared_name is empty, the table is shared
+     * using the node name.
+     */
+    public final boolean useNodeNameSharing;
+
+    /**
+     * Type of the table keys.
+     */
+    public final DataType keyDtype;
+
+    /**
+     * Type of the table values.
+     */
+    public final DataType valueDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new HashTable(op), op, Arrays.asList("container", "shared_name", "use_node_name_sharing", "key_dtype", "value_dtype"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      useNodeNameSharing = op.attributes().getAttrBool("use_node_name_sharing");
+      keyDtype = op.attributes().getAttrType("key_dtype");
+      valueDtype = op.attributes().getAttrType("value_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java
index 0188d810dad..fc7ac24dbaf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -72,7 +76,7 @@ private HistogramFixedWidth(Operation operation) {
    * values &lt;= value_range[0] will be mapped to hist[0],
    * values &gt;= value_range[1] will be mapped to hist[-1].
    * @param nbins Scalar {@code int32 Tensor}.  Number of histogram bins.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param <U> data type for {@code HistogramFixedWidth} output and operands
    * @param <T> data type for {@code HistogramFixedWidth} output and operands
    * @return a new instance of HistogramFixedWidth
@@ -123,4 +127,43 @@ public Output<U> out() {
   public Output<U> asOutput() {
     return out;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<HistogramFixedWidth<?>> {
+    /**
+     * Numeric {@code Tensor}.
+     */
+    public final Operand<T> values;
+
+    /**
+     * Shape [2] {@code Tensor} of same {@code dtype} as {@code values}.
+     * values &lt;= value_range[0] will be mapped to hist[0],
+     * values &gt;= value_range[1] will be mapped to hist[-1].
+     */
+    public final Operand<T> valueRange;
+
+    /**
+     * Scalar {@code int32 Tensor}.  Number of histogram bins.
+     */
+    public final Operand<TInt32> nbins;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new HistogramFixedWidth<>(op), op, Arrays.asList("T", "dtype"));
+      int inputIndex = 0;
+      values = (Operand<T>) op.input(inputIndex++);
+      valueRange = (Operand<T>) op.input(inputIndex++);
+      nbins = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java
index 25cb4a0ee7e..a07329e1b19 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,7 +55,7 @@ private Identity(Operation operation) {
    * Factory method to create a class wrapping a new Identity operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code Identity} output and operands
    * @return a new instance of Identity
    */
@@ -77,4 +81,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Identity<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Identity<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IdentityN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IdentityN.java
index 794f2a63e4a..ec6b7c51e61 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IdentityN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IdentityN.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -69,7 +72,7 @@ private IdentityN(Operation operation) {
    * Factory method to create a class wrapping a new IdentityN operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of IdentityN
    */
   @Endpoint(
@@ -95,4 +98,25 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<IdentityN> {
+    /**
+     * The input input
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    public Inputs(GraphOperation op) {
+      super(new IdentityN(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      T = op.attributes().getAttrTypeList("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/If.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/If.java
index 2ba19c25f25..1a4e15f2ed6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/If.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/If.java
@@ -98,7 +98,7 @@ static Options outputShapes(List<Shape> outputShapes) {
    * @param outputShapes the outputShapes option
    * @return this Options instance.
    */
-  static Options outputShapes(Shape[] outputShapes) {
+  static Options outputShapes(Shape... outputShapes) {
     return new Options().outputShapes(outputShapes);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java
index be6d47d25ab..8dbe85ffc6e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -86,4 +90,30 @@ public Output<T> tensor() {
   public Output<T> asOutput() {
     return tensor;
   }
+
+  public static class Inputs extends RawOpInputs<ImmutableConst<?>> {
+    /**
+     * Type of the returned tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * Shape of the returned tensor.
+     */
+    public final Shape shape;
+
+    /**
+     * Name of readonly memory region used by the tensor, see
+     * NewReadOnlyMemoryRegionFromFile in tensorflow::Env.
+     */
+    public final String memoryRegionName;
+
+    public Inputs(GraphOperation op) {
+      super(new ImmutableConst<>(op), op, Arrays.asList("dtype", "shape", "memory_region_name"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      memoryRegionName = op.attributes().getAttrString("memory_region_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTable.java
index 65156cd5a92..fa23039a392 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTable.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,4 +64,41 @@ public static InitializeTable create(Scope scope, Operand<? extends TType> table
     opBuilder.addInput(values.asOutput());
     return new InitializeTable(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<InitializeTable> {
+    /**
+     * Handle to a table which will be initialized.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * Keys of type Tkey.
+     */
+    public final Operand<? extends TType> keys;
+
+    /**
+     * Values of type Tval.
+     */
+    public final Operand<? extends TType> values;
+
+    /**
+     * The Tkey attribute
+     */
+    public final DataType Tkey;
+
+    /**
+     * The Tval attribute
+     */
+    public final DataType Tval;
+
+    public Inputs(GraphOperation op) {
+      super(new InitializeTable(op), op, Arrays.asList("Tkey", "Tval"));
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      keys = (Operand<? extends TType>) op.input(inputIndex++);
+      values = (Operand<? extends TType>) op.input(inputIndex++);
+      Tkey = op.attributes().getAttrType("Tkey");
+      Tval = op.attributes().getAttrType("Tval");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java
index 27971df17b5..96f0274ddf7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -167,4 +170,54 @@ public Options offset(Long offset) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<InitializeTableFromTextFile> {
+    /**
+     * Handle to a table which will be initialized.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * Filename of a vocabulary text file.
+     */
+    public final Operand<TString> filename;
+
+    /**
+     * Column index in a line to get the table `key` values from.
+     */
+    public final long keyIndex;
+
+    /**
+     * Column index that represents information of a line to get the table
+     * `value` values from.
+     */
+    public final long valueIndex;
+
+    /**
+     * Number of elements of the file, use -1 if unknown.
+     */
+    public final long vocabSize;
+
+    /**
+     * Delimiter to separate fields in a line.
+     */
+    public final String delimiter;
+
+    /**
+     * The offset attribute
+     */
+    public final long offset;
+
+    public Inputs(GraphOperation op) {
+      super(new InitializeTableFromTextFile(op), op, Arrays.asList("key_index", "value_index", "vocab_size", "delimiter", "offset"));
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      filename = (Operand<TString>) op.input(inputIndex++);
+      keyIndex = op.attributes().getAttrInt("key_index");
+      valueIndex = op.attributes().getAttrInt("value_index");
+      vocabSize = op.attributes().getAttrInt("vocab_size");
+      delimiter = op.attributes().getAttrString("delimiter");
+      offset = op.attributes().getAttrInt("offset");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java
index 42f4d90e0a6..b0f8ad1113c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -86,4 +90,35 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<InplaceAdd<T>> {
+    /**
+     * A {@code Tensor} of type T.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A vector. Indices into the left-most dimension of {@code x}.
+     */
+    public final Operand<TInt32> i;
+
+    /**
+     * A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size.
+     */
+    public final Operand<T> v;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new InplaceAdd<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      i = (Operand<TInt32>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java
index 67be6f601a8..87329d1405f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -87,4 +91,35 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<InplaceSub<T>> {
+    /**
+     * A {@code Tensor} of type T.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A vector. Indices into the left-most dimension of {@code x}.
+     */
+    public final Operand<TInt32> i;
+
+    /**
+     * A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size.
+     */
+    public final Operand<T> v;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new InplaceSub<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      i = (Operand<TInt32>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java
index 0cdc6d077f8..b3cc7b8ca35 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -86,4 +90,35 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<InplaceUpdate<T>> {
+    /**
+     * A tensor of type {@code T}.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A vector. Indices into the left-most dimension of {@code x}.
+     */
+    public final Operand<TInt32> i;
+
+    /**
+     * A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size.
+     */
+    public final Operand<T> v;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new InplaceUpdate<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      i = (Operand<TInt32>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IsVariableInitialized.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IsVariableInitialized.java
index 30f37d85402..2d386193212 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IsVariableInitialized.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/IsVariableInitialized.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -76,4 +80,23 @@ public Output<TBool> isInitialized() {
   public Output<TBool> asOutput() {
     return isInitialized;
   }
+
+  public static class Inputs extends RawOpInputs<IsVariableInitialized> {
+    /**
+     * Should be from a {@code Variable} node. May be uninitialized.
+     */
+    public final Operand<? extends TType> ref;
+
+    /**
+     * The type of elements in the variable tensor.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new IsVariableInitialized(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      ref = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/KthOrderStatistic.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/KthOrderStatistic.java
index 000f85c7791..d8d7a3c2411 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/KthOrderStatistic.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/KthOrderStatistic.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -63,8 +66,8 @@ private KthOrderStatistic(Operation operation) {
    * Factory method to create a class wrapping a new KthOrderStatistic operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param k the value of the k property
+   * @param input The input value
+   * @param k The value of the k attribute
    * @return a new instance of KthOrderStatistic
    */
   @Endpoint(
@@ -90,4 +93,23 @@ public Output<TFloat32> output() {
   public Output<TFloat32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<KthOrderStatistic> {
+    /**
+     * The input input
+     */
+    public final Operand<TFloat32> input;
+
+    /**
+     * The k attribute
+     */
+    public final long k;
+
+    public Inputs(GraphOperation op) {
+      super(new KthOrderStatistic(op), op, Arrays.asList("k"));
+      int inputIndex = 0;
+      input = (Operand<TFloat32>) op.input(inputIndex++);
+      k = op.attributes().getAttrInt("k");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java
index 03f9bfde2fa..b8d1000d67e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -87,4 +91,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LinSpace<T>> {
+    /**
+     * 0-D tensor. First entry in the range.
+     */
+    public final Operand<T> start;
+
+    /**
+     * 0-D tensor. Last entry in the range.
+     */
+    public final Operand<T> stop;
+
+    /**
+     * 0-D tensor. Number of values to generate.
+     */
+    public final Operand<? extends TNumber> num;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new LinSpace<>(op), op, Arrays.asList("T", "Tidx"));
+      int inputIndex = 0;
+      start = (Operand<T>) op.input(inputIndex++);
+      stop = (Operand<T>) op.input(inputIndex++);
+      num = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java
index 2b8b6d6c798..d36982e1128 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -58,8 +62,8 @@ private LookupTableExport(Operation operation) {
    *
    * @param scope current scope
    * @param tableHandle Handle to the table.
-   * @param Tkeys the value of the Tkeys property
-   * @param Tvalues the value of the Tvalues property
+   * @param Tkeys The value of the Tkeys attribute
+   * @param Tvalues The value of the Tvalues attribute
    * @param <T> data type for {@code LookupTableExportV2} output and operands
    * @param <U> data type for {@code LookupTableExportV2} output and operands
    * @return a new instance of LookupTableExport
@@ -93,4 +97,29 @@ public Output<T> keys() {
   public Output<U> values() {
     return values;
   }
+
+  public static class Inputs extends RawOpInputs<LookupTableExport<?, ?>> {
+    /**
+     * Handle to the table.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * The Tkeys attribute
+     */
+    public final DataType Tkeys;
+
+    /**
+     * The Tvalues attribute
+     */
+    public final DataType Tvalues;
+
+    public Inputs(GraphOperation op) {
+      super(new LookupTableExport<>(op), op, Arrays.asList("Tkeys", "Tvalues"));
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      Tkeys = op.attributes().getAttrType("Tkeys");
+      Tvalues = op.attributes().getAttrType("Tvalues");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java
index e7d4586a47e..fb9508e2d30 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,7 +61,7 @@ private LookupTableFind(Operation operation) {
    * @param scope current scope
    * @param tableHandle Handle to the table.
    * @param keys Any shape.  Keys to look up.
-   * @param defaultValue the defaultValue value
+   * @param defaultValue The defaultValue value
    * @param <U> data type for {@code LookupTableFindV2} output and operands
    * @return a new instance of LookupTableFind
    */
@@ -88,4 +92,41 @@ public Output<U> values() {
   public Output<U> asOutput() {
     return values;
   }
+
+  public static class Inputs<U extends TType> extends RawOpInputs<LookupTableFind<U>> {
+    /**
+     * Handle to the table.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * Any shape.  Keys to look up.
+     */
+    public final Operand<? extends TType> keys;
+
+    /**
+     * The defaultValue input
+     */
+    public final Operand<U> defaultValue;
+
+    /**
+     * The Tin attribute
+     */
+    public final DataType Tin;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new LookupTableFind<>(op), op, Arrays.asList("Tin", "Tout"));
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      keys = (Operand<? extends TType>) op.input(inputIndex++);
+      defaultValue = (Operand<U>) op.input(inputIndex++);
+      Tin = op.attributes().getAttrType("Tin");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableImport.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableImport.java
index 053f2f0091d..b2483f12b25 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableImport.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableImport.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -62,4 +66,41 @@ public static LookupTableImport create(Scope scope, Operand<? extends TType> tab
     opBuilder.addInput(values.asOutput());
     return new LookupTableImport(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<LookupTableImport> {
+    /**
+     * Handle to the table.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * Any shape.  Keys to look up.
+     */
+    public final Operand<? extends TType> keys;
+
+    /**
+     * Values to associate with keys.
+     */
+    public final Operand<? extends TType> values;
+
+    /**
+     * The Tin attribute
+     */
+    public final DataType Tin;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new LookupTableImport(op), op, Arrays.asList("Tin", "Tout"));
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      keys = (Operand<? extends TType>) op.input(inputIndex++);
+      values = (Operand<? extends TType>) op.input(inputIndex++);
+      Tin = op.attributes().getAttrType("Tin");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableInsert.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableInsert.java
index f5616043057..143032f960a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableInsert.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableInsert.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -62,4 +66,41 @@ public static LookupTableInsert create(Scope scope, Operand<? extends TType> tab
     opBuilder.addInput(values.asOutput());
     return new LookupTableInsert(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<LookupTableInsert> {
+    /**
+     * Handle to the table.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * Any shape.  Keys to look up.
+     */
+    public final Operand<? extends TType> keys;
+
+    /**
+     * Values to associate with keys.
+     */
+    public final Operand<? extends TType> values;
+
+    /**
+     * The Tin attribute
+     */
+    public final DataType Tin;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new LookupTableInsert(op), op, Arrays.asList("Tin", "Tout"));
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      keys = (Operand<? extends TType>) op.input(inputIndex++);
+      values = (Operand<? extends TType>) op.input(inputIndex++);
+      Tin = op.attributes().getAttrType("Tin");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableRemove.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableRemove.java
index c732e49e4a2..1e6a0864a29 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableRemove.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableRemove.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -58,4 +62,29 @@ public static LookupTableRemove create(Scope scope, Operand<? extends TType> tab
     opBuilder.addInput(keys.asOutput());
     return new LookupTableRemove(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<LookupTableRemove> {
+    /**
+     * Handle to the table.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * Any shape.  Keys of the elements to remove.
+     */
+    public final Operand<? extends TType> keys;
+
+    /**
+     * The Tin attribute
+     */
+    public final DataType Tin;
+
+    public Inputs(GraphOperation op) {
+      super(new LookupTableRemove(op), op, Arrays.asList("Tin"));
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      keys = (Operand<? extends TType>) op.input(inputIndex++);
+      Tin = op.attributes().getAttrType("Tin");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableSize.java
index 3f830d19ae6..e437e22fa0e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableSize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -75,4 +78,17 @@ public Output<TInt64> output() {
   public Output<TInt64> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<LookupTableSize> {
+    /**
+     * Handle to the table.
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new LookupTableSize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LoopCond.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LoopCond.java
index ebec402e7c7..1322b0c6e8f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LoopCond.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LoopCond.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -76,4 +79,17 @@ public Output<TBool> output() {
   public Output<TBool> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<LoopCond> {
+    /**
+     * A boolean scalar, representing the branch predicate of the Switch op.
+     */
+    public final Operand<TBool> input;
+
+    public Inputs(GraphOperation op) {
+      super(new LoopCond(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java
index c85ad6e4d03..53a0a5b7028 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -68,7 +72,7 @@ private LowerBound(Operation operation) {
    * @param sortedInputs 2-D Tensor where each row is ordered.
    * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains
    * the values that will be searched for in {@code sorted_search_values}.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code LowerBound} output and operands
    * @param <T> data type for {@code LowerBound} output and operands
    * @return a new instance of LowerBound
@@ -118,4 +122,36 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<LowerBound<?>> {
+    /**
+     * 2-D Tensor where each row is ordered.
+     */
+    public final Operand<T> sortedInputs;
+
+    /**
+     * 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains
+     * the values that will be searched for in {@code sorted_search_values}.
+     */
+    public final Operand<T> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new LowerBound<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      sortedInputs = (Operand<T>) op.input(inputIndex++);
+      values = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MakeUnique.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MakeUnique.java
index 08c937e66d0..6e4ba6ab699 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MakeUnique.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MakeUnique.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -53,7 +56,7 @@ private MakeUnique(Operation operation) {
    * Factory method to create a class wrapping a new MakeUnique operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of MakeUnique
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<TFloat32> output() {
   public Output<TFloat32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<MakeUnique> {
+    /**
+     * The input input
+     */
+    public final Operand<TFloat32> input;
+
+    public Inputs(GraphOperation op) {
+      super(new MakeUnique(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TFloat32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java
index 3c5286f441e..035faa1eac7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -45,7 +49,7 @@ private MapClear(Operation operation) {
    * Factory method to create a class wrapping a new MapClear operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapClear
    */
@@ -174,4 +178,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapClear> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new MapClear(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapDefun.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapDefun.java
index 79a32975feb..f7762d6dbce 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapDefun.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapDefun.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,8 +29,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -75,7 +78,7 @@ private MapDefun(Operation operation) {
    * </pre>
    * @param outputTypes A list of types.
    * @param outputShapes A list of shapes.
-   * @param f the value of the f property
+   * @param f The value of the f attribute
    * @param options carries optional attribute values
    * @return a new instance of MapDefun
    */
@@ -154,4 +157,63 @@ public Options maxIntraOpParallelism(Long maxIntraOpParallelism) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapDefun> {
+    /**
+     * <pre>
+     * A list of tensors whose types are `Targuments`, corresponding to the inputs
+     * the function should be mapped over.
+     * </pre>
+     */
+    public final Iterable<Operand<?>> arguments;
+
+    /**
+     * <pre>
+     * A list of tensors whose types are `Tcaptured`, corresponding to the captured
+     * inputs of the defun.
+     * </pre>
+     */
+    public final Iterable<Operand<?>> capturedInputs;
+
+    /**
+     * A list of types.
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * A list of types.
+     */
+    public final DataType[] Tcaptured;
+
+    /**
+     * A list of types.
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * A list of shapes.
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The maxIntraOpParallelism attribute
+     */
+    public final long maxIntraOpParallelism;
+
+    public Inputs(GraphOperation op) {
+      super(new MapDefun(op), op, Arrays.asList("Targuments", "Tcaptured", "output_types", "output_shapes", "max_intra_op_parallelism"));
+      int inputIndex = 0;
+      int argumentsLength = op.inputListLength("arguments");
+      arguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argumentsLength));
+      inputIndex += argumentsLength;
+      int capturedInputsLength = op.inputListLength("captured_inputs");
+      capturedInputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, capturedInputsLength));
+      inputIndex += capturedInputsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      Tcaptured = op.attributes().getAttrTypeList("Tcaptured");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      maxIntraOpParallelism = op.attributes().getAttrInt("max_intra_op_parallelism");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java
index 62bd05c0e04..1f93fd8fae3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -52,7 +56,7 @@ private MapIncompleteSize(Operation operation) {
    * Factory method to create a class wrapping a new MapIncompleteSize operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapIncompleteSize
    */
@@ -195,4 +199,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapIncompleteSize> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new MapIncompleteSize(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java
index c6adbd2b857..6c0a543d536 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -60,9 +63,9 @@ private MapPeek(Operation operation) {
    * Factory method to create a class wrapping a new MapPeek operation.
    *
    * @param scope current scope
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapPeek
    */
@@ -208,4 +211,53 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapPeek> {
+    /**
+     * The key input
+     */
+    public final Operand<TInt64> key;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new MapPeek(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      key = (Operand<TInt64>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java
index ceadc2bef4e..30beae4600a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -52,7 +56,7 @@ private MapSize(Operation operation) {
    * Factory method to create a class wrapping a new MapSize operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapSize
    */
@@ -195,4 +199,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapSize> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new MapSize(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java
index 574cd60547f..2a23b4711f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -49,10 +53,10 @@ private MapStage(Operation operation) {
    *
    * @param scope current scope
    * @param key int64
-   * @param indices the indices value
+   * @param indices The indices value
    * @param values a list of tensors
    * dtypes A list of data types that inserted values should adhere to.
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapStage
    */
@@ -188,4 +192,70 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapStage> {
+    /**
+     * int64
+     */
+    public final Operand<TInt64> key;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * a list of tensors
+     * dtypes A list of data types that inserted values should adhere to.
+     */
+    public final Iterable<Operand<?>> values;
+
+    /**
+     * Maximum number of elements in the Staging Area. If > 0, inserts
+     * on the container will block when the capacity is reached.
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The fakeDtypes attribute
+     */
+    public final DataType[] fakeDtypes;
+
+    /**
+     * If non-empty, this queue is placed in the given container. Otherwise,
+     * a default container is used.
+     */
+    public final String container;
+
+    /**
+     * It is necessary to match this name to the matching Unstage Op.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new MapStage(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "fake_dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      key = (Operand<TInt64>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      fakeDtypes = op.attributes().getAttrTypeList("fake_dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java
index 2ef7744f042..7eb18247706 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -60,9 +63,9 @@ private MapUnstage(Operation operation) {
    * Factory method to create a class wrapping a new MapUnstage operation.
    *
    * @param scope current scope
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapUnstage
    */
@@ -208,4 +211,53 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapUnstage> {
+    /**
+     * The key input
+     */
+    public final Operand<TInt64> key;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new MapUnstage(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      key = (Operand<TInt64>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java
index 81f4f6d9be4..753817a5d3b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java
@@ -19,15 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -62,8 +65,8 @@ private MapUnstageNoKey(Operation operation) {
    * Factory method to create a class wrapping a new MapUnstageNoKey operation.
    *
    * @param scope current scope
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapUnstageNoKey
    */
@@ -211,4 +214,47 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapUnstageNoKey> {
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new MapUnstageNoKey(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java
index 80021bab383..71ae0f7c0e5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -124,4 +128,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Max<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Max<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java
index 1394ac32f14..1117e800c59 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -90,4 +94,25 @@ public Output<T> output() {
   public Output<TInt32> valueIndex() {
     return valueIndex;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Merge<T>> {
+    /**
+     * The input tensors, exactly one of which will become available.
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Merge<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java
index 103d84eb153..695c92a70e8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -124,4 +128,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Min<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Min<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java
index 023d692cc37..d557fc71ea5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -109,4 +113,46 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MirrorPad<T>> {
+    /**
+     * The input tensor to be padded.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A two-column matrix specifying the padding sizes. The number of
+     * rows must be the same as the rank of {@code input}.
+     */
+    public final Operand<? extends TNumber> paddings;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tpaddings attribute
+     */
+    public final DataType Tpaddings;
+
+    /**
+     * Either `REFLECT` or `SYMMETRIC`. In reflect mode the padded regions
+     * do not include the borders, while in symmetric mode the padded regions
+     * do include the borders. For example, if `input` is `[1, 2, 3]` and `paddings`
+     * is `[0, 2]`, then the output is `[1, 2, 3, 2, 1]` in reflect mode, and
+     * it is `[1, 2, 3, 3, 2]` in symmetric mode.
+     */
+    public final String mode;
+
+    public Inputs(GraphOperation op) {
+      super(new MirrorPad<>(op), op, Arrays.asList("T", "Tpaddings", "mode"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      paddings = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tpaddings = op.attributes().getAttrType("Tpaddings");
+      mode = op.attributes().getAttrString("mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java
index d3b94e606cf..6d4efbf43c3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -96,4 +100,42 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MirrorPadGrad<T>> {
+    /**
+     * The input tensor to be folded.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A two-column matrix specifying the padding sizes. The number of
+     * rows must be the same as the rank of {@code input}.
+     */
+    public final Operand<? extends TNumber> paddings;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tpaddings attribute
+     */
+    public final DataType Tpaddings;
+
+    /**
+     * The mode used in the `MirrorPad` op.
+     */
+    public final String mode;
+
+    public Inputs(GraphOperation op) {
+      super(new MirrorPadGrad<>(op), op, Arrays.asList("T", "Tpaddings", "mode"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      paddings = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tpaddings = op.attributes().getAttrType("Tpaddings");
+      mode = op.attributes().getAttrString("mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java
index 5640a48575d..67dda410e1f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -84,9 +87,9 @@ private MlirPassthroughOp(Operation operation) {
    * Factory method to create a class wrapping a new MlirPassthroughOp operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
-   * @param mlirModule the value of the mlirModule property
-   * @param Toutputs the value of the Toutputs property
+   * @param inputs The inputs value
+   * @param mlirModule The value of the mlirModule attribute
+   * @param Toutputs The value of the Toutputs attribute
    * @return a new instance of MlirPassthroughOp
    */
   @Endpoint(
@@ -115,4 +118,37 @@ public List<Output<?>> outputs() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<MlirPassthroughOp> {
+    /**
+     * The inputs input
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The mlirModule attribute
+     */
+    public final String mlirModule;
+
+    /**
+     * The Tinputs attribute
+     */
+    public final DataType[] Tinputs;
+
+    /**
+     * The Toutputs attribute
+     */
+    public final DataType[] Toutputs;
+
+    public Inputs(GraphOperation op) {
+      super(new MlirPassthroughOp(op), op, Arrays.asList("mlir_module", "Tinputs", "Toutputs"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      mlirModule = op.attributes().getAttrString("mlir_module");
+      Tinputs = op.attributes().getAttrTypeList("Tinputs");
+      Toutputs = op.attributes().getAttrTypeList("Toutputs");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java
index 85c6d3e59bc..ad2418679a5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,7 +63,7 @@ private MutableDenseHashTable(Operation operation) {
    * @param scope current scope
    * @param emptyKey The key used to represent empty key buckets internally. Must not
    * be used in insert or lookup operations.
-   * @param deletedKey the deletedKey value
+   * @param deletedKey The deletedKey value
    * @param valueDtype Type of the table values.
    * @param options carries optional attribute values
    * @param <T> data type for {@code MutableDenseHashTableV2} output and operands
@@ -268,4 +272,76 @@ public Options maxLoadFactor(Float maxLoadFactor) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MutableDenseHashTable> {
+    /**
+     * The key used to represent empty key buckets internally. Must not
+     * be used in insert or lookup operations.
+     */
+    public final Operand<T> emptyKey;
+
+    /**
+     * The deletedKey input
+     */
+    public final Operand<T> deletedKey;
+
+    /**
+     * If non-empty, this table is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this table is shared under the given name across
+     * multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * The useNodeNameSharing attribute
+     */
+    public final boolean useNodeNameSharing;
+
+    /**
+     * Type of the table keys.
+     */
+    public final DataType keyDtype;
+
+    /**
+     * Type of the table values.
+     */
+    public final DataType valueDtype;
+
+    /**
+     * The shape of each value.
+     */
+    public final Shape valueShape;
+
+    /**
+     * The initial number of hash table buckets. Must be a power
+     * to 2.
+     */
+    public final long initialNumBuckets;
+
+    /**
+     * The maximum ratio between number of entries and number of
+     * buckets before growing the table. Must be between 0 and 1.
+     */
+    public final float maxLoadFactor;
+
+    public Inputs(GraphOperation op) {
+      super(new MutableDenseHashTable(op), op, Arrays.asList("container", "shared_name", "use_node_name_sharing", "key_dtype", "value_dtype", "value_shape", "initial_num_buckets", "max_load_factor"));
+      int inputIndex = 0;
+      emptyKey = (Operand<T>) op.input(inputIndex++);
+      deletedKey = (Operand<T>) op.input(inputIndex++);
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      useNodeNameSharing = op.attributes().getAttrBool("use_node_name_sharing");
+      keyDtype = op.attributes().getAttrType("key_dtype");
+      valueDtype = op.attributes().getAttrType("value_dtype");
+      valueShape = op.attributes().getAttrShape("value_shape");
+      initialNumBuckets = op.attributes().getAttrInt("initial_num_buckets");
+      maxLoadFactor = op.attributes().getAttrFloat("max_load_factor");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java
index c36a434d511..dec668bf3b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -182,4 +186,44 @@ public Options useNodeNameSharing(Boolean useNodeNameSharing) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MutableHashTable> {
+    /**
+     * If non-empty, this table is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this table is shared under the given name across
+     * multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * If true and shared_name is empty, the table is shared
+     * using the node name.
+     */
+    public final boolean useNodeNameSharing;
+
+    /**
+     * Type of the table keys.
+     */
+    public final DataType keyDtype;
+
+    /**
+     * Type of the table values.
+     */
+    public final DataType valueDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new MutableHashTable(op), op, Arrays.asList("container", "shared_name", "use_node_name_sharing", "key_dtype", "value_dtype"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      useNodeNameSharing = op.attributes().getAttrBool("use_node_name_sharing");
+      keyDtype = op.attributes().getAttrType("key_dtype");
+      valueDtype = op.attributes().getAttrType("value_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java
index 642d121f525..8c11236dc3f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -207,4 +211,49 @@ public Options valueShape(Shape valueShape) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MutableHashTableOfTensors> {
+    /**
+     * If non-empty, this table is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this table is shared under the given name across
+     * multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * The useNodeNameSharing attribute
+     */
+    public final boolean useNodeNameSharing;
+
+    /**
+     * Type of the table keys.
+     */
+    public final DataType keyDtype;
+
+    /**
+     * Type of the table values.
+     */
+    public final DataType valueDtype;
+
+    /**
+     * The valueShape attribute
+     */
+    public final Shape valueShape;
+
+    public Inputs(GraphOperation op) {
+      super(new MutableHashTableOfTensors(op), op, Arrays.asList("container", "shared_name", "use_node_name_sharing", "key_dtype", "value_dtype", "value_shape"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      useNodeNameSharing = op.attributes().getAttrBool("use_node_name_sharing");
+      keyDtype = op.attributes().getAttrType("key_dtype");
+      valueDtype = op.attributes().getAttrType("value_dtype");
+      valueShape = op.attributes().getAttrShape("value_shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Mutex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Mutex.java
index 077d073461f..0c50b069a1d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Mutex.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Mutex.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -143,4 +146,25 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Mutex> {
+    /**
+     * If non-empty, this variable is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this variable is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new Mutex(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutexLock.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutexLock.java
index f455b008631..080673e5d78 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutexLock.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutexLock.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -111,4 +114,17 @@ public Output<? extends TType> mutexLock() {
   public Output<TType> asOutput() {
     return (Output<TType>) mutexLock;
   }
+
+  public static class Inputs extends RawOpInputs<MutexLock> {
+    /**
+     * The mutex resource to lock.
+     */
+    public final Operand<? extends TType> mutex;
+
+    public Inputs(GraphOperation op) {
+      super(new MutexLock(op), op, Arrays.asList());
+      int inputIndex = 0;
+      mutex = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java
index 20f02704c1e..a59d41302c5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -62,10 +66,10 @@ private NcclAllReduce(Operation operation) {
    * Factory method to create a class wrapping a new NcclAllReduce operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param reduction the value of the reduction property
-   * @param numDevices the value of the numDevices property
-   * @param sharedName the value of the sharedName property
+   * @param input The input value
+   * @param reduction The value of the reduction attribute
+   * @param numDevices The value of the numDevices attribute
+   * @param sharedName The value of the sharedName attribute
    * @param <T> data type for {@code NcclAllReduce} output and operands
    * @return a new instance of NcclAllReduce
    */
@@ -95,4 +99,41 @@ public Output<T> data() {
   public Output<T> asOutput() {
     return data;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NcclAllReduce<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The reduction attribute
+     */
+    public final String reduction;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The numDevices attribute
+     */
+    public final long numDevices;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new NcclAllReduce<>(op), op, Arrays.asList("reduction", "T", "num_devices", "shared_name"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      reduction = op.attributes().getAttrString("reduction");
+      T = op.attributes().getAttrType("T");
+      numDevices = op.attributes().getAttrInt("num_devices");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java
index 051928fcc27..c8b9e6d3d88 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -59,8 +63,8 @@ private NcclBroadcast(Operation operation) {
    * Factory method to create a class wrapping a new NcclBroadcast operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param shape the value of the shape property
+   * @param input The input value
+   * @param shape The value of the shape attribute
    * @param <T> data type for {@code NcclBroadcast} output and operands
    * @return a new instance of NcclBroadcast
    */
@@ -88,4 +92,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NcclBroadcast<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The shape attribute
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new NcclBroadcast<>(op), op, Arrays.asList("T", "shape"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java
index 41e9310df19..97f3b57983d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -59,8 +63,8 @@ private NcclReduce(Operation operation) {
    * Factory method to create a class wrapping a new NcclReduce operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param reduction the value of the reduction property
+   * @param input The input value
+   * @param reduction The value of the reduction attribute
    * @param <T> data type for {@code NcclReduce} output and operands
    * @return a new instance of NcclReduce
    */
@@ -88,4 +92,31 @@ public Output<T> data() {
   public Output<T> asOutput() {
     return data;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NcclReduce<T>> {
+    /**
+     * The input input
+     */
+    public final Iterable<Operand<T>> input;
+
+    /**
+     * The reduction attribute
+     */
+    public final String reduction;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new NcclReduce<>(op), op, Arrays.asList("reduction", "T"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      reduction = op.attributes().getAttrString("reduction");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java
index 749b779b930..63f3133570e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -77,4 +81,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<NextIteration<T>> {
+    /**
+     * The tensor to be made available to the next iteration.
+     */
+    public final Operand<T> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new NextIteration<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NoOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NoOp.java
index 1ac38903d0e..1fd31154b5d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NoOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NoOp.java
@@ -17,9 +17,12 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -51,4 +54,11 @@ public static NoOp create(Scope scope) {
     OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "NoOp");
     return new NoOp(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<NoOp> {
+    public Inputs(GraphOperation op) {
+      super(new NoOp(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java
index ba0abba8433..52e2c895139 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -199,4 +203,53 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TType> extends RawOpInputs<OneHot<U>> {
+    /**
+     * A tensor of indices.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A scalar defining the depth of the one hot dimension.
+     */
+    public final Operand<TInt32> depth;
+
+    /**
+     * A scalar defining the value to fill in output when {@code indices[j] = i}.
+     */
+    public final Operand<U> onValue;
+
+    /**
+     * A scalar defining the value to fill in output when {@code indices[j] != i}.
+     */
+    public final Operand<U> offValue;
+
+    /**
+     * The axis to fill (default: -1, a new inner-most axis).
+     */
+    public final long axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The TI attribute
+     */
+    public final DataType TI;
+
+    public Inputs(GraphOperation op) {
+      super(new OneHot<>(op), op, Arrays.asList("axis", "T", "TI"));
+      int inputIndex = 0;
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      depth = (Operand<TInt32>) op.input(inputIndex++);
+      onValue = (Operand<U>) op.input(inputIndex++);
+      offValue = (Operand<U>) op.input(inputIndex++);
+      axis = op.attributes().getAttrInt("axis");
+      T = op.attributes().getAttrType("T");
+      TI = op.attributes().getAttrType("TI");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java
index b2b7ca9aea1..cba88e78d14 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -77,4 +81,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<OnesLike<T>> {
+    /**
+     * a tensor of type T.
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new OnesLike<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java
index 0802458e81a..7899b26b3a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -45,7 +49,7 @@ private OrderedMapClear(Operation operation) {
    * Factory method to create a class wrapping a new OrderedMapClear operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapClear
    */
@@ -174,4 +178,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OrderedMapClear> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OrderedMapClear(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java
index a57953ba304..f04fbc1c64b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -52,7 +56,7 @@ private OrderedMapIncompleteSize(Operation operation) {
    * Factory method to create a class wrapping a new OrderedMapIncompleteSize operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapIncompleteSize
    */
@@ -195,4 +199,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OrderedMapIncompleteSize> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OrderedMapIncompleteSize(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java
index ae95103b6e6..91e50b0b013 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -61,9 +64,9 @@ private OrderedMapPeek(Operation operation) {
    * Factory method to create a class wrapping a new OrderedMapPeek operation.
    *
    * @param scope current scope
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapPeek
    */
@@ -209,4 +212,53 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OrderedMapPeek> {
+    /**
+     * The key input
+     */
+    public final Operand<TInt64> key;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OrderedMapPeek(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      key = (Operand<TInt64>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java
index 4c84756d610..f8f939ba8f4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -52,7 +56,7 @@ private OrderedMapSize(Operation operation) {
    * Factory method to create a class wrapping a new OrderedMapSize operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapSize
    */
@@ -195,4 +199,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OrderedMapSize> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OrderedMapSize(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java
index 760eb4ca9c2..14edbf02357 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -50,10 +54,10 @@ private OrderedMapStage(Operation operation) {
    *
    * @param scope current scope
    * @param key int64
-   * @param indices the indices value
+   * @param indices The indices value
    * @param values a list of tensors
    * dtypes A list of data types that inserted values should adhere to.
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapStage
    */
@@ -189,4 +193,70 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OrderedMapStage> {
+    /**
+     * int64
+     */
+    public final Operand<TInt64> key;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * a list of tensors
+     * dtypes A list of data types that inserted values should adhere to.
+     */
+    public final Iterable<Operand<?>> values;
+
+    /**
+     * Maximum number of elements in the Staging Area. If > 0, inserts
+     * on the container will block when the capacity is reached.
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The fakeDtypes attribute
+     */
+    public final DataType[] fakeDtypes;
+
+    /**
+     * If non-empty, this queue is placed in the given container. Otherwise,
+     * a default container is used.
+     */
+    public final String container;
+
+    /**
+     * It is necessary to match this name to the matching Unstage Op.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OrderedMapStage(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "fake_dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      key = (Operand<TInt64>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      fakeDtypes = op.attributes().getAttrTypeList("fake_dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java
index 28b1341ab2d..e6596e04550 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -60,9 +63,9 @@ private OrderedMapUnstage(Operation operation) {
    * Factory method to create a class wrapping a new OrderedMapUnstage operation.
    *
    * @param scope current scope
-   * @param key the key value
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param key The key value
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapUnstage
    */
@@ -208,4 +211,53 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OrderedMapUnstage> {
+    /**
+     * The key input
+     */
+    public final Operand<TInt64> key;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OrderedMapUnstage(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      key = (Operand<TInt64>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java
index eb283576e4a..7bc8fb6219b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java
@@ -19,15 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -62,8 +65,8 @@ private OrderedMapUnstageNoKey(Operation operation) {
    * Factory method to create a class wrapping a new OrderedMapUnstageNoKey operation.
    *
    * @param scope current scope
-   * @param indices the indices value
-   * @param dtypes the value of the dtypes property
+   * @param indices The indices value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of OrderedMapUnstageNoKey
    */
@@ -211,4 +214,47 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OrderedMapUnstageNoKey> {
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OrderedMapUnstageNoKey(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java
index 4bcbc23ecaa..434a94076fa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -72,9 +76,9 @@ private Pad(Operation operation) {
    * Factory method to create a class wrapping a new PadV2 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param paddings the paddings value
-   * @param constantValues the constantValues value
+   * @param input The input value
+   * @param paddings The paddings value
+   * @param constantValues The constantValues value
    * @param <T> data type for {@code PadV2} output and operands
    * @return a new instance of Pad
    */
@@ -103,4 +107,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Pad<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The paddings input
+     */
+    public final Operand<? extends TNumber> paddings;
+
+    /**
+     * The constantValues input
+     */
+    public final Operand<T> constantValues;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tpaddings attribute
+     */
+    public final DataType Tpaddings;
+
+    public Inputs(GraphOperation op) {
+      super(new Pad<>(op), op, Arrays.asList("T", "Tpaddings"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      paddings = (Operand<? extends TNumber>) op.input(inputIndex++);
+      constantValues = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tpaddings = op.attributes().getAttrType("Tpaddings");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java
index e126523c99d..093ac6c690d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -97,4 +101,33 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ParallelConcat<T>> {
+    /**
+     * Tensors to be concatenated. All must have size 1 in the first dimension
+     * and same shape.
+     */
+    public final Iterable<Operand<T>> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * the final shape of the result; should be equal to the shapes of any input
+     * but with the number of input values in the first dimension.
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new ParallelConcat<>(op), op, Arrays.asList("T", "shape"));
+      int inputIndex = 0;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      T = op.attributes().getAttrType("T");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java
index 3cf3afa61d6..abba8e503f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -105,8 +109,8 @@ private ParallelDynamicStitch(Operation operation) {
    * Factory method to create a class wrapping a new ParallelDynamicStitch operation.
    *
    * @param scope current scope
-   * @param indices the indices value
-   * @param data the data value
+   * @param indices The indices value
+   * @param data The data value
    * @param <T> data type for {@code ParallelDynamicStitch} output and operands
    * @return a new instance of ParallelDynamicStitch
    */
@@ -134,4 +138,33 @@ public Output<T> merged() {
   public Output<T> asOutput() {
     return merged;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ParallelDynamicStitch<T>> {
+    /**
+     * The indices input
+     */
+    public final Iterable<Operand<TInt32>> indices;
+
+    /**
+     * The data input
+     */
+    public final Iterable<Operand<T>> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ParallelDynamicStitch<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      int indicesLength = op.inputListLength("indices");
+      indices = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, indicesLength));
+      inputIndex += indicesLength;
+      int dataLength = op.inputListLength("data");
+      data = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, dataLength));
+      inputIndex += dataLength;
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java
index c8af0e07380..11a54982337 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -124,4 +128,24 @@ public Options shape(Shape shape) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Placeholder<?>> {
+    /**
+     * The type of elements in the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * (Optional) The shape of the tensor. If the shape has 0 dimensions, the
+     * shape is unconstrained.
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new Placeholder<>(op), op, Arrays.asList("dtype", "shape"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java
index cbfefa3b7e0..dec98e433f9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -81,4 +85,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<PlaceholderWithDefault<T>> {
+    /**
+     * The default value to produce when {@code output} is not fed.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The type of elements in the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * The (possibly partial) shape of the tensor.
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new PlaceholderWithDefault<>(op), op, Arrays.asList("dtype", "shape"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Print.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Print.java
index 3b5a840baba..d957b42e290 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Print.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Print.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -121,4 +124,29 @@ public Options end(String end) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Print> {
+    /**
+     * The string scalar to print.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * A string specifying the output stream or logging level to print to.
+     */
+    public final String outputStream;
+
+    /**
+     * The end attribute
+     */
+    public final String end;
+
+    public Inputs(GraphOperation op) {
+      super(new Print(op), op, Arrays.asList("output_stream", "end"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      outputStream = op.attributes().getAttrString("output_stream");
+      end = op.attributes().getAttrString("end");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java
index bdbc831c731..7404306824e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -125,4 +129,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Prod<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Prod<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java
index 109794e32d1..b301d427311 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -59,7 +63,7 @@ private QuantizedReshape(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedReshape operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
+   * @param tensor The tensor value
    * @param shape Defines the shape of the output tensor.
    * @param inputMin The minimum value of the input.
    * @param inputMax The maximum value of the input.
@@ -105,4 +109,47 @@ public Output<TFloat32> outputMin() {
   public Output<TFloat32> outputMax() {
     return outputMax;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<QuantizedReshape<T>> {
+    /**
+     * The tensor input
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * Defines the shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The minimum value of the input.
+     */
+    public final Operand<TFloat32> inputMin;
+
+    /**
+     * The maximum value of the input.
+     */
+    public final Operand<TFloat32> inputMax;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedReshape<>(op), op, Arrays.asList("T", "Tshape"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      inputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      inputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java
index efa7b52d5de..d06a61b77d7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -91,4 +95,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Range<T>> {
+    /**
+     * 0-D (scalar). First entry in the sequence.
+     */
+    public final Operand<T> start;
+
+    /**
+     * 0-D (scalar). Upper limit of sequence, exclusive.
+     */
+    public final Operand<T> limit;
+
+    /**
+     * 0-D (scalar). Optional. Default is 1. Number that increments {@code start}.
+     */
+    public final Operand<T> delta;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Range<>(op), op, Arrays.asList("Tidx"));
+      int inputIndex = 0;
+      start = (Operand<T>) op.input(inputIndex++);
+      limit = (Operand<T>) op.input(inputIndex++);
+      delta = (Operand<T>) op.input(inputIndex++);
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rank.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rank.java
index 107dcf55c3c..8561087dad8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rank.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rank.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -60,7 +64,7 @@ private Rank(Operation operation) {
    * Factory method to create a class wrapping a new Rank operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Rank
    */
   @Endpoint(
@@ -85,4 +89,23 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Rank> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Rank(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java
index 574f737fbf5..f461b9fd855 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -86,4 +90,23 @@ public Output<T> value() {
   public Output<T> asOutput() {
     return value;
   }
+
+  public static class Inputs extends RawOpInputs<ReadVariableOp<?>> {
+    /**
+     * handle to the resource in which to store the variable.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * the dtype of the value.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new ReadVariableOp<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java
index f149bf45dfd..5235cae884c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -50,7 +54,7 @@ private Recv(Operation operation) {
    * Factory method to create a class wrapping a new Recv operation.
    *
    * @param scope current scope
-   * @param tensorType the value of the tensorType property
+   * @param tensorType The value of the tensorType attribute
    * @param tensorName The name of the tensor to receive.
    * @param sendDevice The name of the device sending the tensor.
    * @param sendDeviceIncarnation The current incarnation of send_device.
@@ -131,4 +135,50 @@ public Options clientTerminated(Boolean clientTerminated) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Recv<?>> {
+    /**
+     * The tensorType attribute
+     */
+    public final DataType tensorType;
+
+    /**
+     * The name of the tensor to receive.
+     */
+    public final String tensorName;
+
+    /**
+     * The name of the device sending the tensor.
+     */
+    public final String sendDevice;
+
+    /**
+     * The current incarnation of send_device.
+     */
+    public final long sendDeviceIncarnation;
+
+    /**
+     * The name of the device receiving the tensor.
+     */
+    public final String recvDevice;
+
+    /**
+     * If set to true, this indicates that the node was added
+     * to the graph as a result of a client-side feed or fetch of Tensor data,
+     * in which case the corresponding send or recv is expected to be managed
+     * locally by the caller.
+     */
+    public final boolean clientTerminated;
+
+    public Inputs(GraphOperation op) {
+      super(new Recv<>(op), op, Arrays.asList("tensor_type", "tensor_name", "send_device", "send_device_incarnation", "recv_device", "client_terminated"));
+      int inputIndex = 0;
+      tensorType = op.attributes().getAttrType("tensor_type");
+      tensorName = op.attributes().getAttrString("tensor_name");
+      sendDevice = op.attributes().getAttrString("send_device");
+      sendDeviceIncarnation = op.attributes().getAttrInt("send_device_incarnation");
+      recvDevice = op.attributes().getAttrString("recv_device");
+      clientTerminated = op.attributes().getAttrBool("client_terminated");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java
index 2f6880725e2..8858cdeb7f4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -122,4 +126,36 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ReduceAll> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<TBool> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceAll(op), op, Arrays.asList("keep_dims", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<TBool>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java
index 268b0bdb9dd..5dcc0185ac8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -122,4 +126,36 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ReduceAny> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<TBool> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceAny(op), op, Arrays.asList("keep_dims", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<TBool>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java
index cae290b380e..913b043560d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -124,4 +128,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ReduceMax<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceMax<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java
index 34ea53c5ea2..bf69583091c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -124,4 +128,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ReduceMin<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceMin<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java
index 41fe7e66613..eb133e52ded 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -125,4 +129,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ReduceProd<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceProd<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java
index e41f01ec5e9..45222cee07a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -125,4 +129,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ReduceSum<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceSum<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java
index f1da7e2da97..aad1e84ea0d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -147,4 +151,41 @@ public Options parallelIterations(Long parallelIterations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RefEnter<T>> {
+    /**
+     * The tensor to be made available to the child frame.
+     */
+    public final Operand<T> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The name of the child frame.
+     */
+    public final String frameName;
+
+    /**
+     * If true, the output is constant within the child frame.
+     */
+    public final boolean isConstant;
+
+    /**
+     * The number of iterations allowed to run in parallel.
+     */
+    public final long parallelIterations;
+
+    public Inputs(GraphOperation op) {
+      super(new RefEnter<>(op), op, Arrays.asList("T", "frame_name", "is_constant", "parallel_iterations"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      frameName = op.attributes().getAttrString("frame_name");
+      isConstant = op.attributes().getAttrBool("is_constant");
+      parallelIterations = op.attributes().getAttrInt("parallel_iterations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java
index 126ed3227fd..42a11c140ed 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -76,4 +80,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RefExit<T>> {
+    /**
+     * The tensor to be made available to the parent frame.
+     */
+    public final Operand<T> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RefExit<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java
index d96655bda8e..b9623c181f1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -49,7 +53,7 @@ private RefIdentity(Operation operation) {
    * Factory method to create a class wrapping a new RefIdentity operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code RefIdentity} output and operands
    * @return a new instance of RefIdentity
    */
@@ -75,4 +79,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RefIdentity<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RefIdentity<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java
index 85832cf8256..911e7d845cf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -88,4 +92,25 @@ public Output<T> output() {
   public Output<TInt32> valueIndex() {
     return valueIndex;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RefMerge<T>> {
+    /**
+     * The input tensors, exactly one of which will become available.
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RefMerge<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java
index b2759dd69c6..4a56e3f5394 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -77,4 +81,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RefNextIteration<T>> {
+    /**
+     * The tensor to be made available to the next iteration.
+     */
+    public final Operand<T> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RefNextIteration<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java
index dfa4056c286..4e449068fdd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -82,4 +86,31 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RefSelect<T>> {
+    /**
+     * A scalar that determines the input that gets selected.
+     */
+    public final Operand<TInt32> index;
+
+    /**
+     * A list of ref tensors, one of which will be forwarded to {@code output}.
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RefSelect<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      index = (Operand<TInt32>) op.input(inputIndex++);
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java
index 67cc4bfda6e..47c7a63df80 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -91,4 +95,29 @@ public Output<T> outputFalse() {
   public Output<T> outputTrue() {
     return outputTrue;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RefSwitch<T>> {
+    /**
+     * The ref tensor to be forwarded to the appropriate output.
+     */
+    public final Operand<T> data;
+
+    /**
+     * A scalar that specifies which output port will receive data.
+     */
+    public final Operand<TBool> pred;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RefSwitch<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      pred = (Operand<TBool>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteCall.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteCall.java
index 7d7b1288f0e..4f53a7940a6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteCall.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteCall.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -91,4 +94,37 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<RemoteCall> {
+    /**
+     * A fully specified device name where we want to run the function.
+     */
+    public final Operand<TString> target;
+
+    /**
+     * A list of arguments for the function.
+     */
+    public final Iterable<Operand<?>> args;
+
+    /**
+     * The type list for the arguments.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * The type list for the return values.
+     */
+    public final DataType[] Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new RemoteCall(op), op, Arrays.asList("Tin", "Tout"));
+      int inputIndex = 0;
+      target = (Operand<TString>) op.input(inputIndex++);
+      int argsLength = op.inputListLength("args");
+      args = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argsLength));
+      inputIndex += argsLength;
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java
index 7a3bc9a893d..e412bf4ccc7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -106,7 +110,7 @@ private Reshape(Operation operation) {
    * Factory method to create a class wrapping a new Reshape operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
+   * @param tensor The tensor value
    * @param shape Defines the shape of the output tensor.
    * @param <T> data type for {@code Reshape} output and operands
    * @return a new instance of Reshape
@@ -135,4 +139,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Reshape<T>> {
+    /**
+     * The tensor input
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * Defines the shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new Reshape<>(op), op, Arrays.asList("T", "Tshape"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java
index 34f0284ae4b..40d808c3cbd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -56,7 +60,7 @@ private ResourceCountUpTo(Operation operation) {
    * @param resource Should be from a scalar {@code Variable} node.
    * @param limit If incrementing ref would bring it above limit, instead generates an
    * 'OutOfRange' error.
-   * @param T the value of the T property
+   * @param T The value of the T attribute
    * @param <T> data type for {@code ResourceCountUpTo} output and operands
    * @return a new instance of ResourceCountUpTo
    */
@@ -86,4 +90,30 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ResourceCountUpTo<?>> {
+    /**
+     * Should be from a scalar {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * If incrementing ref would bring it above limit, instead generates an
+     * 'OutOfRange' error.
+     */
+    public final long limit;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceCountUpTo<>(op), op, Arrays.asList("limit", "T"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      limit = op.attributes().getAttrInt("limit");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java
index fdaab3aec2c..195677c0764 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -65,9 +69,9 @@ private ResourceGather(Operation operation) {
    * Factory method to create a class wrapping a new ResourceGather operation.
    *
    * @param scope current scope
-   * @param resource the resource value
-   * @param indices the indices value
-   * @param dtype the value of the dtype property
+   * @param resource The resource value
+   * @param indices The indices value
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code ResourceGather} output and operands
    * @return a new instance of ResourceGather
@@ -162,4 +166,47 @@ public Options validateIndices(Boolean validateIndices) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResourceGather<?>> {
+    /**
+     * The resource input
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The indices input
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The batchDims attribute
+     */
+    public final long batchDims;
+
+    /**
+     * The validateIndices attribute
+     */
+    public final boolean validateIndices;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceGather<>(op), op, Arrays.asList("batch_dims", "validate_indices", "dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      batchDims = op.attributes().getAttrInt("batch_dims");
+      validateIndices = op.attributes().getAttrBool("validate_indices");
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java
index af2d44099ab..42737e67583 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -53,9 +57,9 @@ private ResourceGatherNd(Operation operation) {
    * Factory method to create a class wrapping a new ResourceGatherNd operation.
    *
    * @param scope current scope
-   * @param resource the resource value
-   * @param indices the indices value
-   * @param dtype the value of the dtype property
+   * @param resource The resource value
+   * @param indices The indices value
+   * @param dtype The value of the dtype attribute
    * @param <U> data type for {@code ResourceGatherNd} output and operands
    * @return a new instance of ResourceGatherNd
    */
@@ -84,4 +88,35 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ResourceGatherNd<?>> {
+    /**
+     * The resource input
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The indices input
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceGatherNd<>(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterAdd.java
index aac3be02552..237c62609ed 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterAdd.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -78,4 +82,41 @@ public static ResourceScatterAdd create(Scope scope, Operand<? extends TType> re
     opBuilder.addInput(updates.asOutput());
     return new ResourceScatterAdd(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterAdd> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterAdd(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterDiv.java
index 7b8f2a59f17..8568d28df4c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterDiv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterDiv.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -78,4 +82,41 @@ public static ResourceScatterDiv create(Scope scope, Operand<? extends TType> re
     opBuilder.addInput(updates.asOutput());
     return new ResourceScatterDiv(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterDiv> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterDiv(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMax.java
index 6ac4a9b54c5..68252db27f2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMax.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -78,4 +82,41 @@ public static ResourceScatterMax create(Scope scope, Operand<? extends TType> re
     opBuilder.addInput(updates.asOutput());
     return new ResourceScatterMax(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterMax> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterMax(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMin.java
index d6564b259f5..1b8a9871b5d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMin.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -78,4 +82,41 @@ public static ResourceScatterMin create(Scope scope, Operand<? extends TType> re
     opBuilder.addInput(updates.asOutput());
     return new ResourceScatterMin(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterMin> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterMin(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMul.java
index e684d3d59c3..bcf7c629746 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterMul.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -78,4 +82,41 @@ public static ResourceScatterMul create(Scope scope, Operand<? extends TType> re
     opBuilder.addInput(updates.asOutput());
     return new ResourceScatterMul(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterMul> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterMul(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java
index 2dbcbb99fb4..f3a8d9746d6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -132,4 +136,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterNdAdd> {
+    /**
+     * A resource handle. Must be from a VarHandleOp.
+     */
+    public final Operand<? extends TType> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of
+     * values to add to ref.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterNdAdd(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java
index e13320ecbbd..0899d59f311 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMax.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -106,4 +110,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterNdMax> {
+    /**
+     * A resource handle. Must be from a VarHandleOp.
+     */
+    public final Operand<? extends TType> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of
+     * values whose element wise max is taken with ref
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterNdMax(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java
index 4ae8c20a593..bf135c7094e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdMin.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -106,4 +110,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterNdMin> {
+    /**
+     * A resource handle. Must be from a VarHandleOp.
+     */
+    public final Operand<? extends TType> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of
+     * values whose element wise min is taken with ref.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterNdMin(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java
index efb90c87f24..5270a1e9bf9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -132,4 +136,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterNdSub> {
+    /**
+     * A resource handle. Must be from a VarHandleOp.
+     */
+    public final Operand<? extends TType> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of
+     * values to add to ref.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterNdSub(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java
index 14d91f6efcf..ebcfd808172 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterNdUpdate.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -133,4 +137,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterNdUpdate> {
+    /**
+     * A resource handle. Must be from a VarHandleOp.
+     */
+    public final Operand<? extends TType> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of updated
+     * values to add to ref.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterNdUpdate(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterSub.java
index 671bad91fea..73050f58930 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterSub.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -78,4 +82,41 @@ public static ResourceScatterSub create(Scope scope, Operand<? extends TType> re
     opBuilder.addInput(updates.asOutput());
     return new ResourceScatterSub(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterSub> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterSub(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterUpdate.java
index 29267287d92..ae7645b7d38 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceScatterUpdate.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -72,4 +76,41 @@ public static ResourceScatterUpdate create(Scope scope, Operand<? extends TType>
     opBuilder.addInput(updates.asOutput());
     return new ResourceScatterUpdate(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceScatterUpdate> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<? extends TType> updates;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceScatterUpdate(op), op, Arrays.asList("dtype", "Tindices"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceStridedSliceAssign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceStridedSliceAssign.java
index 955b0ada1c7..fa3670c11f9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceStridedSliceAssign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceStridedSliceAssign.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -50,11 +54,11 @@ private ResourceStridedSliceAssign(Operation operation) {
    * Factory method to create a class wrapping a new ResourceStridedSliceAssign operation.
    *
    * @param scope current scope
-   * @param ref the ref value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param value the value value
+   * @param ref The ref value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param value The value value
    * @param options carries optional attribute values
    * @param <T> data type for {@code ResourceStridedSliceAssign} output and operands
    * @return a new instance of ResourceStridedSliceAssign
@@ -215,4 +219,83 @@ public Options shrinkAxisMask(Long shrinkAxisMask) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ResourceStridedSliceAssign> {
+    /**
+     * The ref input
+     */
+    public final Operand<? extends TType> ref;
+
+    /**
+     * The begin input
+     */
+    public final Operand<T> begin;
+
+    /**
+     * The end input
+     */
+    public final Operand<T> end;
+
+    /**
+     * The strides input
+     */
+    public final Operand<T> strides;
+
+    /**
+     * The value input
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    /**
+     * The beginMask attribute
+     */
+    public final long beginMask;
+
+    /**
+     * The endMask attribute
+     */
+    public final long endMask;
+
+    /**
+     * The ellipsisMask attribute
+     */
+    public final long ellipsisMask;
+
+    /**
+     * The newAxisMask attribute
+     */
+    public final long newAxisMask;
+
+    /**
+     * The shrinkAxisMask attribute
+     */
+    public final long shrinkAxisMask;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceStridedSliceAssign(op), op, Arrays.asList("T", "Index", "begin_mask", "end_mask", "ellipsis_mask", "new_axis_mask", "shrink_axis_mask"));
+      int inputIndex = 0;
+      ref = (Operand<? extends TType>) op.input(inputIndex++);
+      begin = (Operand<T>) op.input(inputIndex++);
+      end = (Operand<T>) op.input(inputIndex++);
+      strides = (Operand<T>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Index = op.attributes().getAttrType("Index");
+      beginMask = op.attributes().getAttrInt("begin_mask");
+      endMask = op.attributes().getAttrInt("end_mask");
+      ellipsisMask = op.attributes().getAttrInt("ellipsis_mask");
+      newAxisMask = op.attributes().getAttrInt("new_axis_mask");
+      shrinkAxisMask = op.attributes().getAttrInt("shrink_axis_mask");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java
index 837592b303e..6cb5d89fa7f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -124,4 +128,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Reverse<T>> {
+    /**
+     * Up to 8-D.
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * 1-D. The indices of the dimensions to reverse. Must be in the range
+     * {@code [-rank(tensor), rank(tensor))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Reverse<>(op), op, Arrays.asList("Tidx", "T"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Tidx = op.attributes().getAttrType("Tidx");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java
index daf11cec5d7..00bc24272c8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -171,4 +175,48 @@ public Options batchDim(Long batchDim) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ReverseSequence<T>> {
+    /**
+     * The input to reverse.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 1-D with length {@code input.dims(batch_dim)} and
+     * {@code max(seq_lengths) <= input.dims(seq_dim)}
+     */
+    public final Operand<? extends TNumber> seqLengths;
+
+    /**
+     * The dimension which is partially reversed.
+     */
+    public final long seqDim;
+
+    /**
+     * The dimension along which reversal is performed.
+     */
+    public final long batchDim;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tlen attribute
+     */
+    public final DataType Tlen;
+
+    public Inputs(GraphOperation op) {
+      super(new ReverseSequence<>(op), op, Arrays.asList("seq_dim", "batch_dim", "T", "Tlen"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      seqLengths = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seqDim = op.attributes().getAttrInt("seq_dim");
+      batchDim = op.attributes().getAttrInt("batch_dim");
+      T = op.attributes().getAttrType("T");
+      Tlen = op.attributes().getAttrType("Tlen");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java
index aac1ac5b97c..83983cf1983 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -70,7 +74,7 @@ private Roll(Operation operation) {
    * Factory method to create a class wrapping a new Roll operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param shift Dimension must be 0-D or 1-D. {@code shift[i]} specifies the number of places by which
    * elements are shifted positively (towards larger indices) along the dimension
    * specified by {@code axis[i]}. Negative shifts will roll the elements in the opposite
@@ -109,4 +113,53 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Roll<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * Dimension must be 0-D or 1-D. {@code shift[i]} specifies the number of places by which
+     * elements are shifted positively (towards larger indices) along the dimension
+     * specified by {@code axis[i]}. Negative shifts will roll the elements in the opposite
+     * direction.
+     */
+    public final Operand<? extends TNumber> shift;
+
+    /**
+     * Dimension must be 0-D or 1-D. {@code axis[i]} specifies the dimension that the shift
+     * {@code shift[i]} should occur. If the same axis is referenced more than once, the
+     * total shift for that axis will be the sum of all the shifts that belong to that
+     * axis.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tshift attribute
+     */
+    public final DataType Tshift;
+
+    /**
+     * The Taxis attribute
+     */
+    public final DataType Taxis;
+
+    public Inputs(GraphOperation op) {
+      super(new Roll<>(op), op, Arrays.asList("T", "Tshift", "Taxis"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      shift = (Operand<? extends TNumber>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tshift = op.attributes().getAttrType("Tshift");
+      Taxis = op.attributes().getAttrType("Taxis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java
index c81635554e4..1f2bb33ba0d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -144,4 +148,48 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterAdd<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to add to {@code ref}.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the addition will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterAdd<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java
index 4b10a83e82e..da43641571e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -141,4 +145,48 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterDiv<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of values that {@code ref} is divided by.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the operation will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterDiv<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java
index 78e7a0941e2..136fa5c92e1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -143,4 +147,48 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ScatterMax<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to reduce into {@code ref}.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the update will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterMax<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java
index 3123ee56351..8b48aecb808 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -143,4 +147,48 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ScatterMin<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to reduce into {@code ref}.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the update will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterMin<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java
index 69b0b2d4f0a..8a979cf3a05 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -141,4 +145,48 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterMul<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to multiply to {@code ref}.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the operation will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterMul<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java
index 9527ab8a9d1..ae84b7cf6ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -153,4 +157,41 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber, U extends TType> extends RawOpInputs<ScatterNd<U>> {
+    /**
+     * Index tensor.
+     */
+    public final Operand<T> indices;
+
+    /**
+     * Updates to scatter into output.
+     */
+    public final Operand<U> updates;
+
+    /**
+     * 1-D. The shape of the resulting tensor.
+     */
+    public final Operand<T> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterNd<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      indices = (Operand<T>) op.input(inputIndex++);
+      updates = (Operand<U>) op.input(inputIndex++);
+      shape = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java
index 0637e6e539f..50d897a1941 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -155,4 +159,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterNdAdd<T>> {
+    /**
+     * A mutable Tensor. Should be from a Variable node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of updated values
+     * to add to ref.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterNdAdd<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java
index c518f023126..2783d423634 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -127,4 +131,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterNdMax<T>> {
+    /**
+     * A mutable Tensor. Should be from a Variable node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of updated values
+     * to add to ref.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterNdMax<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java
index e273fac503d..19415c2abd9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -127,4 +131,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterNdMin<T>> {
+    /**
+     * A mutable Tensor. Should be from a Variable node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of updated values
+     * to add to ref.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterNdMin<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java
index 585cfaae92e..d8e6cdb20de 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -113,4 +117,43 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterNdNonAliasingAdd<T>> {
+    /**
+     * A Tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A Tensor. Must be one of the following types: {@code int32}, {@code int64}.
+     * A tensor of indices into {@code input}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of updated values
+     * to add to {@code input}.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterNdNonAliasingAdd<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java
index ee2cff02224..71100507d7d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -156,4 +160,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterNdSub<T>> {
+    /**
+     * A mutable Tensor. Should be from a Variable node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of updated values
+     * to subtract from ref.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterNdSub<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java
index ba0b795aa83..9ee766d0c98 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -155,4 +159,51 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterNdUpdate<T>> {
+    /**
+     * A mutable Tensor. Should be from a Variable node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A Tensor. Must be one of the following types: int32, int64.
+     * A tensor of indices into ref.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A Tensor. Must have the same type as ref. A tensor of updated
+     * values to add to ref.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * An optional bool. Defaults to True. If True, the assignment will
+     * be protected by a lock; otherwise the behavior is undefined,
+     * but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterNdUpdate<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java
index cae017a50ac..7ebbd6730ad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -143,4 +147,48 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterSub<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to subtract from {@code ref}.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterSub<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java
index 4bd3154363b..cc9cebb665f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -146,4 +150,48 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ScatterUpdate<T>> {
+    /**
+     * Should be from a {@code Variable} node.
+     */
+    public final Operand<T> ref;
+
+    /**
+     * A tensor of indices into the first dimension of {@code ref}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A tensor of updated values to store in {@code ref}.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the assignment will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ScatterUpdate<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java
index 440d414329a..b112acf4e8c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -52,9 +56,9 @@ private Select(Operation operation) {
    * Factory method to create a class wrapping a new SelectV2 operation.
    *
    * @param scope current scope
-   * @param condition the condition value
-   * @param t the t value
-   * @param e the e value
+   * @param condition The condition value
+   * @param t The t value
+   * @param e The e value
    * @param <T> data type for {@code SelectV2} output and operands
    * @return a new instance of Select
    */
@@ -83,4 +87,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Select<T>> {
+    /**
+     * The condition input
+     */
+    public final Operand<TBool> condition;
+
+    /**
+     * The t input
+     */
+    public final Operand<T> t;
+
+    /**
+     * The e input
+     */
+    public final Operand<T> e;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Select<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      condition = (Operand<TBool>) op.input(inputIndex++);
+      t = (Operand<T>) op.input(inputIndex++);
+      e = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Send.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Send.java
index 5109bd3822b..7822dbe0ab6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Send.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Send.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -107,4 +111,56 @@ public Options clientTerminated(Boolean clientTerminated) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Send> {
+    /**
+     * The tensor to send.
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The name of the tensor to send.
+     */
+    public final String tensorName;
+
+    /**
+     * The name of the device sending the tensor.
+     */
+    public final String sendDevice;
+
+    /**
+     * The current incarnation of send_device.
+     */
+    public final long sendDeviceIncarnation;
+
+    /**
+     * The name of the device receiving the tensor.
+     */
+    public final String recvDevice;
+
+    /**
+     * If set to true, this indicates that the node was added
+     * to the graph as a result of a client-side feed or fetch of Tensor data,
+     * in which case the corresponding send or recv is expected to be managed
+     * locally by the caller.
+     */
+    public final boolean clientTerminated;
+
+    public Inputs(GraphOperation op) {
+      super(new Send(op), op, Arrays.asList("T", "tensor_name", "send_device", "send_device_incarnation", "recv_device", "client_terminated"));
+      int inputIndex = 0;
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      tensorName = op.attributes().getAttrString("tensor_name");
+      sendDevice = op.attributes().getAttrString("send_device");
+      sendDeviceIncarnation = op.attributes().getAttrInt("send_device_incarnation");
+      recvDevice = op.attributes().getAttrString("recv_device");
+      clientTerminated = op.attributes().getAttrBool("client_terminated");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java
index 97a1e34ec7c..b777c48ccbc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -77,7 +81,7 @@ private SetDiff1d(Operation operation) {
    * @param scope current scope
    * @param x 1-D. Values to keep.
    * @param y 1-D. Values to remove.
-   * @param outIdx the value of the outIdx property
+   * @param outIdx The value of the outIdx attribute
    * @param <T> data type for {@code ListDiff} output and operands
    * @param <U> data type for {@code ListDiff} output and operands
    * @return a new instance of SetDiff1d
@@ -128,4 +132,35 @@ public Output<T> out() {
   public Output<U> idx() {
     return idx;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SetDiff1d<T, ?>> {
+    /**
+     * 1-D. Values to keep.
+     */
+    public final Operand<T> x;
+
+    /**
+     * 1-D. Values to remove.
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outIdx attribute
+     */
+    public final DataType outIdx;
+
+    public Inputs(GraphOperation op) {
+      super(new SetDiff1d<>(op), op, Arrays.asList("T", "out_idx"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outIdx = op.attributes().getAttrType("out_idx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetSize.java
index c604a916ab0..8872c75a20f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetSize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -127,4 +131,41 @@ public Options validateIndices(Boolean validateIndices) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SetSize> {
+    /**
+     * 2D {@code Tensor}, indices of a {@code SparseTensor}.
+     */
+    public final Operand<TInt64> setIndices;
+
+    /**
+     * 1D {@code Tensor}, values of a {@code SparseTensor}.
+     */
+    public final Operand<? extends TType> setValues;
+
+    /**
+     * 1D {@code Tensor}, shape of a {@code SparseTensor}.
+     */
+    public final Operand<TInt64> setShape;
+
+    /**
+     * The validateIndices attribute
+     */
+    public final boolean validateIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SetSize(op), op, Arrays.asList("validate_indices", "T"));
+      int inputIndex = 0;
+      setIndices = (Operand<TInt64>) op.input(inputIndex++);
+      setValues = (Operand<? extends TType>) op.input(inputIndex++);
+      setShape = (Operand<TInt64>) op.input(inputIndex++);
+      validateIndices = op.attributes().getAttrBool("validate_indices");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java
index 64a2b0a20b4..836ace328b7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -60,8 +64,8 @@ private Shape(Operation operation) {
    * Factory method to create a class wrapping a new Shape operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code Shape} output and operands
    * @return a new instance of Shape
    */
@@ -80,7 +84,7 @@ public static <U extends TNumber> Shape<U> create(Scope scope, Operand<? extends
    * Factory method to create a class wrapping a new Shape operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Shape, with default output types
    */
   @Endpoint(
@@ -103,4 +107,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Shape<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new Shape<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java
index 7b253f50380..34a95d4de91 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -61,8 +64,8 @@ private ShapeN(Operation operation) {
    * Factory method to create a class wrapping a new ShapeN operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code ShapeN} output and operands
    * @return a new instance of ShapeN
    */
@@ -81,7 +84,7 @@ public static <U extends TNumber> ShapeN<U> create(Scope scope,
    * Factory method to create a class wrapping a new ShapeN operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of ShapeN, with default output types
    */
   @Endpoint(
@@ -105,4 +108,31 @@ public List<Output<U>> output() {
   public Iterator<Operand<U>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<ShapeN<?>> {
+    /**
+     * The input input
+     */
+    public final Iterable<Operand<? extends TType>> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new ShapeN<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java
index 0f53c9b0d96..2a0eed3e437 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -61,8 +65,8 @@ private Size(Operation operation) {
    * Factory method to create a class wrapping a new Size operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code Size} output and operands
    * @return a new instance of Size
    */
@@ -81,7 +85,7 @@ public static <U extends TNumber> Size<U> create(Scope scope, Operand<? extends
    * Factory method to create a class wrapping a new Size operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Size, with default output types
    */
   @Endpoint(
@@ -104,4 +108,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Size<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new Size<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Skipgram.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Skipgram.java
index f456a2cfe18..f4ef6d93e92 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Skipgram.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Skipgram.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -239,4 +242,43 @@ public Options subsample(Float subsample) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Skipgram> {
+    /**
+     * The corpus's text file name.
+     */
+    public final String filename;
+
+    /**
+     * The size of produced batch.
+     */
+    public final long batchSize;
+
+    /**
+     * The number of words to predict to the left and right of the target.
+     */
+    public final long windowSize;
+
+    /**
+     * The minimum number of word occurrences for it to be included in the
+     * vocabulary.
+     */
+    public final long minCount;
+
+    /**
+     * Threshold for word occurrence. Words that appear with higher
+     * frequency will be randomly down-sampled. Set to 0 to disable.
+     */
+    public final float subsample;
+
+    public Inputs(GraphOperation op) {
+      super(new Skipgram(op), op, Arrays.asList("filename", "batch_size", "window_size", "min_count", "subsample"));
+      int inputIndex = 0;
+      filename = op.attributes().getAttrString("filename");
+      batchSize = op.attributes().getAttrInt("batch_size");
+      windowSize = op.attributes().getAttrInt("window_size");
+      minCount = op.attributes().getAttrInt("min_count");
+      subsample = op.attributes().getAttrFloat("subsample");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java
index 0a746d7218c..733a500cca8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -57,7 +61,7 @@ private Slice(Operation operation) {
    * Factory method to create a class wrapping a new Slice operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param begin begin[i] specifies the offset into the 'i'th dimension of
    * 'input' to slice from.
    * @param sizeOutput size[i] specifies the number of elements of the 'i'th dimension
@@ -93,4 +97,45 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<Slice<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * begin[i] specifies the offset into the 'i'th dimension of
+     * 'input' to slice from.
+     */
+    public final Operand<U> begin;
+
+    /**
+     * size[i] specifies the number of elements of the 'i'th dimension
+     * of 'input' to slice. If size[i] is -1, all remaining elements in dimension
+     * i are included in the slice (i.e. this is equivalent to setting
+     * size[i] = input.dim_size(i) - begin[i]).
+     */
+    public final Operand<U> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    public Inputs(GraphOperation op) {
+      super(new Slice<>(op), op, Arrays.asList("T", "Index"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      begin = (Operand<U>) op.input(inputIndex++);
+      sizeOutput = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Index = op.attributes().getAttrType("Index");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java
index c4c48291adb..10ccbddac2f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,7 +55,7 @@ private Snapshot(Operation operation) {
    * Factory method to create a class wrapping a new Snapshot operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code Snapshot} output and operands
    * @return a new instance of Snapshot
    */
@@ -77,4 +81,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Snapshot<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Snapshot<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java
index 16509bc4a85..d7a39406724 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -183,4 +187,51 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SpaceToBatchNd<T>> {
+    /**
+     * N-D with shape {@code input_shape = [batch] + spatial_shape + remaining_shape},
+     * where spatial_shape has {@code M} dimensions.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 1-D with shape {@code [M]}, all values must be &gt;= 1.
+     */
+    public final Operand<? extends TNumber> blockShape;
+
+    /**
+     * 2-D with shape {@code [M, 2]}, all values must be &gt;= 0.
+     * {@code paddings[i] = [pad_start, pad_end]} specifies the padding for input dimension
+     * {@code i + 1}, which corresponds to spatial dimension {@code i}.  It is required that
+     * {@code block_shape[i]} divides {@code input_shape[i + 1] + pad_start + pad_end}.
+     */
+    public final Operand<? extends TNumber> paddings;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The TblockShape attribute
+     */
+    public final DataType TblockShape;
+
+    /**
+     * The Tpaddings attribute
+     */
+    public final DataType Tpaddings;
+
+    public Inputs(GraphOperation op) {
+      super(new SpaceToBatchNd<>(op), op, Arrays.asList("T", "Tblock_shape", "Tpaddings"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      blockShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      paddings = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      TblockShape = op.attributes().getAttrType("Tblock_shape");
+      Tpaddings = op.attributes().getAttrType("Tpaddings");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java
index a6427f4b6e6..def301c84d3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java
@@ -20,14 +20,17 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -94,4 +97,30 @@ public List<Output<T>> output() {
   public Iterator<Operand<T>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Split<T>> {
+    /**
+     * 0-D.  The dimension along which to split.  Must be in the range
+     * {@code [-rank(value), rank(value))}.
+     */
+    public final Operand<TInt32> axis;
+
+    /**
+     * The tensor to split.
+     */
+    public final Operand<T> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Split<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      axis = (Operand<TInt32>) op.input(inputIndex++);
+      value = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java
index 6bec947b699..26d0cc172ce 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java
@@ -20,14 +20,17 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -65,7 +68,7 @@ private SplitV(Operation operation) {
    * Can contain one -1 indicating that dimension is to be inferred.
    * @param axis 0-D.  The dimension along which to split.  Must be in the range
    * {@code [-rank(value), rank(value))}.
-   * @param numSplit the value of the numSplit property
+   * @param numSplit The value of the numSplit attribute
    * @param <T> data type for {@code SplitV} output and operands
    * @return a new instance of SplitV
    */
@@ -98,4 +101,44 @@ public List<Output<T>> output() {
   public Iterator<Operand<T>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SplitV<T>> {
+    /**
+     * The tensor to split.
+     */
+    public final Operand<T> value;
+
+    /**
+     * list containing the sizes of each output tensor along the split
+     * dimension. Must sum to the dimension of value along split_dim.
+     * Can contain one -1 indicating that dimension is to be inferred.
+     */
+    public final Operand<? extends TNumber> sizeSplits;
+
+    /**
+     * 0-D.  The dimension along which to split.  Must be in the range
+     * {@code [-rank(value), rank(value))}.
+     */
+    public final Operand<TInt32> axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tlen attribute
+     */
+    public final DataType Tlen;
+
+    public Inputs(GraphOperation op) {
+      super(new SplitV<>(op), op, Arrays.asList("T", "Tlen"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      sizeSplits = (Operand<? extends TNumber>) op.input(inputIndex++);
+      axis = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tlen = op.attributes().getAttrType("Tlen");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java
index a835bd6a74b..d9c8956f5a1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -113,7 +116,7 @@ public static Options axis(List<Long> axis) {
    * be in the range {@code [-rank(input), rank(input))}.
    * @return this Options instance.
    */
-  public static Options axis(Long[] axis) {
+  public static Options axis(Long... axis) {
     return new Options().axis(axis);
   }
 
@@ -167,4 +170,31 @@ public Options axis(Long... axis) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Squeeze<T>> {
+    /**
+     * The {@code input} to squeeze.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If specified, only squeezes the dimensions listed. The dimension
+     * index starts at 0. It is an error to squeeze a dimension that is not 1. Must
+     * be in the range `[-rank(input), rank(input))`.
+     */
+    public final long[] axis;
+
+    public Inputs(GraphOperation op) {
+      super(new Squeeze<>(op), op, Arrays.asList("T", "squeeze_dims"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      axis = op.attributes().getAttrIntList("squeeze_dims");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java
index 7c8e0e5a906..be4cdfe3921 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -135,4 +139,32 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Stack<T>> {
+    /**
+     * Must be of same shape and type.
+     */
+    public final Iterable<Operand<T>> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Dimension along which to pack.  Negative values wrap around, so the
+     * valid range is `[-(R+1), R+1)`.
+     */
+    public final long axis;
+
+    public Inputs(GraphOperation op) {
+      super(new Stack<>(op), op, Arrays.asList("T", "axis"));
+      int inputIndex = 0;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      T = op.attributes().getAttrType("T");
+      axis = op.attributes().getAttrInt("axis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java
index 3256cf414d0..adc05358314 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * Stage values similar to a lightweight Enqueue.
@@ -181,4 +185,53 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Stage> {
+    /**
+     * a list of tensors
+     * dtypes A list of data types that inserted values should adhere to.
+     */
+    public final Iterable<Operand<?>> values;
+
+    /**
+     * Maximum number of elements in the Staging Area. If > 0, inserts
+     * on the container will block when the capacity is reached.
+     */
+    public final long capacity;
+
+    /**
+     * The maximum number of bytes allowed for Tensors in the Staging Area.
+     * If > 0, inserts will block until sufficient space is available.
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * If non-empty, this queue is placed in the given container. Otherwise,
+     * a default container is used.
+     */
+    public final String container;
+
+    /**
+     * It is necessary to match this name to the matching Unstage Op.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new Stage(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java
index 5b0783a7749..9431054d8a7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -45,7 +49,7 @@ private StageClear(Operation operation) {
    * Factory method to create a class wrapping a new StageClear operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of StageClear
    */
@@ -174,4 +178,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StageClear> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new StageClear(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java
index aec3b040f83..dab381005af 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -60,8 +63,8 @@ private StagePeek(Operation operation) {
    * Factory method to create a class wrapping a new StagePeek operation.
    *
    * @param scope current scope
-   * @param index the index value
-   * @param dtypes the value of the dtypes property
+   * @param index The index value
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of StagePeek
    */
@@ -206,4 +209,47 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StagePeek> {
+    /**
+     * The index input
+     */
+    public final Operand<TInt32> index;
+
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new StagePeek(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      index = (Operand<TInt32>) op.input(inputIndex++);
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java
index e850b1ef705..609a40599a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -52,7 +56,7 @@ private StageSize(Operation operation) {
    * Factory method to create a class wrapping a new StageSize operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of StageSize
    */
@@ -195,4 +199,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StageSize> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new StageSize(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulCase.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulCase.java
index 33592086451..a040d5ccd26 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulCase.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulCase.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,9 +29,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -131,4 +134,43 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatefulCase> {
+    /**
+     * The branch selector, an int32 Tensor.
+     */
+    public final Operand<TInt32> branchIndex;
+
+    /**
+     * A list of input tensors passed to the branch function.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * A list of input types.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * A list of output types.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulCase(op), op, Arrays.asList("Tin", "Tout", "output_shapes"));
+      int inputIndex = 0;
+      branchIndex = (Operand<TInt32>) op.input(inputIndex++);
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulIf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulIf.java
index 9aa0ff99791..98dfb290406 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulIf.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulIf.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,9 +29,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -120,4 +123,56 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatefulIf> {
+    /**
+     * <pre>
+     *   A Tensor. If the tensor is a scalar of non-boolean type, the
+     *   scalar is converted to a boolean according to the
+     *   following rule: if the scalar is a numerical value, non-zero means
+     *   `True` and zero means False; if the scalar is a string, non-empty
+     *   means `True` and empty means `False`. If the tensor is not a scalar,
+     *   being empty means False and being non-empty means True.
+     * </pre>
+     */
+    public final Operand<? extends TType> cond;
+
+    /**
+     * A list of input tensors.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * The Tcond attribute
+     */
+    public final DataType Tcond;
+
+    /**
+     * A list of input types.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * A list of output types.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulIf(op), op, Arrays.asList("Tcond", "Tin", "Tout", "output_shapes"));
+      int inputIndex = 0;
+      cond = (Operand<? extends TType>) op.input(inputIndex++);
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      Tcond = op.attributes().getAttrType("Tcond");
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulPartitionedCall.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulPartitionedCall.java
index 465930a4057..00572804fb3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulPartitionedCall.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulPartitionedCall.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -109,4 +112,49 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatefulPartitionedCall> {
+    /**
+     * A list of input tensors.
+     */
+    public final Iterable<Operand<?>> args;
+
+    /**
+     * A list of input types.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * A list of output types.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    /**
+     * The configProto attribute
+     */
+    public final String configProto;
+
+    /**
+     * The executorType attribute
+     */
+    public final String executorType;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulPartitionedCall(op), op, Arrays.asList("Tin", "Tout", "config", "config_proto", "executor_type"));
+      int inputIndex = 0;
+      int argsLength = op.inputListLength("args");
+      args = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argsLength));
+      inputIndex += argsLength;
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      config = op.attributes().getAttrString("config");
+      configProto = op.attributes().getAttrString("config_proto");
+      executorType = op.attributes().getAttrString("executor_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulWhile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulWhile.java
index 4ea25bdd005..0297bdd06ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulWhile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatefulWhile.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,9 +29,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -117,4 +120,37 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatefulWhile> {
+    /**
+     * A list of input tensors whose types are T.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * dtype in use.
+     */
+    public final DataType[] T;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The parallelIterations attribute
+     */
+    public final long parallelIterations;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulWhile(op), op, Arrays.asList("T", "output_shapes", "parallel_iterations"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      T = op.attributes().getAttrTypeList("T");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      parallelIterations = op.attributes().getAttrInt("parallel_iterations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessCase.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessCase.java
index 2241b1c8c5f..3b9da5431de 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessCase.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessCase.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,8 +29,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -131,4 +134,43 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatelessCase> {
+    /**
+     * The branch selector, an int32 Tensor.
+     */
+    public final Operand<TInt32> branchIndex;
+
+    /**
+     * A list of input tensors passed to the branch function.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * A list of input types.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * A list of output types.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessCase(op), op, Arrays.asList("Tin", "Tout", "output_shapes"));
+      int inputIndex = 0;
+      branchIndex = (Operand<TInt32>) op.input(inputIndex++);
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessIf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessIf.java
index 820c287e503..e4d4a60e693 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessIf.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessIf.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,9 +29,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -123,4 +126,59 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatelessIf> {
+    /**
+     * <pre>
+     *   A Tensor. If the tensor is a scalar of non-boolean type, the
+     *   scalar is converted to a boolean according to the
+     *   following rule: if the scalar is a numerical value, non-zero means
+     *   `True` and zero means False; if the scalar is a string, non-empty
+     *   means `True` and empty means `False`. If the tensor is not a scalar,
+     *   being empty means False and being non-empty means True.
+     *
+     *   This should only be used when the if then/else body functions do not
+     *   have stateful ops.
+     * </pre>
+     */
+    public final Operand<? extends TType> cond;
+
+    /**
+     * A list of input tensors.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * The Tcond attribute
+     */
+    public final DataType Tcond;
+
+    /**
+     * A list of input types.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * A list of output types.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessIf(op), op, Arrays.asList("Tcond", "Tin", "Tout", "output_shapes"));
+      int inputIndex = 0;
+      cond = (Operand<? extends TType>) op.input(inputIndex++);
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      Tcond = op.attributes().getAttrType("Tcond");
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessPartitionedCall.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessPartitionedCall.java
index 1563fa781d6..f819677d6e7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessPartitionedCall.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessPartitionedCall.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -111,4 +114,49 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatelessPartitionedCall> {
+    /**
+     * A list of input tensors.
+     */
+    public final Iterable<Operand<?>> args;
+
+    /**
+     * A list of input types.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * A list of output types.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    /**
+     * The configProto attribute
+     */
+    public final String configProto;
+
+    /**
+     * The executorType attribute
+     */
+    public final String executorType;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessPartitionedCall(op), op, Arrays.asList("Tin", "Tout", "config", "config_proto", "executor_type"));
+      int inputIndex = 0;
+      int argsLength = op.inputListLength("args");
+      args = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argsLength));
+      inputIndex += argsLength;
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      config = op.attributes().getAttrString("config");
+      configProto = op.attributes().getAttrString("config_proto");
+      executorType = op.attributes().getAttrString("executor_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessWhile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessWhile.java
index 94fc05214d6..da5e3146ec7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessWhile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StatelessWhile.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,9 +29,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -120,4 +123,37 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<StatelessWhile> {
+    /**
+     * A list of input tensors whose types are T.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * dtype in use.
+     */
+    public final DataType[] T;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The parallelIterations attribute
+     */
+    public final long parallelIterations;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessWhile(op), op, Arrays.asList("T", "output_shapes", "parallel_iterations"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      T = op.attributes().getAttrTypeList("T");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      parallelIterations = op.attributes().getAttrInt("parallel_iterations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java
index 045f9f840ec..861c19e863d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -101,7 +105,7 @@ private StopGradient(Operation operation) {
    * Factory method to create a class wrapping a new StopGradient operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code StopGradient} output and operands
    * @return a new instance of StopGradient
    */
@@ -127,4 +131,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<StopGradient<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new StopGradient<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java
index 60be840fc96..3eeabb0160b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -149,7 +153,7 @@ private StridedSlice(Operation operation) {
    * Factory method to create a class wrapping a new StridedSlice operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param begin {@code begin[k]} specifies the offset into the {@code k}th range specification.
    * The exact dimension this corresponds to will be determined by context.
    * Out-of-bounds values will be silently clamped. If the {@code k}th bit of
@@ -365,4 +369,101 @@ public Options shrinkAxisMask(Long shrinkAxisMask) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<StridedSlice<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * {@code begin[k]} specifies the offset into the {@code k}th range specification.
+     * The exact dimension this corresponds to will be determined by context.
+     * Out-of-bounds values will be silently clamped. If the {@code k}th bit of
+     * {@code begin_mask} then {@code begin[k]} is ignored and the full range of the
+     * appropriate dimension is used instead. Negative values causes indexing
+     * to start from the highest element e.g. If {@code foo==[1,2,3]} then {@code foo[-1]==3}.
+     */
+    public final Operand<U> begin;
+
+    /**
+     * {@code end[i]} is like {@code begin} with the exception that {@code end_mask} is
+     * used to determine full ranges.
+     */
+    public final Operand<U> end;
+
+    /**
+     * {@code strides[i]} specifies the increment in the {@code i}th specification
+     * after extracting a given element. Negative indices will reverse
+     * the original order. Out or range values are
+     * clamped to {@code [0,dim[i]) if slice[i]>0} or {@code [-1,dim[i]-1] if slice[i] < 0}
+     */
+    public final Operand<U> strides;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    /**
+     * a bitmask where a bit i being 1 means to ignore the begin
+     * value and instead use the largest interval possible. At runtime
+     * begin[i] will be replaced with `[0, n-1)` if `stride[i] > 0` or
+     * `[-1, n-1]` if `stride[i] < 0`
+     */
+    public final long beginMask;
+
+    /**
+     * analogous to `begin_mask`
+     */
+    public final long endMask;
+
+    /**
+     * a bitmask where bit `i` being 1 means the `i`th
+     * position is actually an ellipsis. One bit at most can be 1.
+     * If `ellipsis_mask == 0`, then an implicit ellipsis mask of `1 << (m+1)`
+     * is provided. This means that `foo[3:5] == foo[3:5, ...]`. An ellipsis
+     * implicitly creates as many range specifications as necessary to fully
+     * specify the sliced range for every dimension. For example for a 4-dimensional
+     * tensor `foo` the slice `foo[2, ..., 5:8]` implies `foo[2, :, :, 5:8]`.
+     */
+    public final long ellipsisMask;
+
+    /**
+     * a bitmask where bit `i` being 1 means the `i`th
+     * specification creates a new shape 1 dimension. For example
+     * `foo[:4, tf.newaxis, :2]` would produce a shape `(4, 1, 2)` tensor.
+     */
+    public final long newAxisMask;
+
+    /**
+     * a bitmask where bit `i` implies that the `i`th
+     * specification should shrink the dimensionality. begin and end
+     * must imply a slice of size 1 in the dimension. For example in
+     * python one might do `foo[:, 3, :]` which would result in
+     * `shrink_axis_mask` being 2.
+     */
+    public final long shrinkAxisMask;
+
+    public Inputs(GraphOperation op) {
+      super(new StridedSlice<>(op), op, Arrays.asList("T", "Index", "begin_mask", "end_mask", "ellipsis_mask", "new_axis_mask", "shrink_axis_mask"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      begin = (Operand<U>) op.input(inputIndex++);
+      end = (Operand<U>) op.input(inputIndex++);
+      strides = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Index = op.attributes().getAttrType("Index");
+      beginMask = op.attributes().getAttrInt("begin_mask");
+      endMask = op.attributes().getAttrInt("end_mask");
+      ellipsisMask = op.attributes().getAttrInt("ellipsis_mask");
+      newAxisMask = op.attributes().getAttrInt("new_axis_mask");
+      shrinkAxisMask = op.attributes().getAttrInt("shrink_axis_mask");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java
index dc64084c4d5..644018b6e74 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -57,11 +61,11 @@ private StridedSliceAssign(Operation operation) {
    * Factory method to create a class wrapping a new StridedSliceAssign operation.
    *
    * @param scope current scope
-   * @param ref the ref value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param value the value value
+   * @param ref The ref value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param value The value value
    * @param options carries optional attribute values
    * @param <T> data type for {@code StridedSliceAssign} output and operands
    * @param <U> data type for {@code StridedSliceAssign} output and operands
@@ -237,4 +241,83 @@ public Options shrinkAxisMask(Long shrinkAxisMask) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<StridedSliceAssign<T>> {
+    /**
+     * The ref input
+     */
+    public final Operand<T> ref;
+
+    /**
+     * The begin input
+     */
+    public final Operand<U> begin;
+
+    /**
+     * The end input
+     */
+    public final Operand<U> end;
+
+    /**
+     * The strides input
+     */
+    public final Operand<U> strides;
+
+    /**
+     * The value input
+     */
+    public final Operand<T> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    /**
+     * The beginMask attribute
+     */
+    public final long beginMask;
+
+    /**
+     * The endMask attribute
+     */
+    public final long endMask;
+
+    /**
+     * The ellipsisMask attribute
+     */
+    public final long ellipsisMask;
+
+    /**
+     * The newAxisMask attribute
+     */
+    public final long newAxisMask;
+
+    /**
+     * The shrinkAxisMask attribute
+     */
+    public final long shrinkAxisMask;
+
+    public Inputs(GraphOperation op) {
+      super(new StridedSliceAssign<>(op), op, Arrays.asList("T", "Index", "begin_mask", "end_mask", "ellipsis_mask", "new_axis_mask", "shrink_axis_mask"));
+      int inputIndex = 0;
+      ref = (Operand<T>) op.input(inputIndex++);
+      begin = (Operand<U>) op.input(inputIndex++);
+      end = (Operand<U>) op.input(inputIndex++);
+      strides = (Operand<U>) op.input(inputIndex++);
+      value = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Index = op.attributes().getAttrType("Index");
+      beginMask = op.attributes().getAttrInt("begin_mask");
+      endMask = op.attributes().getAttrInt("end_mask");
+      ellipsisMask = op.attributes().getAttrInt("ellipsis_mask");
+      newAxisMask = op.attributes().getAttrInt("new_axis_mask");
+      shrinkAxisMask = op.attributes().getAttrInt("shrink_axis_mask");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java
index 123691b24c9..07947acab0a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -59,11 +63,11 @@ private StridedSliceGrad(Operation operation) {
    * Factory method to create a class wrapping a new StridedSliceGrad operation.
    *
    * @param scope current scope
-   * @param shape the shape value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param dy the dy value
+   * @param shape The shape value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param dy The dy value
    * @param options carries optional attribute values
    * @param <U> data type for {@code StridedSliceGrad} output and operands
    * @param <T> data type for {@code StridedSliceGrad} output and operands
@@ -239,4 +243,83 @@ public Options shrinkAxisMask(Long shrinkAxisMask) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TType> extends RawOpInputs<StridedSliceGrad<U>> {
+    /**
+     * The shape input
+     */
+    public final Operand<T> shape;
+
+    /**
+     * The begin input
+     */
+    public final Operand<T> begin;
+
+    /**
+     * The end input
+     */
+    public final Operand<T> end;
+
+    /**
+     * The strides input
+     */
+    public final Operand<T> strides;
+
+    /**
+     * The dy input
+     */
+    public final Operand<U> dy;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    /**
+     * The beginMask attribute
+     */
+    public final long beginMask;
+
+    /**
+     * The endMask attribute
+     */
+    public final long endMask;
+
+    /**
+     * The ellipsisMask attribute
+     */
+    public final long ellipsisMask;
+
+    /**
+     * The newAxisMask attribute
+     */
+    public final long newAxisMask;
+
+    /**
+     * The shrinkAxisMask attribute
+     */
+    public final long shrinkAxisMask;
+
+    public Inputs(GraphOperation op) {
+      super(new StridedSliceGrad<>(op), op, Arrays.asList("T", "Index", "begin_mask", "end_mask", "ellipsis_mask", "new_axis_mask", "shrink_axis_mask"));
+      int inputIndex = 0;
+      shape = (Operand<T>) op.input(inputIndex++);
+      begin = (Operand<T>) op.input(inputIndex++);
+      end = (Operand<T>) op.input(inputIndex++);
+      strides = (Operand<T>) op.input(inputIndex++);
+      dy = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Index = op.attributes().getAttrType("Index");
+      beginMask = op.attributes().getAttrInt("begin_mask");
+      endMask = op.attributes().getAttrInt("end_mask");
+      ellipsisMask = op.attributes().getAttrInt("ellipsis_mask");
+      newAxisMask = op.attributes().getAttrInt("new_axis_mask");
+      shrinkAxisMask = op.attributes().getAttrInt("shrink_axis_mask");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java
index ec0dfd9f6e9..5df5a25d98e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -125,4 +129,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sum<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Sum<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java
index a65d91c3038..00f21eb34bc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -91,4 +95,29 @@ public Output<T> outputFalse() {
   public Output<T> outputTrue() {
     return outputTrue;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SwitchCond<T>> {
+    /**
+     * The tensor to be forwarded to the appropriate output.
+     */
+    public final Operand<T> data;
+
+    /**
+     * A scalar that specifies which output port will receive data.
+     */
+    public final Operand<TBool> pred;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SwitchCond<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      pred = (Operand<TBool>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java
index 93baf455fa5..a16282ea459 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -134,4 +138,30 @@ public Options varName(String varName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TemporaryVariable<?>> {
+    /**
+     * The shape of the variable tensor.
+     */
+    public final Shape shape;
+
+    /**
+     * The type of elements in the variable tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * Overrides the name used for the temporary variable resource. Default
+     * value is the name of the 'TemporaryVariable' op (which is guaranteed unique).
+     */
+    public final String varName;
+
+    public Inputs(GraphOperation op) {
+      super(new TemporaryVariable<>(op), op, Arrays.asList("shape", "dtype", "var_name"));
+      int inputIndex = 0;
+      shape = op.attributes().getAttrShape("shape");
+      dtype = op.attributes().getAttrType("dtype");
+      varName = op.attributes().getAttrString("var_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java
index 39979757083..34ca0e49eab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
@@ -258,4 +262,65 @@ public Options tensorArrayName(String tensorArrayName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TensorArray> {
+    /**
+     * The size of the array.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The type of the elements on the tensor_array.
+     */
+    public final DataType dtype;
+
+    /**
+     * The expected shape of an element, if known. Used to
+     * validate the shapes of TensorArray elements. If this shape is not
+     * fully specified, gathering zero-size TensorArrays is an error.
+     */
+    public final Shape elementShape;
+
+    /**
+     * A boolean that determines whether writes to the TensorArray
+     * are allowed to grow the size.  By default, this is not allowed.
+     */
+    public final boolean dynamicSize;
+
+    /**
+     * If true (default), Tensors in the TensorArray are cleared
+     * after being read.  This disables multiple read semantics but allows early
+     * release of memory.
+     */
+    public final boolean clearAfterRead;
+
+    /**
+     * If true (default is false), then all
+     * elements in the TensorArray will be expected to have identical shapes.
+     * This allows certain behaviors, like dynamically checking for
+     * consistent shapes on write, and being able to fill in properly
+     * shaped zero tensors on stack -- even if the element_shape attribute
+     * is not fully defined.
+     */
+    public final boolean identicalElementShapes;
+
+    /**
+     * Overrides the name used for the temporary tensor_array
+     * resource. Default value is the name of the 'TensorArray' op (which
+     * is guaranteed unique).
+     */
+    public final String tensorArrayName;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArray(op), op, Arrays.asList("dtype", "element_shape", "dynamic_size", "clear_after_read", "identical_element_shapes", "tensor_array_name"));
+      int inputIndex = 0;
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      elementShape = op.attributes().getAttrShape("element_shape");
+      dynamicSize = op.attributes().getAttrBool("dynamic_size");
+      clearAfterRead = op.attributes().getAttrBool("clear_after_read");
+      identicalElementShapes = op.attributes().getAttrBool("identical_element_shapes");
+      tensorArrayName = op.attributes().getAttrString("tensor_array_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayClose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayClose.java
index 37ac21f17af..df1db0abdba 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayClose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayClose.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -57,4 +60,17 @@ public static TensorArrayClose create(Scope scope, Operand<? extends TType> hand
     opBuilder.addInput(handle.asOutput());
     return new TensorArrayClose(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayClose> {
+    /**
+     * The handle to a TensorArray (output of TensorArray or TensorArrayGrad).
+     */
+    public final Operand<? extends TType> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayClose(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java
index 6c4cb0582ff..decac97c386 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -149,4 +153,38 @@ public Options elementShapeExcept0(Shape elementShapeExcept0) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayConcat<?>> {
+    /**
+     * The handle to a TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The type of the elem that is returned.
+     */
+    public final DataType dtype;
+
+    /**
+     * The expected shape of an element, if known,
+     * excluding the first dimension. Used to validate the shapes of
+     * TensorArray elements. If this shape is not fully specified, concatenating
+     * zero-size TensorArrays is an error.
+     */
+    public final Shape elementShapeExcept0;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayConcat<>(op), op, Arrays.asList("dtype", "element_shape_except0"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      elementShapeExcept0 = op.attributes().getAttrShape("element_shape_except0");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java
index 9560693fd21..e21dd4eea21 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
@@ -134,4 +138,43 @@ public Options elementShape(Shape elementShape) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayGather<?>> {
+    /**
+     * The handle to a TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The locations in the TensorArray from which to read tensor elements.
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The type of the elem that is returned.
+     */
+    public final DataType dtype;
+
+    /**
+     * The expected shape of an element, if known. Used to
+     * validate the shapes of TensorArray elements. If this shape is not
+     * fully specified, gathering zero-size TensorArrays is an error.
+     */
+    public final Shape elementShape;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayGather<>(op), op, Arrays.asList("dtype", "element_shape"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      elementShape = op.attributes().getAttrShape("element_shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGrad.java
index 0047982655f..2b42e5dfe78 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGrad.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -117,4 +120,30 @@ public Output<? extends TType> gradHandle() {
   public Output<TFloat32> flowOut() {
     return flowOut;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayGrad> {
+    /**
+     * The handle to the forward TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The gradient source string, used to decide which gradient TensorArray
+     * to return.
+     */
+    public final String source;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayGrad(op), op, Arrays.asList("source"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      source = op.attributes().getAttrString("source");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGradWithShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGradWithShape.java
index c4da5d01248..163dec99fc4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGradWithShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGradWithShape.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -98,4 +101,38 @@ public Output<? extends TType> gradHandle() {
   public Output<TFloat32> flowOut() {
     return flowOut;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayGradWithShape> {
+    /**
+     * The handle to the forward TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * An int32 vector representing a shape. Elements in the gradient accumulator will
+     * have shape which is this shape_to_prepend value concatenated with shape of the
+     * elements in the TensorArray corresponding to the input handle.
+     */
+    public final Operand<TInt32> shapeToPrepend;
+
+    /**
+     * The gradient source string, used to decide which gradient TensorArray
+     * to return.
+     */
+    public final String source;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayGradWithShape(op), op, Arrays.asList("source"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      shapeToPrepend = (Operand<TInt32>) op.input(inputIndex++);
+      source = op.attributes().getAttrString("source");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java
index f51f2f30a17..41fe676090e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -55,9 +59,9 @@ private TensorArrayPack(Operation operation) {
    * Factory method to create a class wrapping a new TensorArrayPack operation.
    *
    * @param scope current scope
-   * @param handle the handle value
-   * @param flowIn the flowIn value
-   * @param dtype the value of the dtype property
+   * @param handle The handle value
+   * @param flowIn The flowIn value
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code TensorArrayPack} output and operands
    * @return a new instance of TensorArrayPack
@@ -125,4 +129,35 @@ public Options elementShape(Shape elementShape) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayPack<?>> {
+    /**
+     * The handle input
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * The flowIn input
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    /**
+     * The elementShape attribute
+     */
+    public final Shape elementShape;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayPack<>(op), op, Arrays.asList("dtype", "element_shape"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      elementShape = op.attributes().getAttrShape("element_shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java
index a7f254c8395..e34c494fa0d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
@@ -55,7 +59,7 @@ private TensorArrayRead(Operation operation) {
    *
    * @param scope current scope
    * @param handle The handle to a TensorArray.
-   * @param index the index value
+   * @param index The index value
    * @param flowIn A float scalar that enforces proper chaining of operations.
    * @param dtype The type of the elem that is returned.
    * @param <T> data type for {@code TensorArrayReadV3} output and operands
@@ -88,4 +92,35 @@ public Output<T> value() {
   public Output<T> asOutput() {
     return value;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayRead<?>> {
+    /**
+     * The handle to a TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The index input
+     */
+    public final Operand<TInt32> index;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The type of the elem that is returned.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayRead<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      index = (Operand<TInt32>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayScatter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayScatter.java
index 2fd32332990..af15fe9187e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayScatter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayScatter.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
@@ -84,4 +88,41 @@ public Output<TFloat32> flowOut() {
   public Output<TFloat32> asOutput() {
     return flowOut;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayScatter> {
+    /**
+     * The handle to a TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The locations at which to write the tensor elements.
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The concatenated tensor to write to the TensorArray.
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayScatter(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySize.java
index b1c0847805e..6bfc5e291b1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -79,4 +82,23 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArraySize> {
+    /**
+     * The handle to a TensorArray (output of TensorArray or TensorArrayGrad).
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArraySize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySplit.java
index 69fa801b51c..3ce1424ae9c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySplit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArraySplit.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -93,4 +97,42 @@ public Output<TFloat32> flowOut() {
   public Output<TFloat32> asOutput() {
     return flowOut;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArraySplit> {
+    /**
+     * The handle to a TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The concatenated tensor to write to the TensorArray.
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * The vector of lengths, how to split the rows of value into the
+     * TensorArray.
+     */
+    public final Operand<TInt64> lengths;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArraySplit(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      lengths = (Operand<TInt64>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayUnpack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayUnpack.java
index 21d9122155f..ce65c26492a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayUnpack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayUnpack.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -51,9 +55,9 @@ private TensorArrayUnpack(Operation operation) {
    * Factory method to create a class wrapping a new TensorArrayUnpack operation.
    *
    * @param scope current scope
-   * @param handle the handle value
-   * @param value the value value
-   * @param flowIn the flowIn value
+   * @param handle The handle value
+   * @param value The value value
+   * @param flowIn The flowIn value
    * @return a new instance of TensorArrayUnpack
    */
   @Endpoint(
@@ -81,4 +85,35 @@ public Output<TFloat32> flowOut() {
   public Output<TFloat32> asOutput() {
     return flowOut;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayUnpack> {
+    /**
+     * The handle input
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * The value input
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * The flowIn input
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayUnpack(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayWrite.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayWrite.java
index cb344c15cf2..e44e81a294d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayWrite.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayWrite.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
@@ -83,4 +87,41 @@ public Output<TFloat32> flowOut() {
   public Output<TFloat32> asOutput() {
     return flowOut;
   }
+
+  public static class Inputs extends RawOpInputs<TensorArrayWrite> {
+    /**
+     * The handle to a TensorArray.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The position to write to inside the TensorArray.
+     */
+    public final Operand<TInt32> index;
+
+    /**
+     * The tensor to write to the TensorArray.
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * A float scalar that enforces proper chaining of operations.
+     */
+    public final Operand<TFloat32> flowIn;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorArrayWrite(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      index = (Operand<TInt32>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      flowIn = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java
index c30cfe610c4..7b77b4870be 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -67,10 +71,10 @@ private TensorListConcat(Operation operation) {
    * Factory method to create a class wrapping a new TensorListConcatV2 operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param elementShape the elementShape value
-   * @param leadingDims the leadingDims value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param elementShape The elementShape value
+   * @param leadingDims The leadingDims value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <U> data type for {@code TensorListConcatV2} output and operands
    * @return a new instance of TensorListConcat
    */
@@ -105,4 +109,41 @@ public Output<U> tensor() {
   public Output<TInt64> lengths() {
     return lengths;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListConcat<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<? extends TNumber> elementShape;
+
+    /**
+     * The leadingDims input
+     */
+    public final Operand<TInt64> leadingDims;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    /**
+     * The shapeType attribute
+     */
+    public final DataType shapeType;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListConcat<>(op), op, Arrays.asList("element_dtype", "shape_type"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      elementShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      leadingDims = (Operand<TInt64>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+      shapeType = op.attributes().getAttrType("shape_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java
index 3e2759d282f..1d1fc91e00d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,9 +55,9 @@ private TensorListConcatLists(Operation operation) {
    * Factory method to create a class wrapping a new TensorListConcatLists operation.
    *
    * @param scope current scope
-   * @param inputA the inputA value
-   * @param inputB the inputB value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputA The inputA value
+   * @param inputB The inputB value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListConcatLists} output and operands
    * @return a new instance of TensorListConcatLists
    */
@@ -83,4 +87,29 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListConcatLists> {
+    /**
+     * The inputA input
+     */
+    public final Operand<? extends TType> inputA;
+
+    /**
+     * The inputB input
+     */
+    public final Operand<? extends TType> inputB;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListConcatLists(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputA = (Operand<? extends TType>) op.input(inputIndex++);
+      inputB = (Operand<? extends TType>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java
index 578a7978697..dbc4eb91ec5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -55,8 +59,8 @@ private TensorListElementShape(Operation operation) {
    * Factory method to create a class wrapping a new TensorListElementShape operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param shapeType the value of the shapeType property
+   * @param inputHandle The inputHandle value
+   * @param shapeType The value of the shapeType attribute
    * @param <T> data type for {@code TensorListElementShape} output and operands
    * @return a new instance of TensorListElementShape
    */
@@ -84,4 +88,23 @@ public Output<T> elementShape() {
   public Output<T> asOutput() {
     return elementShape;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListElementShape<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The shapeType attribute
+     */
+    public final DataType shapeType;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListElementShape<>(op), op, Arrays.asList("shape_type"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      shapeType = op.attributes().getAttrType("shape_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListFromTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListFromTensor.java
index 76f3a4c3c51..f193b8c7f13 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListFromTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListFromTensor.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -54,8 +58,8 @@ private TensorListFromTensor(Operation operation) {
    * Factory method to create a class wrapping a new TensorListFromTensor operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
-   * @param elementShape the elementShape value
+   * @param tensor The tensor value
+   * @param elementShape The elementShape value
    * @return a new instance of TensorListFromTensor
    */
   @Endpoint(
@@ -83,4 +87,35 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListFromTensor> {
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<? extends TNumber> elementShape;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    /**
+     * The shapeType attribute
+     */
+    public final DataType shapeType;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListFromTensor(op), op, Arrays.asList("element_dtype", "shape_type"));
+      int inputIndex = 0;
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      elementShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+      shapeType = op.attributes().getAttrType("shape_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java
index 41848040b03..d4e08702d4d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -58,10 +62,10 @@ private TensorListGather(Operation operation) {
    * Factory method to create a class wrapping a new TensorListGather operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param indices the indices value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param indices The indices value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListGather} output and operands
    * @return a new instance of TensorListGather
    */
@@ -92,4 +96,35 @@ public Output<T> values() {
   public Output<T> asOutput() {
     return values;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListGather<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<TInt32> elementShape;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListGather<>(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      elementShape = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java
index 61fdb9b41b6..c1841854a1e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -53,10 +57,10 @@ private TensorListGetItem(Operation operation) {
    * Factory method to create a class wrapping a new TensorListGetItem operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param index the index value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param index The index value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListGetItem} output and operands
    * @return a new instance of TensorListGetItem
    */
@@ -87,4 +91,35 @@ public Output<T> item() {
   public Output<T> asOutput() {
     return item;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListGetItem<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The index input
+     */
+    public final Operand<TInt32> index;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<TInt32> elementShape;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListGetItem<>(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      index = (Operand<TInt32>) op.input(inputIndex++);
+      elementShape = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListLength.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListLength.java
index 9fd22ca4a11..d3b70223fe1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListLength.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListLength.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private TensorListLength(Operation operation) {
    * Factory method to create a class wrapping a new TensorListLength operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of TensorListLength
    */
   @Endpoint(
@@ -77,4 +80,17 @@ public Output<TInt32> length() {
   public Output<TInt32> asOutput() {
     return length;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListLength> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListLength(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java
index 09b6bf41be9..7656c8f71b8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -62,9 +66,9 @@ private TensorListPopBack(Operation operation) {
    * Factory method to create a class wrapping a new TensorListPopBack operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <T> data type for {@code TensorListPopBack} output and operands
    * @return a new instance of TensorListPopBack
    */
@@ -97,4 +101,29 @@ public Output<? extends TType> outputHandle() {
   public Output<T> tensor() {
     return tensor;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListPopBack<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<TInt32> elementShape;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListPopBack<>(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      elementShape = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBack.java
index e347e64313d..d5d4b471c56 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBack.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private TensorListPushBack(Operation operation) {
    * Factory method to create a class wrapping a new TensorListPushBack operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param tensor the tensor value
+   * @param inputHandle The inputHandle value
+   * @param tensor The tensor value
    * @return a new instance of TensorListPushBack
    */
   @Endpoint(
@@ -84,4 +88,29 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListPushBack> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListPushBack(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBackBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBackBatch.java
index a48e5c5f2d4..694cc698ca3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBackBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPushBackBatch.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -50,8 +54,8 @@ private TensorListPushBackBatch(Operation operation) {
    * Factory method to create a class wrapping a new TensorListPushBackBatch operation.
    *
    * @param scope current scope
-   * @param inputHandles the inputHandles value
-   * @param tensor the tensor value
+   * @param inputHandles The inputHandles value
+   * @param tensor The tensor value
    * @return a new instance of TensorListPushBackBatch
    */
   @Endpoint(
@@ -79,4 +83,29 @@ public Output<? extends TType> outputHandles() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandles;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListPushBackBatch> {
+    /**
+     * The inputHandles input
+     */
+    public final Operand<? extends TType> inputHandles;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListPushBackBatch(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputHandles = (Operand<? extends TType>) op.input(inputIndex++);
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java
index 923592b48be..b539e5114a7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -57,9 +61,9 @@ private TensorListReserve(Operation operation) {
    * Factory method to create a class wrapping a new TensorListReserve operation.
    *
    * @param scope current scope
-   * @param elementShape the elementShape value
-   * @param numElements the numElements value
-   * @param elementDtype the value of the elementDtype property
+   * @param elementShape The elementShape value
+   * @param numElements The numElements value
+   * @param elementDtype The value of the elementDtype attribute
    * @param <U> data type for {@code TensorListReserve} output and operands
    * @return a new instance of TensorListReserve
    */
@@ -89,4 +93,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListReserve> {
+    /**
+     * The elementShape input
+     */
+    public final Operand<? extends TNumber> elementShape;
+
+    /**
+     * The numElements input
+     */
+    public final Operand<TInt32> numElements;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    /**
+     * The shapeType attribute
+     */
+    public final DataType shapeType;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListReserve(op), op, Arrays.asList("element_dtype", "shape_type"));
+      int inputIndex = 0;
+      elementShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numElements = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+      shapeType = op.attributes().getAttrType("shape_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListResize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListResize.java
index 5642bc4ba3a..445f0177118 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListResize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListResize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -53,8 +56,8 @@ private TensorListResize(Operation operation) {
    * Factory method to create a class wrapping a new TensorListResize operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param sizeOutput the sizeOutput value
+   * @param inputHandle The inputHandle value
+   * @param sizeOutput The sizeOutput value
    * @return a new instance of TensorListResize
    */
   @Endpoint(
@@ -82,4 +85,23 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListResize> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The sizeOutput input
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListResize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatter.java
index efc6c1b57e6..c321d7f227a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatter.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -62,10 +66,10 @@ private TensorListScatter(Operation operation) {
    * Factory method to create a class wrapping a new TensorListScatterV2 operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
-   * @param indices the indices value
-   * @param elementShape the elementShape value
-   * @param numElements the numElements value
+   * @param tensor The tensor value
+   * @param indices The indices value
+   * @param elementShape The elementShape value
+   * @param numElements The numElements value
    * @return a new instance of TensorListScatter
    */
   @Endpoint(
@@ -96,4 +100,47 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListScatter> {
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<? extends TNumber> elementShape;
+
+    /**
+     * The numElements input
+     */
+    public final Operand<TInt32> numElements;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    /**
+     * The shapeType attribute
+     */
+    public final DataType shapeType;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListScatter(op), op, Arrays.asList("element_dtype", "shape_type"));
+      int inputIndex = 0;
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      elementShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numElements = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+      shapeType = op.attributes().getAttrType("shape_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatterIntoExistingList.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatterIntoExistingList.java
index 6365d722f80..15c38200e5d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatterIntoExistingList.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListScatterIntoExistingList.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -57,9 +61,9 @@ private TensorListScatterIntoExistingList(Operation operation) {
    * Factory method to create a class wrapping a new TensorListScatterIntoExistingList operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param tensor the tensor value
-   * @param indices the indices value
+   * @param inputHandle The inputHandle value
+   * @param tensor The tensor value
+   * @param indices The indices value
    * @return a new instance of TensorListScatterIntoExistingList
    */
   @Endpoint(
@@ -89,4 +93,35 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListScatterIntoExistingList> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The indices input
+     */
+    public final Operand<TInt32> indices;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListScatterIntoExistingList(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSetItem.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSetItem.java
index 6974ee0a1a1..d8010760cdb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSetItem.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSetItem.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -51,9 +55,9 @@ private TensorListSetItem(Operation operation) {
    * Factory method to create a class wrapping a new TensorListSetItem operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param index the index value
-   * @param item the item value
+   * @param inputHandle The inputHandle value
+   * @param index The index value
+   * @param item The item value
    * @return a new instance of TensorListSetItem
    */
   @Endpoint(
@@ -82,4 +86,35 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListSetItem> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The index input
+     */
+    public final Operand<TInt32> index;
+
+    /**
+     * The item input
+     */
+    public final Operand<? extends TType> item;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListSetItem(op), op, Arrays.asList("element_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      index = (Operand<TInt32>) op.input(inputIndex++);
+      item = (Operand<? extends TType>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSplit.java
index 18987c1c9ef..27121f34aff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSplit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListSplit.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -58,9 +62,9 @@ private TensorListSplit(Operation operation) {
    * Factory method to create a class wrapping a new TensorListSplit operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
-   * @param elementShape the elementShape value
-   * @param lengths the lengths value
+   * @param tensor The tensor value
+   * @param elementShape The elementShape value
+   * @param lengths The lengths value
    * @return a new instance of TensorListSplit
    */
   @Endpoint(
@@ -89,4 +93,41 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorListSplit> {
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<? extends TNumber> elementShape;
+
+    /**
+     * The lengths input
+     */
+    public final Operand<TInt64> lengths;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    /**
+     * The shapeType attribute
+     */
+    public final DataType shapeType;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListSplit(op), op, Arrays.asList("element_dtype", "shape_type"));
+      int inputIndex = 0;
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      elementShape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      lengths = (Operand<TInt64>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+      shapeType = op.attributes().getAttrType("shape_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java
index 28c33663b69..1f0a2364c20 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -57,9 +61,9 @@ private TensorListStack(Operation operation) {
    * Factory method to create a class wrapping a new TensorListStack operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param elementShape the elementShape value
-   * @param elementDtype the value of the elementDtype property
+   * @param inputHandle The inputHandle value
+   * @param elementShape The elementShape value
+   * @param elementDtype The value of the elementDtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code TensorListStack} output and operands
    * @return a new instance of TensorListStack
@@ -128,4 +132,35 @@ public Options numElements(Long numElements) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TensorListStack<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The elementShape input
+     */
+    public final Operand<TInt32> elementShape;
+
+    /**
+     * The elementDtype attribute
+     */
+    public final DataType elementDtype;
+
+    /**
+     * The numElements attribute
+     */
+    public final long numElements;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorListStack<>(op), op, Arrays.asList("element_dtype", "num_elements"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      elementShape = (Operand<TInt32>) op.input(inputIndex++);
+      elementDtype = op.attributes().getAttrType("element_dtype");
+      numElements = op.attributes().getAttrInt("num_elements");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapErase.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapErase.java
index a714154cb25..93d15ad6fcf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapErase.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapErase.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,9 +58,9 @@ private TensorMapErase(Operation operation) {
    * Factory method to create a class wrapping a new TensorMapErase operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param key the key value
-   * @param valueDtype the value of the valueDtype property
+   * @param inputHandle The inputHandle value
+   * @param key The key value
+   * @param valueDtype The value of the valueDtype attribute
    * @param <U> data type for {@code TensorMapErase} output and operands
    * @return a new instance of TensorMapErase
    */
@@ -86,4 +90,35 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorMapErase> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The key input
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * The keyDtype attribute
+     */
+    public final DataType keyDtype;
+
+    /**
+     * The valueDtype attribute
+     */
+    public final DataType valueDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorMapErase(op), op, Arrays.asList("key_dtype", "value_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      keyDtype = op.attributes().getAttrType("key_dtype");
+      valueDtype = op.attributes().getAttrType("value_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapHasKey.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapHasKey.java
index 99bbff077b5..1d4659c3e24 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapHasKey.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapHasKey.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -53,8 +57,8 @@ private TensorMapHasKey(Operation operation) {
    * Factory method to create a class wrapping a new TensorMapHasKey operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param key the key value
+   * @param inputHandle The inputHandle value
+   * @param key The key value
    * @return a new instance of TensorMapHasKey
    */
   @Endpoint(
@@ -81,4 +85,29 @@ public Output<TBool> hasKey() {
   public Output<TBool> asOutput() {
     return hasKey;
   }
+
+  public static class Inputs extends RawOpInputs<TensorMapHasKey> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The key input
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * The keyDtype attribute
+     */
+    public final DataType keyDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorMapHasKey(op), op, Arrays.asList("key_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      keyDtype = op.attributes().getAttrType("key_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapInsert.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapInsert.java
index c51ea51b187..7c4c494fe22 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapInsert.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapInsert.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,9 +58,9 @@ private TensorMapInsert(Operation operation) {
    * Factory method to create a class wrapping a new TensorMapInsert operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param key the key value
-   * @param value the value value
+   * @param inputHandle The inputHandle value
+   * @param key The key value
+   * @param value The value value
    * @return a new instance of TensorMapInsert
    */
   @Endpoint(
@@ -85,4 +89,41 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorMapInsert> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The key input
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * The value input
+     */
+    public final Operand<? extends TType> value;
+
+    /**
+     * The keyDtype attribute
+     */
+    public final DataType keyDtype;
+
+    /**
+     * The valueDtype attribute
+     */
+    public final DataType valueDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorMapInsert(op), op, Arrays.asList("key_dtype", "value_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      value = (Operand<? extends TType>) op.input(inputIndex++);
+      keyDtype = op.attributes().getAttrType("key_dtype");
+      valueDtype = op.attributes().getAttrType("value_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java
index 74455fd3cba..203fd5ea752 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private TensorMapLookup(Operation operation) {
    * Factory method to create a class wrapping a new TensorMapLookup operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param key the key value
-   * @param valueDtype the value of the valueDtype property
+   * @param inputHandle The inputHandle value
+   * @param key The key value
+   * @param valueDtype The value of the valueDtype attribute
    * @param <U> data type for {@code TensorMapLookup} output and operands
    * @return a new instance of TensorMapLookup
    */
@@ -86,4 +90,35 @@ public Output<U> value() {
   public Output<U> asOutput() {
     return value;
   }
+
+  public static class Inputs extends RawOpInputs<TensorMapLookup<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The key input
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * The keyDtype attribute
+     */
+    public final DataType keyDtype;
+
+    /**
+     * The valueDtype attribute
+     */
+    public final DataType valueDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorMapLookup<>(op), op, Arrays.asList("key_dtype", "value_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      keyDtype = op.attributes().getAttrType("key_dtype");
+      valueDtype = op.attributes().getAttrType("value_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapSize.java
index aac7031a7ec..8efc6ef987b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapSize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private TensorMapSize(Operation operation) {
    * Factory method to create a class wrapping a new TensorMapSize operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of TensorMapSize
    */
   @Endpoint(
@@ -77,4 +80,17 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<TensorMapSize> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorMapSize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java
index 968e251c9ec..3badf5126d8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,8 +58,8 @@ private TensorMapStackKeys(Operation operation) {
    * Factory method to create a class wrapping a new TensorMapStackKeys operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
-   * @param keyDtype the value of the keyDtype property
+   * @param inputHandle The inputHandle value
+   * @param keyDtype The value of the keyDtype attribute
    * @param <T> data type for {@code TensorMapStackKeys} output and operands
    * @return a new instance of TensorMapStackKeys
    */
@@ -83,4 +87,23 @@ public Output<T> keys() {
   public Output<T> asOutput() {
     return keys;
   }
+
+  public static class Inputs extends RawOpInputs<TensorMapStackKeys<?>> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    /**
+     * The keyDtype attribute
+     */
+    public final DataType keyDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorMapStackKeys<>(op), op, Arrays.asList("key_dtype"));
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      keyDtype = op.attributes().getAttrType("key_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java
index d3ab1b40ef3..2e676d0c7f2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -139,4 +143,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TensorScatterNdAdd<T>> {
+    /**
+     * Tensor to copy/update.
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * Index tensor.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Updates to scatter into output.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorScatterNdAdd<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java
index 19e3b4e8a53..8693ee3efd1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -83,4 +87,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TensorScatterNdMax<T>> {
+    /**
+     * Tensor to update.
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * Index tensor.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Updates to scatter into output.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorScatterNdMax<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java
index d8c54e576d1..6826e3c035d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -83,4 +87,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TensorScatterNdMin<T>> {
+    /**
+     * Tensor to update.
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * Index tensor.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Updates to scatter into output.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorScatterNdMin<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java
index 0cf16e8e677..a03f78e1f59 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -138,4 +142,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TensorScatterNdSub<T>> {
+    /**
+     * Tensor to copy/update.
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * Index tensor.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Updates to scatter into output.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorScatterNdSub<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java
index 0ed584af1b8..3cfec508b4b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -113,4 +117,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TensorScatterNdUpdate<T>> {
+    /**
+     * Tensor to copy/update.
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * Index tensor.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Updates to scatter into output.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorScatterNdUpdate<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java
index 58d071b28c9..f2a68cb155a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -57,11 +61,11 @@ private TensorStridedSliceUpdate(Operation operation) {
    * Factory method to create a class wrapping a new TensorStridedSliceUpdate operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param begin the begin value
-   * @param end the end value
-   * @param strides the strides value
-   * @param value the value value
+   * @param input The input value
+   * @param begin The begin value
+   * @param end The end value
+   * @param strides The strides value
+   * @param value The value value
    * @param options carries optional attribute values
    * @param <T> data type for {@code TensorStridedSliceUpdate} output and operands
    * @param <U> data type for {@code TensorStridedSliceUpdate} output and operands
@@ -237,4 +241,83 @@ public Options shrinkAxisMask(Long shrinkAxisMask) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<TensorStridedSliceUpdate<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The begin input
+     */
+    public final Operand<U> begin;
+
+    /**
+     * The end input
+     */
+    public final Operand<U> end;
+
+    /**
+     * The strides input
+     */
+    public final Operand<U> strides;
+
+    /**
+     * The value input
+     */
+    public final Operand<T> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    /**
+     * The beginMask attribute
+     */
+    public final long beginMask;
+
+    /**
+     * The endMask attribute
+     */
+    public final long endMask;
+
+    /**
+     * The ellipsisMask attribute
+     */
+    public final long ellipsisMask;
+
+    /**
+     * The newAxisMask attribute
+     */
+    public final long newAxisMask;
+
+    /**
+     * The shrinkAxisMask attribute
+     */
+    public final long shrinkAxisMask;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorStridedSliceUpdate<>(op), op, Arrays.asList("T", "Index", "begin_mask", "end_mask", "ellipsis_mask", "new_axis_mask", "shrink_axis_mask"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      begin = (Operand<U>) op.input(inputIndex++);
+      end = (Operand<U>) op.input(inputIndex++);
+      strides = (Operand<U>) op.input(inputIndex++);
+      value = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Index = op.attributes().getAttrType("Index");
+      beginMask = op.attributes().getAttrInt("begin_mask");
+      endMask = op.attributes().getAttrInt("end_mask");
+      ellipsisMask = op.attributes().getAttrInt("ellipsis_mask");
+      newAxisMask = op.attributes().getAttrInt("new_axis_mask");
+      shrinkAxisMask = op.attributes().getAttrInt("shrink_axis_mask");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java
index a417dea0725..4dbd1ef3a64 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -112,4 +116,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Tile<T>> {
+    /**
+     * 1-D or higher.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 1-D. Length must be the same as the number of dimensions in {@code input}
+     */
+    public final Operand<? extends TNumber> multiples;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tmultiples attribute
+     */
+    public final DataType Tmultiples;
+
+    public Inputs(GraphOperation op) {
+      super(new Tile<>(op), op, Arrays.asList("T", "Tmultiples"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      multiples = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tmultiples = op.attributes().getAttrType("Tmultiples");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Timestamp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Timestamp.java
index 2c017c1cd51..e77de2d52ee 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Timestamp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Timestamp.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -75,4 +78,11 @@ public Output<TFloat64> ts() {
   public Output<TFloat64> asOutput() {
     return ts;
   }
+
+  public static class Inputs extends RawOpInputs<Timestamp> {
+    public Inputs(GraphOperation op) {
+      super(new Timestamp(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKUnique.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKUnique.java
index 5d20c9f2160..081529475b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKUnique.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKUnique.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -65,8 +68,8 @@ private TopKUnique(Operation operation) {
    * Factory method to create a class wrapping a new TopKUnique operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param k the value of the k property
+   * @param input The input value
+   * @param k The value of the k attribute
    * @return a new instance of TopKUnique
    */
   @Endpoint(
@@ -96,4 +99,23 @@ public Output<TFloat32> topk() {
   public Output<TInt32> topkIndices() {
     return topkIndices;
   }
+
+  public static class Inputs extends RawOpInputs<TopKUnique> {
+    /**
+     * The input input
+     */
+    public final Operand<TFloat32> input;
+
+    /**
+     * The k attribute
+     */
+    public final long k;
+
+    public Inputs(GraphOperation op) {
+      super(new TopKUnique(op), op, Arrays.asList("k"));
+      int inputIndex = 0;
+      input = (Operand<TFloat32>) op.input(inputIndex++);
+      k = op.attributes().getAttrInt("k");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKWithUnique.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKWithUnique.java
index e0e4d468a0f..856b03835ec 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKWithUnique.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TopKWithUnique.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -58,8 +61,8 @@ private TopKWithUnique(Operation operation) {
    * Factory method to create a class wrapping a new TopKWithUnique operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param k the value of the k property
+   * @param input The input value
+   * @param k The value of the k attribute
    * @return a new instance of TopKWithUnique
    */
   @Endpoint(
@@ -89,4 +92,23 @@ public Output<TFloat32> topk() {
   public Output<TInt32> topkIndices() {
     return topkIndices;
   }
+
+  public static class Inputs extends RawOpInputs<TopKWithUnique> {
+    /**
+     * The input input
+     */
+    public final Operand<TFloat32> input;
+
+    /**
+     * The k attribute
+     */
+    public final long k;
+
+    public Inputs(GraphOperation op) {
+      super(new TopKWithUnique(op), op, Arrays.asList("k"));
+      int inputIndex = 0;
+      input = (Operand<TFloat32>) op.input(inputIndex++);
+      k = op.attributes().getAttrInt("k");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java
index 00c93f97129..f39e219d59a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -69,10 +73,10 @@ private Unbatch(Operation operation) {
    * Factory method to create a class wrapping a new Unbatch operation.
    *
    * @param scope current scope
-   * @param batchedTensor the batchedTensor value
-   * @param batchIndex the batchIndex value
-   * @param id the id value
-   * @param timeoutMicros the value of the timeoutMicros property
+   * @param batchedTensor The batchedTensor value
+   * @param batchIndex The batchIndex value
+   * @param id The id value
+   * @param timeoutMicros The value of the timeoutMicros attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code Unbatch} output and operands
    * @return a new instance of Unbatch
@@ -167,4 +171,53 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Unbatch<T>> {
+    /**
+     * The batchedTensor input
+     */
+    public final Operand<T> batchedTensor;
+
+    /**
+     * The batchIndex input
+     */
+    public final Operand<TInt64> batchIndex;
+
+    /**
+     * The id input
+     */
+    public final Operand<TInt64> id;
+
+    /**
+     * The timeoutMicros attribute
+     */
+    public final long timeoutMicros;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Unbatch<>(op), op, Arrays.asList("timeout_micros", "container", "shared_name", "T"));
+      int inputIndex = 0;
+      batchedTensor = (Operand<T>) op.input(inputIndex++);
+      batchIndex = (Operand<TInt64>) op.input(inputIndex++);
+      id = (Operand<TInt64>) op.input(inputIndex++);
+      timeoutMicros = op.attributes().getAttrInt("timeout_micros");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java
index 877fda71471..71687f10ad6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -65,10 +69,10 @@ private UnbatchGrad(Operation operation) {
    * Factory method to create a class wrapping a new UnbatchGrad operation.
    *
    * @param scope current scope
-   * @param originalInput the originalInput value
-   * @param batchIndex the batchIndex value
-   * @param grad the grad value
-   * @param id the id value
+   * @param originalInput The originalInput value
+   * @param batchIndex The batchIndex value
+   * @param grad The grad value
+   * @param id The id value
    * @param options carries optional attribute values
    * @param <T> data type for {@code UnbatchGrad} output and operands
    * @return a new instance of UnbatchGrad
@@ -163,4 +167,53 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<UnbatchGrad<T>> {
+    /**
+     * The originalInput input
+     */
+    public final Operand<T> originalInput;
+
+    /**
+     * The batchIndex input
+     */
+    public final Operand<TInt64> batchIndex;
+
+    /**
+     * The grad input
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The id input
+     */
+    public final Operand<TInt64> id;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new UnbatchGrad<>(op), op, Arrays.asList("container", "shared_name", "T"));
+      int inputIndex = 0;
+      originalInput = (Operand<T>) op.input(inputIndex++);
+      batchIndex = (Operand<TInt64>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      id = (Operand<TInt64>) op.input(inputIndex++);
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java
index 7fec4d36cce..e08cc3c6309 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -98,7 +102,7 @@ private Unique(Operation operation) {
    * @param x A {@code Tensor}.
    * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to
    * find the unique elements.
-   * @param outIdx the value of the outIdx property
+   * @param outIdx The value of the outIdx attribute
    * @param <T> data type for {@code UniqueV2} output and operands
    * @param <V> data type for {@code UniqueV2} output and operands
    * @return a new instance of Unique
@@ -151,4 +155,42 @@ public Output<T> y() {
   public Output<V> idx() {
     return idx;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Unique<T, ?>> {
+    /**
+     * A {@code Tensor}.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to
+     * find the unique elements.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Taxis attribute
+     */
+    public final DataType Taxis;
+
+    /**
+     * The outIdx attribute
+     */
+    public final DataType outIdx;
+
+    public Inputs(GraphOperation op) {
+      super(new Unique<>(op), op, Arrays.asList("T", "Taxis", "out_idx"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Taxis = op.attributes().getAttrType("Taxis");
+      outIdx = op.attributes().getAttrType("out_idx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java
index 9ccfcc22319..0fa3499fab6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -105,7 +109,7 @@ private UniqueWithCounts(Operation operation) {
    * @param x A {@code Tensor}.
    * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to
    * find the unique elements.
-   * @param outIdx the value of the outIdx property
+   * @param outIdx The value of the outIdx attribute
    * @param <T> data type for {@code UniqueWithCountsV2} output and operands
    * @param <V> data type for {@code UniqueWithCountsV2} output and operands
    * @return a new instance of UniqueWithCounts
@@ -167,4 +171,42 @@ public Output<V> idx() {
   public Output<V> count() {
     return count;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<UniqueWithCounts<T, ?>> {
+    /**
+     * A {@code Tensor}.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to
+     * find the unique elements.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Taxis attribute
+     */
+    public final DataType Taxis;
+
+    /**
+     * The outIdx attribute
+     */
+    public final DataType outIdx;
+
+    public Inputs(GraphOperation op) {
+      super(new UniqueWithCounts<>(op), op, Arrays.asList("T", "Taxis", "out_idx"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Taxis = op.attributes().getAttrType("Taxis");
+      outIdx = op.attributes().getAttrType("out_idx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java
index 4a603b49357..17ca0f50647 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -100,4 +104,31 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<UnravelIndex<T>> {
+    /**
+     * An 0-D or 1-D {@code int} Tensor whose elements are indices into the
+     * flattened version of an array of dimensions dims.
+     */
+    public final Operand<T> indices;
+
+    /**
+     * An 1-D {@code int} Tensor. The shape of the array to use for unraveling
+     * indices.
+     */
+    public final Operand<T> dims;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new UnravelIndex<>(op), op, Arrays.asList("Tidx"));
+      int inputIndex = 0;
+      indices = (Operand<T>) op.input(inputIndex++);
+      dims = (Operand<T>) op.input(inputIndex++);
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java
index 19d4e08c44e..0038c66838c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java
@@ -20,14 +20,17 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -67,7 +70,7 @@ private Unstack(Operation operation) {
    *
    * @param scope current scope
    * @param value 1-D or higher, with {@code axis} dimension size equal to {@code num}.
-   * @param num the value of the num property
+   * @param num The value of the num attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code Unpack} output and operands
    * @return a new instance of Unstack
@@ -137,4 +140,30 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Unstack<T>> {
+    /**
+     * 1-D or higher, with {@code axis} dimension size equal to {@code num}.
+     */
+    public final Operand<T> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Dimension along which to unpack.  Negative values wrap around, so the
+     * valid range is `[-R, R)`.
+     */
+    public final long axis;
+
+    public Inputs(GraphOperation op) {
+      super(new Unstack<>(op), op, Arrays.asList("T", "axis"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      axis = op.attributes().getAttrInt("axis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java
index a0cd29d2014..def9253c00c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -58,7 +61,7 @@ private Unstage(Operation operation) {
    * Factory method to create a class wrapping a new Unstage operation.
    *
    * @param scope current scope
-   * @param dtypes the value of the dtypes property
+   * @param dtypes The value of the dtypes attribute
    * @param options carries optional attribute values
    * @return a new instance of Unstage
    */
@@ -202,4 +205,41 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Unstage> {
+    /**
+     * The capacity attribute
+     */
+    public final long capacity;
+
+    /**
+     * The memoryLimit attribute
+     */
+    public final long memoryLimit;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new Unstage(op), op, Arrays.asList("capacity", "memory_limit", "dtypes", "container", "shared_name"));
+      int inputIndex = 0;
+      capacity = op.attributes().getAttrInt("capacity");
+      memoryLimit = op.attributes().getAttrInt("memory_limit");
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java
index 23a292eeaf7..f7a13f62d04 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -68,7 +72,7 @@ private UpperBound(Operation operation) {
    * @param sortedInputs 2-D Tensor where each row is ordered.
    * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains
    * the values that will be searched for in {@code sorted_search_values}.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code UpperBound} output and operands
    * @param <T> data type for {@code UpperBound} output and operands
    * @return a new instance of UpperBound
@@ -118,4 +122,36 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<UpperBound<?>> {
+    /**
+     * 2-D Tensor where each row is ordered.
+     */
+    public final Operand<T> sortedInputs;
+
+    /**
+     * 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains
+     * the values that will be searched for in {@code sorted_search_values}.
+     */
+    public final Operand<T> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new UpperBound<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      sortedInputs = (Operand<T>) op.input(inputIndex++);
+      values = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java
index 465941df1ab..67e1454d37c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -127,7 +130,7 @@ public static Options allowedDevices(List<String> allowedDevices) {
    * output ResourceHandle represents a per-replica/partitioned resource variable.
    * @return this Options instance.
    */
-  public static Options allowedDevices(String[] allowedDevices) {
+  public static Options allowedDevices(String... allowedDevices) {
     return new Options().allowedDevices(allowedDevices);
   }
 
@@ -205,4 +208,43 @@ public Options allowedDevices(String... allowedDevices) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<VarHandleOp> {
+    /**
+     * the container this variable is placed in.
+     */
+    public final String container;
+
+    /**
+     * the name by which this variable is referred to.
+     */
+    public final String sharedName;
+
+    /**
+     * the type of this variable. Must agree with the dtypes
+     * of all ops using this variable.
+     */
+    public final DataType dtype;
+
+    /**
+     * The (possibly partially specified) shape of this variable.
+     */
+    public final Shape shape;
+
+    /**
+     * DEPRECATED. The allowed devices containing the resource variable. Set when the
+     * output ResourceHandle represents a per-replica/partitioned resource variable.
+     */
+    public final String[] allowedDevices;
+
+    public Inputs(GraphOperation op) {
+      super(new VarHandleOp(op), op, Arrays.asList("container", "shared_name", "dtype", "shape", "allowed_devices"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      allowedDevices = op.attributes().getAttrStringList("allowed_devices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarIsInitializedOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarIsInitializedOp.java
index 93e9feb7f44..25156efd4ec 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarIsInitializedOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarIsInitializedOp.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -76,4 +79,17 @@ public Output<TBool> isInitialized() {
   public Output<TBool> asOutput() {
     return isInitialized;
   }
+
+  public static class Inputs extends RawOpInputs<VarIsInitializedOp> {
+    /**
+     * the input resource handle.
+     */
+    public final Operand<? extends TType> resource;
+
+    public Inputs(GraphOperation op) {
+      super(new VarIsInitializedOp(op), op, Arrays.asList());
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java
index 04b8a8df6f1..12eebf8189c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -154,4 +158,37 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Variable<?>> {
+    /**
+     * The shape of the variable tensor.
+     */
+    public final Shape shape;
+
+    /**
+     * The type of elements in the variable tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * If non-empty, this variable is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this variable is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new Variable<>(op), op, Arrays.asList("shape", "dtype", "container", "shared_name"));
+      int inputIndex = 0;
+      shape = op.attributes().getAttrShape("shape");
+      dtype = op.attributes().getAttrType("dtype");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java
index a026bd66862..f7d5a59a1b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -60,8 +64,8 @@ private VariableShape(Operation operation) {
    * Factory method to create a class wrapping a new VariableShape operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <T> data type for {@code VariableShape} output and operands
    * @return a new instance of VariableShape
    */
@@ -80,7 +84,7 @@ public static <T extends TNumber> VariableShape<T> create(Scope scope,
    * Factory method to create a class wrapping a new VariableShape operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of VariableShape, with default output types
    */
   @Endpoint(
@@ -103,4 +107,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<VariableShape<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new VariableShape<>(op), op, Arrays.asList("out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Where.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Where.java
index fefc32b1675..4fc22c56aed 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Where.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Where.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -107,7 +111,7 @@ private Where(Operation operation) {
    * Factory method to create a class wrapping a new Where operation.
    *
    * @param scope current scope
-   * @param condition the condition value
+   * @param condition The condition value
    * @return a new instance of Where
    */
   @Endpoint(
@@ -132,4 +136,23 @@ public Output<TInt64> index() {
   public Output<TInt64> asOutput() {
     return index;
   }
+
+  public static class Inputs extends RawOpInputs<Where> {
+    /**
+     * The condition input
+     */
+    public final Operand<? extends TType> condition;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Where(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      condition = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/While.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/While.java
index 714929f426c..958b06e7c0b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/While.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/While.java
@@ -94,7 +94,7 @@ static Options outputShapes(List<Shape> outputShapes) {
    * @param outputShapes the outputShapes option
    * @return this Options instance.
    */
-  static Options outputShapes(Shape[] outputShapes) {
+  static Options outputShapes(Shape... outputShapes) {
     return new Options().outputShapes(outputShapes);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Window.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Window.java
index e10608a3782..a363a2eab9e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Window.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Window.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,9 +55,9 @@ private Window(Operation operation) {
    * Factory method to create a class wrapping a new Window operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputs The inputs value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of Window
    */
   @Endpoint(
@@ -86,4 +90,37 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<Window> {
+    /**
+     * The inputs input
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The Tinputs attribute
+     */
+    public final DataType[] Tinputs;
+
+    public Inputs(GraphOperation op) {
+      super(new Window(op), op, Arrays.asList("output_types", "output_shapes", "Tinputs"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      Tinputs = op.attributes().getAttrTypeList("Tinputs");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java
index 815c4adcc41..ece2adac5ce 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.core;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -77,4 +81,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ZerosLike<T>> {
+    /**
+     * a tensor of type T.
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ZerosLike<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java
index b6d11b4598b..010fdceba22 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,8 +61,8 @@ private AnonymousIterator(Operation operation) {
    * Factory method to create a class wrapping a new AnonymousIteratorV2 operation.
    *
    * @param scope current scope
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AnonymousIterator
    */
   @Endpoint(
@@ -96,4 +100,23 @@ public Output<? extends TType> handle() {
   public Output<? extends TType> deleter() {
     return deleter;
   }
+
+  public static class Inputs extends RawOpInputs<AnonymousIterator> {
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new AnonymousIterator(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMemoryCache.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMemoryCache.java
index 4a24a88e1ca..1ab01851c85 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMemoryCache.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMemoryCache.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -77,4 +80,11 @@ public Output<? extends TType> handle() {
   public Output<? extends TType> deleter() {
     return deleter;
   }
+
+  public static class Inputs extends RawOpInputs<AnonymousMemoryCache> {
+    public Inputs(GraphOperation op) {
+      super(new AnonymousMemoryCache(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java
index 362ff05583e..19f0ae37083 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,9 +57,9 @@ private AnonymousMultiDeviceIterator(Operation operation) {
    * Factory method to create a class wrapping a new AnonymousMultiDeviceIterator operation.
    *
    * @param scope current scope
-   * @param devices the value of the devices property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param devices The value of the devices attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AnonymousMultiDeviceIterator
    */
   @Endpoint(
@@ -98,4 +102,29 @@ public Output<? extends TType> handle() {
   public Output<? extends TType> deleter() {
     return deleter;
   }
+
+  public static class Inputs extends RawOpInputs<AnonymousMultiDeviceIterator> {
+    /**
+     * The devices attribute
+     */
+    public final String[] devices;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new AnonymousMultiDeviceIterator(op), op, Arrays.asList("devices", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      devices = op.attributes().getAttrStringList("devices");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertCardinalityDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertCardinalityDataset.java
index 766e8632d32..004b64d085e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertCardinalityDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertCardinalityDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,10 +60,10 @@ private AssertCardinalityDataset(Operation operation) {
    * Factory method to create a class wrapping a new AssertCardinalityDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param cardinality the cardinality value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param cardinality The cardinality value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AssertCardinalityDataset
    */
   @Endpoint(
@@ -94,4 +98,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<AssertCardinalityDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The cardinality input
+     */
+    public final Operand<TInt64> cardinality;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new AssertCardinalityDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      cardinality = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java
index d6598f345a2..957589aa4c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -67,8 +71,8 @@ private AssertNextDataset(Operation operation) {
    * {@code data.AssertNextDataset} passes through the outputs of its input dataset.
    * @param transformations A {@code tf.string} vector {@code tf.Tensor} identifying the transformations that are
    * expected to happen next.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AssertNextDataset
    */
   @Endpoint(
@@ -103,4 +107,37 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<AssertNextDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     * {@code data.AssertNextDataset} passes through the outputs of its input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A {@code tf.string} vector {@code tf.Tensor} identifying the transformations that are
+     * expected to happen next.
+     */
+    public final Operand<TString> transformations;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new AssertNextDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      transformations = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java
index 616e51b9948..46150ca633f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -65,8 +69,8 @@ private AutoShardDataset(Operation operation) {
    * @param inputDataset A variant tensor representing the input dataset.
    * @param numWorkers A scalar representing the number of workers to distribute this dataset across.
    * @param index A scalar representing the index of the current worker out of num_workers.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of AutoShardDataset
    */
@@ -167,4 +171,53 @@ public Options numReplicas(Long numReplicas) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AutoShardDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of workers to distribute this dataset across.
+     */
+    public final Operand<TInt64> numWorkers;
+
+    /**
+     * A scalar representing the index of the current worker out of num_workers.
+     */
+    public final Operand<TInt64> index;
+
+    /**
+     * The autoShardPolicy attribute
+     */
+    public final long autoShardPolicy;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The numReplicas attribute
+     */
+    public final long numReplicas;
+
+    public Inputs(GraphOperation op) {
+      super(new AutoShardDataset(op), op, Arrays.asList("auto_shard_policy", "output_types", "output_shapes", "num_replicas"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numWorkers = (Operand<TInt64>) op.input(inputIndex++);
+      index = (Operand<TInt64>) op.input(inputIndex++);
+      autoShardPolicy = op.attributes().getAttrInt("auto_shard_policy");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      numReplicas = op.attributes().getAttrInt("num_replicas");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java
index 9443135081b..aaf79b9104d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -57,12 +61,12 @@ private BatchDataset(Operation operation) {
    * Factory method to create a class wrapping a new BatchDatasetV2 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param batchSize A scalar representing the number of elements to accumulate in a batch.
    * @param dropRemainder A scalar representing whether the last batch should be dropped in case its size
    * is smaller than desired.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of BatchDataset
    */
@@ -137,4 +141,48 @@ public Options parallelCopy(Boolean parallelCopy) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BatchDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements to accumulate in a batch.
+     */
+    public final Operand<TInt64> batchSize;
+
+    /**
+     * A scalar representing whether the last batch should be dropped in case its size
+     * is smaller than desired.
+     */
+    public final Operand<TBool> dropRemainder;
+
+    /**
+     * The parallelCopy attribute
+     */
+    public final boolean parallelCopy;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchDataset(op), op, Arrays.asList("parallel_copy", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      batchSize = (Operand<TInt64>) op.input(inputIndex++);
+      dropRemainder = (Operand<TBool>) op.input(inputIndex++);
+      parallelCopy = op.attributes().getAttrBool("parallel_copy");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java
index 3eb3923a58c..ead0ae179b3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -56,10 +60,10 @@ private BytesProducedStatsDataset(Operation operation) {
    * Factory method to create a class wrapping a new BytesProducedStatsDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param tag the tag value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param tag The tag value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of BytesProducedStatsDataset
    */
   @Endpoint(
@@ -93,4 +97,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<BytesProducedStatsDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new BytesProducedStatsDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CSVDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CSVDataset.java
index 36f923b377f..5865a5bbfff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CSVDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CSVDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -58,17 +62,17 @@ private CSVDataset(Operation operation) {
    * Factory method to create a class wrapping a new CSVDatasetV2 operation.
    *
    * @param scope current scope
-   * @param filenames the filenames value
-   * @param compressionType the compressionType value
-   * @param bufferSize the bufferSize value
-   * @param header the header value
-   * @param fieldDelim the fieldDelim value
-   * @param useQuoteDelim the useQuoteDelim value
-   * @param naValue the naValue value
-   * @param selectCols the selectCols value
-   * @param recordDefaults the recordDefaults value
-   * @param excludeCols the excludeCols value
-   * @param outputShapes the value of the outputShapes property
+   * @param filenames The filenames value
+   * @param compressionType The compressionType value
+   * @param bufferSize The bufferSize value
+   * @param header The header value
+   * @param fieldDelim The fieldDelim value
+   * @param useQuoteDelim The useQuoteDelim value
+   * @param naValue The naValue value
+   * @param selectCols The selectCols value
+   * @param recordDefaults The recordDefaults value
+   * @param excludeCols The excludeCols value
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of CSVDataset
    */
   @Endpoint(
@@ -112,4 +116,85 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<CSVDataset> {
+    /**
+     * The filenames input
+     */
+    public final Operand<TString> filenames;
+
+    /**
+     * The compressionType input
+     */
+    public final Operand<TString> compressionType;
+
+    /**
+     * The bufferSize input
+     */
+    public final Operand<TInt64> bufferSize;
+
+    /**
+     * The header input
+     */
+    public final Operand<TBool> header;
+
+    /**
+     * The fieldDelim input
+     */
+    public final Operand<TString> fieldDelim;
+
+    /**
+     * The useQuoteDelim input
+     */
+    public final Operand<TBool> useQuoteDelim;
+
+    /**
+     * The naValue input
+     */
+    public final Operand<TString> naValue;
+
+    /**
+     * The selectCols input
+     */
+    public final Operand<TInt64> selectCols;
+
+    /**
+     * The recordDefaults input
+     */
+    public final Iterable<Operand<?>> recordDefaults;
+
+    /**
+     * The excludeCols input
+     */
+    public final Operand<TInt64> excludeCols;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new CSVDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      filenames = (Operand<TString>) op.input(inputIndex++);
+      compressionType = (Operand<TString>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+      header = (Operand<TBool>) op.input(inputIndex++);
+      fieldDelim = (Operand<TString>) op.input(inputIndex++);
+      useQuoteDelim = (Operand<TBool>) op.input(inputIndex++);
+      naValue = (Operand<TString>) op.input(inputIndex++);
+      selectCols = (Operand<TInt64>) op.input(inputIndex++);
+      int recordDefaultsLength = op.inputListLength("record_defaults");
+      recordDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, recordDefaultsLength));
+      inputIndex += recordDefaultsLength;
+      excludeCols = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java
index a52a8fba718..8634e504fa2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -56,11 +60,11 @@ private CacheDataset(Operation operation) {
    * Factory method to create a class wrapping a new CacheDatasetV2 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param filename the filename value
-   * @param cache the cache value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param filename The filename value
+   * @param cache The cache value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of CacheDataset
    */
   @Endpoint(
@@ -96,4 +100,41 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<CacheDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The filename input
+     */
+    public final Operand<TString> filename;
+
+    /**
+     * The cache input
+     */
+    public final Operand<? extends TType> cache;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new CacheDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      filename = (Operand<TString>) op.input(inputIndex++);
+      cache = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestBranchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestBranchDataset.java
index 6a5cd6ae86f..ce7bc509f4e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestBranchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestBranchDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -57,15 +61,15 @@ private ChooseFastestBranchDataset(Operation operation) {
    * Factory method to create a class wrapping a new ChooseFastestBranchDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param ratioNumerator the ratioNumerator value
-   * @param ratioDenominator the ratioDenominator value
-   * @param otherArguments the otherArguments value
-   * @param numElementsPerBranch the value of the numElementsPerBranch property
-   * @param branches the value of the branches property
-   * @param otherArgumentsLengths the value of the otherArgumentsLengths property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param ratioNumerator The ratioNumerator value
+   * @param ratioDenominator The ratioDenominator value
+   * @param otherArguments The otherArguments value
+   * @param numElementsPerBranch The value of the numElementsPerBranch attribute
+   * @param branches The value of the branches attribute
+   * @param otherArgumentsLengths The value of the otherArgumentsLengths attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ChooseFastestBranchDataset
    */
   @Endpoint(
@@ -115,4 +119,67 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ChooseFastestBranchDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The ratioNumerator input
+     */
+    public final Operand<TInt64> ratioNumerator;
+
+    /**
+     * The ratioDenominator input
+     */
+    public final Operand<TInt64> ratioDenominator;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The numElementsPerBranch attribute
+     */
+    public final long numElementsPerBranch;
+
+    /**
+     * The otherArgumentsLengths attribute
+     */
+    public final long[] otherArgumentsLengths;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ChooseFastestBranchDataset(op), op, Arrays.asList("Targuments", "num_elements_per_branch", "other_arguments_lengths", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      ratioNumerator = (Operand<TInt64>) op.input(inputIndex++);
+      ratioDenominator = (Operand<TInt64>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      numElementsPerBranch = op.attributes().getAttrInt("num_elements_per_branch");
+      otherArgumentsLengths = op.attributes().getAttrIntList("other_arguments_lengths");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java
index bec675ca410..a617ab45fa3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,10 +59,10 @@ private ChooseFastestDataset(Operation operation) {
    * Factory method to create a class wrapping a new ChooseFastestDataset operation.
    *
    * @param scope current scope
-   * @param inputDatasets the inputDatasets value
-   * @param numExperiments the value of the numExperiments property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDatasets The inputDatasets value
+   * @param numExperiments The value of the numExperiments attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ChooseFastestDataset
    */
   @Endpoint(
@@ -93,4 +97,37 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ChooseFastestDataset> {
+    /**
+     * The inputDatasets input
+     */
+    public final Iterable<Operand<? extends TType>> inputDatasets;
+
+    /**
+     * The numExperiments attribute
+     */
+    public final long numExperiments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ChooseFastestDataset(op), op, Arrays.asList("num_experiments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      int inputDatasetsLength = op.inputListLength("input_datasets");
+      inputDatasets = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, inputDatasetsLength));
+      inputIndex += inputDatasetsLength;
+      numExperiments = op.attributes().getAttrInt("num_experiments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CompressElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CompressElement.java
index 270538bf6a4..6fc99b577b4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CompressElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CompressElement.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -49,7 +53,7 @@ private CompressElement(Operation operation) {
    * Factory method to create a class wrapping a new CompressElement operation.
    *
    * @param scope current scope
-   * @param components the components value
+   * @param components The components value
    * @return a new instance of CompressElement
    */
   @Endpoint(
@@ -75,4 +79,25 @@ public Output<? extends TType> compressed() {
   public Output<TType> asOutput() {
     return (Output<TType>) compressed;
   }
+
+  public static class Inputs extends RawOpInputs<CompressElement> {
+    /**
+     * The components input
+     */
+    public final Iterable<Operand<?>> components;
+
+    /**
+     * The inputTypes attribute
+     */
+    public final DataType[] inputTypes;
+
+    public Inputs(GraphOperation op) {
+      super(new CompressElement(op), op, Arrays.asList("input_types"));
+      int inputIndex = 0;
+      int componentsLength = op.inputListLength("components");
+      components = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, componentsLength));
+      inputIndex += componentsLength;
+      inputTypes = op.attributes().getAttrTypeList("input_types");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java
index 0bc81bd18a2..b5f7cb8c11a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,10 +59,10 @@ private ConcatenateDataset(Operation operation) {
    * Factory method to create a class wrapping a new ConcatenateDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param anotherDataset the anotherDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param anotherDataset The anotherDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ConcatenateDataset
    */
   @Endpoint(
@@ -93,4 +97,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ConcatenateDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The anotherDataset input
+     */
+    public final Operand<? extends TType> anotherDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ConcatenateDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      anotherDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DataServiceDatasetV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DataServiceDatasetV2.java
index 2ee876e396f..20cf98e1806 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DataServiceDatasetV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DataServiceDatasetV2.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -57,17 +61,17 @@ private DataServiceDatasetV2(Operation operation) {
    * Factory method to create a class wrapping a new DataServiceDatasetV2 operation.
    *
    * @param scope current scope
-   * @param datasetId the datasetId value
-   * @param processingMode the processingMode value
-   * @param address the address value
-   * @param protocol the protocol value
-   * @param jobName the jobName value
-   * @param consumerIndex the consumerIndex value
-   * @param numConsumers the numConsumers value
-   * @param maxOutstandingRequests the maxOutstandingRequests value
-   * @param iterationCounter the iterationCounter value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param datasetId The datasetId value
+   * @param processingMode The processingMode value
+   * @param address The address value
+   * @param protocol The protocol value
+   * @param jobName The jobName value
+   * @param consumerIndex The consumerIndex value
+   * @param numConsumers The numConsumers value
+   * @param maxOutstandingRequests The maxOutstandingRequests value
+   * @param iterationCounter The iterationCounter value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of DataServiceDatasetV2
    */
@@ -202,4 +206,95 @@ public Options targetWorkers(String targetWorkers) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DataServiceDatasetV2> {
+    /**
+     * The datasetId input
+     */
+    public final Operand<TInt64> datasetId;
+
+    /**
+     * The processingMode input
+     */
+    public final Operand<TString> processingMode;
+
+    /**
+     * The address input
+     */
+    public final Operand<TString> address;
+
+    /**
+     * The protocol input
+     */
+    public final Operand<TString> protocol;
+
+    /**
+     * The jobName input
+     */
+    public final Operand<TString> jobName;
+
+    /**
+     * The consumerIndex input
+     */
+    public final Operand<TInt64> consumerIndex;
+
+    /**
+     * The numConsumers input
+     */
+    public final Operand<TInt64> numConsumers;
+
+    /**
+     * The maxOutstandingRequests input
+     */
+    public final Operand<TInt64> maxOutstandingRequests;
+
+    /**
+     * The iterationCounter input
+     */
+    public final Operand<? extends TType> iterationCounter;
+
+    /**
+     * The taskRefreshIntervalHintMs attribute
+     */
+    public final long taskRefreshIntervalHintMs;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The dataTransferProtocol attribute
+     */
+    public final String dataTransferProtocol;
+
+    /**
+     * The targetWorkers attribute
+     */
+    public final String targetWorkers;
+
+    public Inputs(GraphOperation op) {
+      super(new DataServiceDatasetV2(op), op, Arrays.asList("task_refresh_interval_hint_ms", "output_types", "output_shapes", "data_transfer_protocol", "target_workers"));
+      int inputIndex = 0;
+      datasetId = (Operand<TInt64>) op.input(inputIndex++);
+      processingMode = (Operand<TString>) op.input(inputIndex++);
+      address = (Operand<TString>) op.input(inputIndex++);
+      protocol = (Operand<TString>) op.input(inputIndex++);
+      jobName = (Operand<TString>) op.input(inputIndex++);
+      consumerIndex = (Operand<TInt64>) op.input(inputIndex++);
+      numConsumers = (Operand<TInt64>) op.input(inputIndex++);
+      maxOutstandingRequests = (Operand<TInt64>) op.input(inputIndex++);
+      iterationCounter = (Operand<? extends TType>) op.input(inputIndex++);
+      taskRefreshIntervalHintMs = op.attributes().getAttrInt("task_refresh_interval_hint_ms");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      dataTransferProtocol = op.attributes().getAttrString("data_transfer_protocol");
+      targetWorkers = op.attributes().getAttrString("target_workers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetCardinality.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetCardinality.java
index 72216097974..4d16a0c6556 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetCardinality.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetCardinality.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -79,4 +82,17 @@ public Output<TInt64> cardinality() {
   public Output<TInt64> asOutput() {
     return cardinality;
   }
+
+  public static class Inputs extends RawOpInputs<DatasetCardinality> {
+    /**
+     * A variant tensor representing the dataset to return cardinality for.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    public Inputs(GraphOperation op) {
+      super(new DatasetCardinality(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetFromGraph.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetFromGraph.java
index c794a89a65d..b1e0f690462 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetFromGraph.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetFromGraph.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -80,4 +83,17 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<DatasetFromGraph> {
+    /**
+     * The graph representation of the dataset (as serialized GraphDef).
+     */
+    public final Operand<TString> graphDef;
+
+    public Inputs(GraphOperation op) {
+      super(new DatasetFromGraph(op), op, Arrays.asList());
+      int inputIndex = 0;
+      graphDef = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToGraph.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToGraph.java
index 0177a116cbe..b8c92cd4c61 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToGraph.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToGraph.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -144,4 +147,29 @@ public Options stripDeviceAssignment(Boolean stripDeviceAssignment) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DatasetToGraph> {
+    /**
+     * A variant tensor representing the dataset to return the graph representation for.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The externalStatePolicy attribute
+     */
+    public final long externalStatePolicy;
+
+    /**
+     * The stripDeviceAssignment attribute
+     */
+    public final boolean stripDeviceAssignment;
+
+    public Inputs(GraphOperation op) {
+      super(new DatasetToGraph(op), op, Arrays.asList("external_state_policy", "strip_device_assignment"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      externalStatePolicy = op.attributes().getAttrInt("external_state_policy");
+      stripDeviceAssignment = op.attributes().getAttrBool("strip_device_assignment");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java
index f5b779ed6bc..1ebef27faa2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,8 +63,8 @@ private DatasetToSingleElement(Operation operation) {
    *
    * @param scope current scope
    * @param dataset A handle to a dataset that contains a single element.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of DatasetToSingleElement
    */
   @Endpoint(
@@ -94,4 +97,29 @@ public List<Output<?>> components() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) components.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<DatasetToSingleElement> {
+    /**
+     * A handle to a dataset that contains a single element.
+     */
+    public final Operand<? extends TType> dataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new DatasetToSingleElement(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      dataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToTfRecord.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToTfRecord.java
index bb4b58da845..02a9153d092 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToTfRecord.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToTfRecord.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -64,4 +67,30 @@ public static DatasetToTfRecord create(Scope scope, Operand<? extends TType> inp
     opBuilder.addInput(compressionType.asOutput());
     return new DatasetToTfRecord(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DatasetToTfRecord> {
+    /**
+     * A variant tensor representing the dataset to write.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar string tensor representing the filename to use.
+     */
+    public final Operand<TString> filename;
+
+    /**
+     * A scalar string tensor containing either (i) the empty string (no
+     * compression), (ii) &quot;ZLIB&quot;, or (iii) &quot;GZIP&quot;.
+     */
+    public final Operand<TString> compressionType;
+
+    public Inputs(GraphOperation op) {
+      super(new DatasetToTfRecord(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      filename = (Operand<TString>) op.input(inputIndex++);
+      compressionType = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteIterator.java
index 0a696c8288e..6888dfa07ca 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteIterator.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -60,4 +63,23 @@ public static DeleteIterator create(Scope scope, Operand<? extends TType> handle
     opBuilder.addInput(deleter.asOutput());
     return new DeleteIterator(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DeleteIterator> {
+    /**
+     * A handle to the iterator to delete.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * A variant deleter.
+     */
+    public final Operand<? extends TType> deleter;
+
+    public Inputs(GraphOperation op) {
+      super(new DeleteIterator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      deleter = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMemoryCache.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMemoryCache.java
index c4b3b450727..d342a701ddf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMemoryCache.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMemoryCache.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -42,8 +45,8 @@ private DeleteMemoryCache(Operation operation) {
    * Factory method to create a class wrapping a new DeleteMemoryCache operation.
    *
    * @param scope current scope
-   * @param handle the handle value
-   * @param deleter the deleter value
+   * @param handle The handle value
+   * @param deleter The deleter value
    * @return a new instance of DeleteMemoryCache
    */
   @Endpoint(
@@ -56,4 +59,23 @@ public static DeleteMemoryCache create(Scope scope, Operand<? extends TType> han
     opBuilder.addInput(deleter.asOutput());
     return new DeleteMemoryCache(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DeleteMemoryCache> {
+    /**
+     * The handle input
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The deleter input
+     */
+    public final Operand<? extends TType> deleter;
+
+    public Inputs(GraphOperation op) {
+      super(new DeleteMemoryCache(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      deleter = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMultiDeviceIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMultiDeviceIterator.java
index af43926e234..cc1239be199 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMultiDeviceIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeleteMultiDeviceIterator.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -60,4 +63,31 @@ public static DeleteMultiDeviceIterator create(Scope scope,
     opBuilder.addInput(deleter.asOutput());
     return new DeleteMultiDeviceIterator(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DeleteMultiDeviceIterator> {
+    /**
+     * A handle to the multi device iterator to delete.
+     */
+    public final Operand<? extends TType> multiDeviceIterator;
+
+    /**
+     * A list of iterator handles (unused). This is added so that automatic control dependencies get added during function tracing that ensure this op runs after all the dependent iterators are deleted.
+     */
+    public final Iterable<Operand<? extends TType>> iterators;
+
+    /**
+     * A variant deleter.
+     */
+    public final Operand<? extends TType> deleter;
+
+    public Inputs(GraphOperation op) {
+      super(new DeleteMultiDeviceIterator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      multiDeviceIterator = (Operand<? extends TType>) op.input(inputIndex++);
+      int iteratorsLength = op.inputListLength("iterators");
+      iterators = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, iteratorsLength));
+      inputIndex += iteratorsLength;
+      deleter = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java
index d507b656d58..69815a21d5c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -62,8 +66,8 @@ private DenseToSparseBatchDataset(Operation operation) {
    * @param rowShape A vector representing the dense shape of each row in the produced
    * SparseTensor. The shape may be partially specified, using {@code -1} to indicate
    * that a particular dimension should use the maximum size of all batch elements.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of DenseToSparseBatchDataset
    */
   @Endpoint(
@@ -99,4 +103,44 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<DenseToSparseBatchDataset> {
+    /**
+     * A handle to an input dataset. Must have a single component.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements to accumulate in a
+     * batch.
+     */
+    public final Operand<TInt64> batchSize;
+
+    /**
+     * A vector representing the dense shape of each row in the produced
+     * SparseTensor. The shape may be partially specified, using {@code -1} to indicate
+     * that a particular dimension should use the maximum size of all batch elements.
+     */
+    public final Operand<TInt64> rowShape;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new DenseToSparseBatchDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      batchSize = (Operand<TInt64>) op.input(inputIndex++);
+      rowShape = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeserializeIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeserializeIterator.java
index a7254cf58ea..0492d8e3a5b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeserializeIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DeserializeIterator.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -61,4 +64,24 @@ public static DeserializeIterator create(Scope scope, Operand<? extends TType> r
     opBuilder.addInput(serialized.asOutput());
     return new DeserializeIterator(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DeserializeIterator> {
+    /**
+     * A handle to an iterator resource.
+     */
+    public final Operand<? extends TType> resourceHandle;
+
+    /**
+     * A variant tensor storing the state of the iterator contained in the
+     * resource.
+     */
+    public final Operand<? extends TType> serialized;
+
+    public Inputs(GraphOperation op) {
+      super(new DeserializeIterator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      resourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      serialized = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java
index 93fa60508a4..9f2b7602cc6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,8 +63,8 @@ private DirectedInterleaveDataset(Operation operation) {
    * {@code N} data inputs should produce the next output element.
    * @param dataInputDatasets {@code N} datasets with the same type that will be interleaved according to
    * the values of {@code selector_input_dataset}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of DirectedInterleaveDataset
    */
@@ -135,4 +139,45 @@ public Options stopOnEmptyDataset(Boolean stopOnEmptyDataset) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DirectedInterleaveDataset> {
+    /**
+     * A dataset of scalar {@code DT_INT64} elements that determines which of the
+     * {@code N} data inputs should produce the next output element.
+     */
+    public final Operand<? extends TType> selectorInputDataset;
+
+    /**
+     * {@code N} datasets with the same type that will be interleaved according to
+     * the values of {@code selector_input_dataset}.
+     */
+    public final Iterable<Operand<? extends TType>> dataInputDatasets;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The stopOnEmptyDataset attribute
+     */
+    public final boolean stopOnEmptyDataset;
+
+    public Inputs(GraphOperation op) {
+      super(new DirectedInterleaveDataset(op), op, Arrays.asList("output_types", "output_shapes", "stop_on_empty_dataset"));
+      int inputIndex = 0;
+      selectorInputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int dataInputDatasetsLength = op.inputListLength("data_input_datasets");
+      dataInputDatasets = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, dataInputDatasetsLength));
+      inputIndex += dataInputDatasetsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      stopOnEmptyDataset = op.attributes().getAttrBool("stop_on_empty_dataset");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DummyIterationCounter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DummyIterationCounter.java
index 837efe0f7b1..10c0ad3c957 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DummyIterationCounter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DummyIterationCounter.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -72,4 +75,11 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<DummyIterationCounter> {
+    public Inputs(GraphOperation op) {
+      super(new DummyIterationCounter(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java
index a2b08845e55..20474ebe360 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private FilterByLastComponentDataset(Operation operation) {
    * Factory method to create a class wrapping a new FilterByLastComponentDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of FilterByLastComponentDataset
    */
   @Endpoint(
@@ -91,4 +95,29 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<FilterByLastComponentDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new FilterByLastComponentDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterDataset.java
index afdbd819ee7..46b5c47e762 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -62,12 +66,12 @@ private FilterDataset(Operation operation) {
    * Factory method to create a class wrapping a new FilterDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param otherArguments A list of tensors, typically values that were captured when
    * building a closure for {@code predicate}.
    * @param predicate A function returning a scalar boolean.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of FilterDataset
    */
   @Endpoint(
@@ -103,4 +107,44 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<FilterDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code predicate}.
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new FilterDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FinalizeDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FinalizeDataset.java
index 5c81b9c4d02..a020f21fddf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FinalizeDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FinalizeDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -56,8 +60,8 @@ private FinalizeDataset(Operation operation) {
    *
    * @param scope current scope
    * @param inputDataset A variant tensor representing the input dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of FinalizeDataset
    */
@@ -129,4 +133,35 @@ public Options hasCapturedRef(Boolean hasCapturedRef) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FinalizeDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The hasCapturedRef attribute
+     */
+    public final boolean hasCapturedRef;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new FinalizeDataset(op), op, Arrays.asList("has_captured_ref", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      hasCapturedRef = op.attributes().getAttrBool("has_captured_ref");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FixedLengthRecordDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FixedLengthRecordDataset.java
index 3ff58fd3784..7f0b41e25b9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FixedLengthRecordDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FixedLengthRecordDataset.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -54,12 +57,12 @@ private FixedLengthRecordDataset(Operation operation) {
    * Factory method to create a class wrapping a new FixedLengthRecordDatasetV2 operation.
    *
    * @param scope current scope
-   * @param filenames the filenames value
-   * @param headerBytes the headerBytes value
-   * @param recordBytes the recordBytes value
-   * @param footerBytes the footerBytes value
-   * @param bufferSize the bufferSize value
-   * @param compressionType the compressionType value
+   * @param filenames The filenames value
+   * @param headerBytes The headerBytes value
+   * @param recordBytes The recordBytes value
+   * @param footerBytes The footerBytes value
+   * @param bufferSize The bufferSize value
+   * @param compressionType The compressionType value
    * @return a new instance of FixedLengthRecordDataset
    */
   @Endpoint(
@@ -92,4 +95,47 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<FixedLengthRecordDataset> {
+    /**
+     * The filenames input
+     */
+    public final Operand<TString> filenames;
+
+    /**
+     * The headerBytes input
+     */
+    public final Operand<TInt64> headerBytes;
+
+    /**
+     * The recordBytes input
+     */
+    public final Operand<TInt64> recordBytes;
+
+    /**
+     * The footerBytes input
+     */
+    public final Operand<TInt64> footerBytes;
+
+    /**
+     * The bufferSize input
+     */
+    public final Operand<TInt64> bufferSize;
+
+    /**
+     * The compressionType input
+     */
+    public final Operand<TString> compressionType;
+
+    public Inputs(GraphOperation op) {
+      super(new FixedLengthRecordDataset(op), op, Arrays.asList());
+      int inputIndex = 0;
+      filenames = (Operand<TString>) op.input(inputIndex++);
+      headerBytes = (Operand<TInt64>) op.input(inputIndex++);
+      recordBytes = (Operand<TInt64>) op.input(inputIndex++);
+      footerBytes = (Operand<TInt64>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+      compressionType = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FlatMapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FlatMapDataset.java
index de6f6783271..2a084772e7a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FlatMapDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FlatMapDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,13 +63,13 @@ private FlatMapDataset(Operation operation) {
    * Factory method to create a class wrapping a new FlatMapDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    * {@code other_arguments}, to a Dataset variant that contains elements matching
    * {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of FlatMapDataset
    */
   @Endpoint(
@@ -101,4 +105,43 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<FlatMapDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new FlatMapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GeneratorDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GeneratorDataset.java
index be66d0404a9..fa2b2c66bc6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GeneratorDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GeneratorDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -56,14 +60,14 @@ private GeneratorDataset(Operation operation) {
    * Factory method to create a class wrapping a new GeneratorDataset operation.
    *
    * @param scope current scope
-   * @param initFuncOtherArgs the initFuncOtherArgs value
-   * @param nextFuncOtherArgs the nextFuncOtherArgs value
-   * @param finalizeFuncOtherArgs the finalizeFuncOtherArgs value
-   * @param initFunc the value of the initFunc property
-   * @param nextFunc the value of the nextFunc property
-   * @param finalizeFunc the value of the finalizeFunc property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param initFuncOtherArgs The initFuncOtherArgs value
+   * @param nextFuncOtherArgs The nextFuncOtherArgs value
+   * @param finalizeFuncOtherArgs The finalizeFuncOtherArgs value
+   * @param initFunc The value of the initFunc attribute
+   * @param nextFunc The value of the nextFunc attribute
+   * @param finalizeFunc The value of the finalizeFunc attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GeneratorDataset
    */
   @Endpoint(
@@ -103,4 +107,65 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<GeneratorDataset> {
+    /**
+     * The initFuncOtherArgs input
+     */
+    public final Iterable<Operand<?>> initFuncOtherArgs;
+
+    /**
+     * The nextFuncOtherArgs input
+     */
+    public final Iterable<Operand<?>> nextFuncOtherArgs;
+
+    /**
+     * The finalizeFuncOtherArgs input
+     */
+    public final Iterable<Operand<?>> finalizeFuncOtherArgs;
+
+    /**
+     * The TinitFuncArgs attribute
+     */
+    public final DataType[] TinitFuncArgs;
+
+    /**
+     * The TnextFuncArgs attribute
+     */
+    public final DataType[] TnextFuncArgs;
+
+    /**
+     * The TfinalizeFuncArgs attribute
+     */
+    public final DataType[] TfinalizeFuncArgs;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new GeneratorDataset(op), op, Arrays.asList("Tinit_func_args", "Tnext_func_args", "Tfinalize_func_args", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      int initFuncOtherArgsLength = op.inputListLength("init_func_other_args");
+      initFuncOtherArgs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, initFuncOtherArgsLength));
+      inputIndex += initFuncOtherArgsLength;
+      int nextFuncOtherArgsLength = op.inputListLength("next_func_other_args");
+      nextFuncOtherArgs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, nextFuncOtherArgsLength));
+      inputIndex += nextFuncOtherArgsLength;
+      int finalizeFuncOtherArgsLength = op.inputListLength("finalize_func_other_args");
+      finalizeFuncOtherArgs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, finalizeFuncOtherArgsLength));
+      inputIndex += finalizeFuncOtherArgsLength;
+      TinitFuncArgs = op.attributes().getAttrTypeList("Tinit_func_args");
+      TnextFuncArgs = op.attributes().getAttrTypeList("Tnext_func_args");
+      TfinalizeFuncArgs = op.attributes().getAttrTypeList("Tfinalize_func_args");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByReducerDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByReducerDataset.java
index 51a104f84c9..92c3b2023f8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByReducerDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByReducerDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -73,8 +77,8 @@ private GroupByReducerDataset(Operation operation) {
    * @param reduceFunc A function mapping the current reducer state and an element of {@code input_dataset},
    * concatenated with {@code reduce_func_other_arguments} to a new reducer state.
    * @param finalizeFunc A function mapping the final reducer state to an output element.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GroupByReducerDataset
    */
   @Endpoint(
@@ -119,4 +123,89 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<GroupByReducerDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code key_func}.
+     */
+    public final Iterable<Operand<?>> keyFuncOtherArguments;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code init_func}.
+     */
+    public final Iterable<Operand<?>> initFuncOtherArguments;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code reduce_func}.
+     */
+    public final Iterable<Operand<?>> reduceFuncOtherArguments;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code finalize_func}.
+     */
+    public final Iterable<Operand<?>> finalizeFuncOtherArguments;
+
+    /**
+     * The TkeyFuncOtherArguments attribute
+     */
+    public final DataType[] TkeyFuncOtherArguments;
+
+    /**
+     * The TinitFuncOtherArguments attribute
+     */
+    public final DataType[] TinitFuncOtherArguments;
+
+    /**
+     * The TreduceFuncOtherArguments attribute
+     */
+    public final DataType[] TreduceFuncOtherArguments;
+
+    /**
+     * The TfinalizeFuncOtherArguments attribute
+     */
+    public final DataType[] TfinalizeFuncOtherArguments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new GroupByReducerDataset(op), op, Arrays.asList("Tkey_func_other_arguments", "Tinit_func_other_arguments", "Treduce_func_other_arguments", "Tfinalize_func_other_arguments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int keyFuncOtherArgumentsLength = op.inputListLength("key_func_other_arguments");
+      keyFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, keyFuncOtherArgumentsLength));
+      inputIndex += keyFuncOtherArgumentsLength;
+      int initFuncOtherArgumentsLength = op.inputListLength("init_func_other_arguments");
+      initFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, initFuncOtherArgumentsLength));
+      inputIndex += initFuncOtherArgumentsLength;
+      int reduceFuncOtherArgumentsLength = op.inputListLength("reduce_func_other_arguments");
+      reduceFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, reduceFuncOtherArgumentsLength));
+      inputIndex += reduceFuncOtherArgumentsLength;
+      int finalizeFuncOtherArgumentsLength = op.inputListLength("finalize_func_other_arguments");
+      finalizeFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, finalizeFuncOtherArgumentsLength));
+      inputIndex += finalizeFuncOtherArgumentsLength;
+      TkeyFuncOtherArguments = op.attributes().getAttrTypeList("Tkey_func_other_arguments");
+      TinitFuncOtherArguments = op.attributes().getAttrTypeList("Tinit_func_other_arguments");
+      TreduceFuncOtherArguments = op.attributes().getAttrTypeList("Treduce_func_other_arguments");
+      TfinalizeFuncOtherArguments = op.attributes().getAttrTypeList("Tfinalize_func_other_arguments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByWindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByWindowDataset.java
index 36c6568c109..539d3cecf14 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByWindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/GroupByWindowDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,16 +61,16 @@ private GroupByWindowDataset(Operation operation) {
    * Factory method to create a class wrapping a new GroupByWindowDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param keyFuncOtherArguments the keyFuncOtherArguments value
-   * @param reduceFuncOtherArguments the reduceFuncOtherArguments value
-   * @param windowSizeFuncOtherArguments the windowSizeFuncOtherArguments value
+   * @param inputDataset The inputDataset value
+   * @param keyFuncOtherArguments The keyFuncOtherArguments value
+   * @param reduceFuncOtherArguments The reduceFuncOtherArguments value
+   * @param windowSizeFuncOtherArguments The windowSizeFuncOtherArguments value
    * @param keyFunc A function mapping an element of {@code input_dataset}, concatenated
    * with {@code key_func_other_arguments} to a scalar value of type DT_INT64.
-   * @param reduceFunc the value of the reduceFunc property
-   * @param windowSizeFunc the value of the windowSizeFunc property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param reduceFunc The value of the reduceFunc attribute
+   * @param windowSizeFunc The value of the windowSizeFunc attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GroupByWindowDataset
    */
   @Endpoint(
@@ -108,4 +112,71 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<GroupByWindowDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The keyFuncOtherArguments input
+     */
+    public final Iterable<Operand<?>> keyFuncOtherArguments;
+
+    /**
+     * The reduceFuncOtherArguments input
+     */
+    public final Iterable<Operand<?>> reduceFuncOtherArguments;
+
+    /**
+     * The windowSizeFuncOtherArguments input
+     */
+    public final Iterable<Operand<?>> windowSizeFuncOtherArguments;
+
+    /**
+     * The TkeyFuncOtherArguments attribute
+     */
+    public final DataType[] TkeyFuncOtherArguments;
+
+    /**
+     * The TreduceFuncOtherArguments attribute
+     */
+    public final DataType[] TreduceFuncOtherArguments;
+
+    /**
+     * The TwindowSizeFuncOtherArguments attribute
+     */
+    public final DataType[] TwindowSizeFuncOtherArguments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new GroupByWindowDataset(op), op, Arrays.asList("Tkey_func_other_arguments", "Treduce_func_other_arguments", "Twindow_size_func_other_arguments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int keyFuncOtherArgumentsLength = op.inputListLength("key_func_other_arguments");
+      keyFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, keyFuncOtherArgumentsLength));
+      inputIndex += keyFuncOtherArgumentsLength;
+      int reduceFuncOtherArgumentsLength = op.inputListLength("reduce_func_other_arguments");
+      reduceFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, reduceFuncOtherArgumentsLength));
+      inputIndex += reduceFuncOtherArgumentsLength;
+      int windowSizeFuncOtherArgumentsLength = op.inputListLength("window_size_func_other_arguments");
+      windowSizeFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, windowSizeFuncOtherArgumentsLength));
+      inputIndex += windowSizeFuncOtherArgumentsLength;
+      TkeyFuncOtherArguments = op.attributes().getAttrTypeList("Tkey_func_other_arguments");
+      TreduceFuncOtherArguments = op.attributes().getAttrTypeList("Treduce_func_other_arguments");
+      TwindowSizeFuncOtherArguments = op.attributes().getAttrTypeList("Twindow_size_func_other_arguments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java
index 25a819a79c6..60216480497 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private IgnoreErrorsDataset(Operation operation) {
    * Factory method to create a class wrapping a new IgnoreErrorsDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of IgnoreErrorsDataset
    */
@@ -129,4 +133,35 @@ public Options logWarning(Boolean logWarning) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<IgnoreErrorsDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The logWarning attribute
+     */
+    public final boolean logWarning;
+
+    public Inputs(GraphOperation op) {
+      super(new IgnoreErrorsDataset(op), op, Arrays.asList("output_types", "output_shapes", "log_warning"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      logWarning = op.attributes().getAttrBool("log_warning");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InitializeTableFromDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InitializeTableFromDataset.java
index a63dbae17c9..dba5858d2ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InitializeTableFromDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InitializeTableFromDataset.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -46,8 +49,8 @@ private InitializeTableFromDataset(Operation operation) {
    * Factory method to create a class wrapping a new InitializeTableFromDataset operation.
    *
    * @param scope current scope
-   * @param tableHandle the tableHandle value
-   * @param dataset the dataset value
+   * @param tableHandle The tableHandle value
+   * @param dataset The dataset value
    * @return a new instance of InitializeTableFromDataset
    */
   @Endpoint(
@@ -60,4 +63,23 @@ public static InitializeTableFromDataset create(Scope scope, Operand<? extends T
     opBuilder.addInput(dataset.asOutput());
     return new InitializeTableFromDataset(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<InitializeTableFromDataset> {
+    /**
+     * The tableHandle input
+     */
+    public final Operand<? extends TType> tableHandle;
+
+    /**
+     * The dataset input
+     */
+    public final Operand<? extends TType> dataset;
+
+    public Inputs(GraphOperation op) {
+      super(new InitializeTableFromDataset(op), op, Arrays.asList());
+      int inputIndex = 0;
+      tableHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      dataset = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InterleaveDataset.java
index f9a53cdc80b..25685e80ba5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/InterleaveDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -62,15 +66,15 @@ private InterleaveDataset(Operation operation) {
    * Factory method to create a class wrapping a new InterleaveDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param cycleLength the cycleLength value
-   * @param blockLength the blockLength value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param cycleLength The cycleLength value
+   * @param blockLength The blockLength value
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    * {@code other_arguments}, to a Dataset variant that contains elements matching
    * {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of InterleaveDataset
    */
   @Endpoint(
@@ -108,4 +112,55 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<InterleaveDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The cycleLength input
+     */
+    public final Operand<TInt64> cycleLength;
+
+    /**
+     * The blockLength input
+     */
+    public final Operand<TInt64> blockLength;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new InterleaveDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      cycleLength = (Operand<TInt64>) op.input(inputIndex++);
+      blockLength = (Operand<TInt64>) op.input(inputIndex++);
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java
index 455c8628554..35b4da85be7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,10 +59,10 @@ private Iterator(Operation operation) {
    * Factory method to create a class wrapping a new IteratorV2 operation.
    *
    * @param scope current scope
-   * @param sharedName the value of the sharedName property
-   * @param container the value of the container property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param sharedName The value of the sharedName attribute
+   * @param container The value of the container attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of Iterator
    */
   @Endpoint(
@@ -92,4 +96,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<Iterator> {
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new Iterator(op), op, Arrays.asList("shared_name", "container", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      sharedName = op.attributes().getAttrString("shared_name");
+      container = op.attributes().getAttrString("container");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java
index 8d05ee3163c..26695a9c0bf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -53,8 +56,8 @@ private IteratorFromStringHandle(Operation operation) {
    * Factory method to create a class wrapping a new IteratorFromStringHandleV2 operation.
    *
    * @param scope current scope
-   * @param stringHandle the stringHandle value
-   * @param outputTypes the value of the outputTypes property
+   * @param stringHandle The stringHandle value
+   * @param outputTypes The value of the outputTypes attribute
    * @param options carries optional attribute values
    * @return a new instance of IteratorFromStringHandle
    */
@@ -96,7 +99,7 @@ public static Options outputShapes(List<Shape> outputShapes) {
    * @param outputShapes the outputShapes option
    * @return this Options instance.
    */
-  public static Options outputShapes(Shape[] outputShapes) {
+  public static Options outputShapes(Shape... outputShapes) {
     return new Options().outputShapes(outputShapes);
   }
 
@@ -146,4 +149,29 @@ public Options outputShapes(Shape... outputShapes) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<IteratorFromStringHandle> {
+    /**
+     * The stringHandle input
+     */
+    public final Operand<TString> stringHandle;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new IteratorFromStringHandle(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      stringHandle = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetDevice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetDevice.java
index d772a2e5066..922c13d28f2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetDevice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetDevice.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -48,7 +51,7 @@ private IteratorGetDevice(Operation operation) {
    * Factory method to create a class wrapping a new IteratorGetDevice operation.
    *
    * @param scope current scope
-   * @param resource the resource value
+   * @param resource The resource value
    * @return a new instance of IteratorGetDevice
    */
   @Endpoint(
@@ -73,4 +76,17 @@ public Output<TString> device() {
   public Output<TString> asOutput() {
     return device;
   }
+
+  public static class Inputs extends RawOpInputs<IteratorGetDevice> {
+    /**
+     * The resource input
+     */
+    public final Operand<? extends TType> resource;
+
+    public Inputs(GraphOperation op) {
+      super(new IteratorGetDevice(op), op, Arrays.asList());
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java
index 5ef82bb3a3d..9d48aeb39a5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,9 +62,9 @@ private IteratorGetNext(Operation operation) {
    * Factory method to create a class wrapping a new IteratorGetNext operation.
    *
    * @param scope current scope
-   * @param iterator the iterator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param iterator The iterator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of IteratorGetNext
    */
   @Endpoint(
@@ -94,4 +97,29 @@ public List<Output<?>> components() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) components.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<IteratorGetNext> {
+    /**
+     * The iterator input
+     */
+    public final Operand<? extends TType> iterator;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new IteratorGetNext(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      iterator = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java
index 87cd3ef37ea..c679cdbae31 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private IteratorGetNextAsOptional(Operation operation) {
    * Factory method to create a class wrapping a new IteratorGetNextAsOptional operation.
    *
    * @param scope current scope
-   * @param iterator the iterator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param iterator The iterator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of IteratorGetNextAsOptional
    */
   @Endpoint(
@@ -90,4 +94,29 @@ public Output<? extends TType> optional() {
   public Output<TType> asOutput() {
     return (Output<TType>) optional;
   }
+
+  public static class Inputs extends RawOpInputs<IteratorGetNextAsOptional> {
+    /**
+     * The iterator input
+     */
+    public final Operand<? extends TType> iterator;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new IteratorGetNextAsOptional(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      iterator = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java
index 018f28dead3..1de3a7c0131 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -63,9 +66,9 @@ private IteratorGetNextSync(Operation operation) {
    * Factory method to create a class wrapping a new IteratorGetNextSync operation.
    *
    * @param scope current scope
-   * @param iterator the iterator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param iterator The iterator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of IteratorGetNextSync
    */
   @Endpoint(
@@ -98,4 +101,29 @@ public List<Output<?>> components() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) components.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<IteratorGetNextSync> {
+    /**
+     * The iterator input
+     */
+    public final Operand<? extends TType> iterator;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new IteratorGetNextSync(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      iterator = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorToStringHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorToStringHandle.java
index 4973206deba..6854c2574c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorToStringHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorToStringHandle.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -78,4 +81,17 @@ public Output<TString> stringHandle() {
   public Output<TString> asOutput() {
     return stringHandle;
   }
+
+  public static class Inputs extends RawOpInputs<IteratorToStringHandle> {
+    /**
+     * A handle to an iterator resource.
+     */
+    public final Operand<? extends TType> resourceHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new IteratorToStringHandle(op), op, Arrays.asList());
+      int inputIndex = 0;
+      resourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java
index cad8616daa3..f65b0c6a2ab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -66,8 +70,8 @@ private LMDBDataset(Operation operation) {
    * @param scope current scope
    * @param filenames A scalar or a vector containing the name(s) of the binary file(s) to be
    * read.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of LMDBDataset
    */
   @Endpoint(
@@ -100,4 +104,30 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<LMDBDataset> {
+    /**
+     * A scalar or a vector containing the name(s) of the binary file(s) to be
+     * read.
+     */
+    public final Operand<TString> filenames;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new LMDBDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      filenames = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java
index 73170c4fac0..bc8c24e59ff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -56,10 +60,10 @@ private LatencyStatsDataset(Operation operation) {
    * Factory method to create a class wrapping a new LatencyStatsDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param tag the tag value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param tag The tag value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of LatencyStatsDataset
    */
   @Endpoint(
@@ -93,4 +97,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<LatencyStatsDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new LatencyStatsDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java
index f54fcd92daa..b30117b7c13 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -118,4 +122,36 @@ public Options alpha(Float alpha) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LeakyReluGrad<T>> {
+    /**
+     * The backpropagated gradients to the corresponding LeakyRelu operation.
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The features passed as input to the corresponding LeakyRelu operation,
+     * OR the outputs of that operation (both work equivalently).
+     */
+    public final Operand<T> features;
+
+    /**
+     * The alpha attribute
+     */
+    public final float alpha;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LeakyReluGrad<>(op), op, Arrays.asList("alpha", "T"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      features = (Operand<T>) op.input(inputIndex++);
+      alpha = op.attributes().getAttrFloat("alpha");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LegacyParallelInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LegacyParallelInterleaveDataset.java
index cde48b6c8ee..94c8f08e22c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LegacyParallelInterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LegacyParallelInterleaveDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -63,17 +67,17 @@ private LegacyParallelInterleaveDataset(Operation operation) {
    * Factory method to create a class wrapping a new LegacyParallelInterleaveDatasetV2 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param cycleLength the cycleLength value
-   * @param blockLength the blockLength value
-   * @param bufferOutputElements the bufferOutputElements value
-   * @param prefetchInputElements the prefetchInputElements value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param cycleLength The cycleLength value
+   * @param blockLength The blockLength value
+   * @param bufferOutputElements The bufferOutputElements value
+   * @param prefetchInputElements The prefetchInputElements value
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    * {@code other_arguments}, to a Dataset variant that contains elements matching
    * {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of LegacyParallelInterleaveDataset
    */
@@ -155,4 +159,73 @@ public Options deterministic(String deterministic) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LegacyParallelInterleaveDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The cycleLength input
+     */
+    public final Operand<TInt64> cycleLength;
+
+    /**
+     * The blockLength input
+     */
+    public final Operand<TInt64> blockLength;
+
+    /**
+     * The bufferOutputElements input
+     */
+    public final Operand<TInt64> bufferOutputElements;
+
+    /**
+     * The prefetchInputElements input
+     */
+    public final Operand<TInt64> prefetchInputElements;
+
+    /**
+     * The deterministic attribute
+     */
+    public final String deterministic;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new LegacyParallelInterleaveDataset(op), op, Arrays.asList("deterministic", "Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      cycleLength = (Operand<TInt64>) op.input(inputIndex++);
+      blockLength = (Operand<TInt64>) op.input(inputIndex++);
+      bufferOutputElements = (Operand<TInt64>) op.input(inputIndex++);
+      prefetchInputElements = (Operand<TInt64>) op.input(inputIndex++);
+      deterministic = op.attributes().getAttrString("deterministic");
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LoadDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LoadDataset.java
index 0d484822f0c..be67a1a67a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LoadDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LoadDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -57,11 +61,11 @@ private LoadDataset(Operation operation) {
    * Factory method to create a class wrapping a new LoadDataset operation.
    *
    * @param scope current scope
-   * @param path the path value
-   * @param readerFuncOtherArgs the readerFuncOtherArgs value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
-   * @param readerFunc the value of the readerFunc property
+   * @param path The path value
+   * @param readerFuncOtherArgs The readerFuncOtherArgs value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
+   * @param readerFunc The value of the readerFunc attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadDataset
    */
@@ -136,4 +140,49 @@ public Options compression(String compression) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadDataset> {
+    /**
+     * The path input
+     */
+    public final Operand<TString> path;
+
+    /**
+     * The readerFuncOtherArgs input
+     */
+    public final Iterable<Operand<?>> readerFuncOtherArgs;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The compression attribute
+     */
+    public final String compression;
+
+    /**
+     * The TreaderFuncArgs attribute
+     */
+    public final DataType[] TreaderFuncArgs;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadDataset(op), op, Arrays.asList("output_types", "output_shapes", "compression", "Treader_func_args"));
+      int inputIndex = 0;
+      path = (Operand<TString>) op.input(inputIndex++);
+      int readerFuncOtherArgsLength = op.inputListLength("reader_func_other_args");
+      readerFuncOtherArgs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, readerFuncOtherArgsLength));
+      inputIndex += readerFuncOtherArgsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      compression = op.attributes().getAttrString("compression");
+      TreaderFuncArgs = op.attributes().getAttrTypeList("Treader_func_args");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MakeIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MakeIterator.java
index e4a39b2f495..93cca862b96 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MakeIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MakeIterator.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -48,8 +51,8 @@ private MakeIterator(Operation operation) {
    * Factory method to create a class wrapping a new MakeIterator operation.
    *
    * @param scope current scope
-   * @param dataset the dataset value
-   * @param iterator the iterator value
+   * @param dataset The dataset value
+   * @param iterator The iterator value
    * @return a new instance of MakeIterator
    */
   @Endpoint(
@@ -62,4 +65,23 @@ public static MakeIterator create(Scope scope, Operand<? extends TType> dataset,
     opBuilder.addInput(iterator.asOutput());
     return new MakeIterator(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<MakeIterator> {
+    /**
+     * The dataset input
+     */
+    public final Operand<? extends TType> dataset;
+
+    /**
+     * The iterator input
+     */
+    public final Operand<? extends TType> iterator;
+
+    public Inputs(GraphOperation op) {
+      super(new MakeIterator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      dataset = (Operand<? extends TType>) op.input(inputIndex++);
+      iterator = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapAndBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapAndBatchDataset.java
index f45037d548f..b1bbacd6622 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapAndBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapAndBatchDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -74,8 +78,8 @@ private MapAndBatchDataset(Operation operation) {
    * @param dropRemainder A scalar representing whether the last batch should be dropped in case its size
    * is smaller than desired.
    * @param f A function to apply to the outputs of {@code input_dataset}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapAndBatchDataset
    */
@@ -154,4 +158,73 @@ public Options preserveCardinality(Boolean preserveCardinality) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapAndBatchDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A list of tensors, typically values that were captured when building a closure
+     * for {@code f}.
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * A scalar representing the number of elements to accumulate in a
+     * batch. It determines the number of concurrent invocations of {@code f} that process
+     * elements from {@code input_dataset} in parallel.
+     */
+    public final Operand<TInt64> batchSize;
+
+    /**
+     * A scalar representing the maximum number of parallel invocations of the {@code map_fn}
+     * function. Applying the {@code map_fn} on consecutive input elements in parallel has
+     * the potential to improve input pipeline throughput.
+     */
+    public final Operand<TInt64> numParallelCalls;
+
+    /**
+     * A scalar representing whether the last batch should be dropped in case its size
+     * is smaller than desired.
+     */
+    public final Operand<TBool> dropRemainder;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The preserveCardinality attribute
+     */
+    public final boolean preserveCardinality;
+
+    public Inputs(GraphOperation op) {
+      super(new MapAndBatchDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "preserve_cardinality"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      batchSize = (Operand<TInt64>) op.input(inputIndex++);
+      numParallelCalls = (Operand<TInt64>) op.input(inputIndex++);
+      dropRemainder = (Operand<TBool>) op.input(inputIndex++);
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      preserveCardinality = op.attributes().getAttrBool("preserve_cardinality");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java
index 872980cca18..81c569034d3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MapDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -56,11 +60,11 @@ private MapDataset(Operation operation) {
    * Factory method to create a class wrapping a new MapDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapDataset
    */
@@ -161,4 +165,55 @@ public Options preserveCardinality(Boolean preserveCardinality) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The useInterOpParallelism attribute
+     */
+    public final boolean useInterOpParallelism;
+
+    /**
+     * The preserveCardinality attribute
+     */
+    public final boolean preserveCardinality;
+
+    public Inputs(GraphOperation op) {
+      super(new MapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "preserve_cardinality"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      useInterOpParallelism = op.attributes().getAttrBool("use_inter_op_parallelism");
+      preserveCardinality = op.attributes().getAttrBool("preserve_cardinality");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MatchingFilesDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MatchingFilesDataset.java
index 8c7d3c019e3..c8d0af517a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MatchingFilesDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MatchingFilesDataset.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -53,7 +56,7 @@ private MatchingFilesDataset(Operation operation) {
    * Factory method to create a class wrapping a new MatchingFilesDataset operation.
    *
    * @param scope current scope
-   * @param patterns the patterns value
+   * @param patterns The patterns value
    * @return a new instance of MatchingFilesDataset
    */
   @Endpoint(
@@ -79,4 +82,17 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<MatchingFilesDataset> {
+    /**
+     * The patterns input
+     */
+    public final Operand<TString> patterns;
+
+    public Inputs(GraphOperation op) {
+      super(new MatchingFilesDataset(op), op, Arrays.asList());
+      int inputIndex = 0;
+      patterns = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java
index d32f1f39ae5..883390d70de 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,10 +60,10 @@ private MaxIntraOpParallelismDataset(Operation operation) {
    * Factory method to create a class wrapping a new MaxIntraOpParallelismDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param maxIntraOpParallelism Identifies the maximum intra-op parallelism to use.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of MaxIntraOpParallelismDataset
    */
   @Endpoint(
@@ -94,4 +98,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<MaxIntraOpParallelismDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * Identifies the maximum intra-op parallelism to use.
+     */
+    public final Operand<TInt64> maxIntraOpParallelism;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxIntraOpParallelismDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      maxIntraOpParallelism = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java
index 0d200d35e3c..b600addbc87 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,8 +61,8 @@ private ModelDataset(Operation operation) {
    *
    * @param scope current scope
    * @param inputDataset A variant tensor representing the input dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ModelDataset
    */
@@ -182,4 +186,47 @@ public Options ramBudget(Long ramBudget) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ModelDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The algorithm attribute
+     */
+    public final long algorithm;
+
+    /**
+     * The cpuBudget attribute
+     */
+    public final long cpuBudget;
+
+    /**
+     * The ramBudget attribute
+     */
+    public final long ramBudget;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ModelDataset(op), op, Arrays.asList("algorithm", "cpu_budget", "ram_budget", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = op.attributes().getAttrInt("algorithm");
+      cpuBudget = op.attributes().getAttrInt("cpu_budget");
+      ramBudget = op.attributes().getAttrInt("ram_budget");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java
index 41b1fe1e662..60589923320 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -96,4 +100,43 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<MultiDeviceIterator> {
+    /**
+     * A list of devices the iterator works across.
+     */
+    public final String[] devices;
+
+    /**
+     * If non-empty, this resource will be shared under the given name
+     * across multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * If non-empty, this resource is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * The type list for the return values.
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The list of shapes being produced.
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new MultiDeviceIterator(op), op, Arrays.asList("devices", "shared_name", "container", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      devices = op.attributes().getAttrStringList("devices");
+      sharedName = op.attributes().getAttrString("shared_name");
+      container = op.attributes().getAttrString("container");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java
index a1c0b1e529b..ce3b30d17f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -96,7 +99,7 @@ public static Options outputShapes(List<Shape> outputShapes) {
    * @param outputShapes The list of shapes being produced.
    * @return this Options instance.
    */
-  public static Options outputShapes(Shape[] outputShapes) {
+  public static Options outputShapes(Shape... outputShapes) {
     return new Options().outputShapes(outputShapes);
   }
 
@@ -146,4 +149,29 @@ public Options outputShapes(Shape... outputShapes) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MultiDeviceIteratorFromStringHandle> {
+    /**
+     * String representing the resource.
+     */
+    public final Operand<TString> stringHandle;
+
+    /**
+     * The type list for the return values.
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The list of shapes being produced.
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new MultiDeviceIteratorFromStringHandle(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      stringHandle = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java
index 5015e405b51..778bf06b10b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -98,4 +101,41 @@ public List<Output<?>> components() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) components.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<MultiDeviceIteratorGetNextFromShard> {
+    /**
+     * A MultiDeviceIterator resource.
+     */
+    public final Operand<? extends TType> multiDeviceIterator;
+
+    /**
+     * Integer representing which shard to fetch data for.
+     */
+    public final Operand<TInt32> shardNum;
+
+    /**
+     * Which incarnation of the MultiDeviceIterator is running.
+     */
+    public final Operand<TInt64> incarnationId;
+
+    /**
+     * The type list for the return values.
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The list of shapes being produced.
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new MultiDeviceIteratorGetNextFromShard(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      multiDeviceIterator = (Operand<? extends TType>) op.input(inputIndex++);
+      shardNum = (Operand<TInt32>) op.input(inputIndex++);
+      incarnationId = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorInit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorInit.java
index aa62b899a44..107b2c1cb5f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorInit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorInit.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -79,4 +82,29 @@ public Output<TInt64> incarnationId() {
   public Output<TInt64> asOutput() {
     return incarnationId;
   }
+
+  public static class Inputs extends RawOpInputs<MultiDeviceIteratorInit> {
+    /**
+     * Dataset to be iterated upon.
+     */
+    public final Operand<? extends TType> dataset;
+
+    /**
+     * A MultiDeviceIteratorResource.
+     */
+    public final Operand<? extends TType> multiDeviceIterator;
+
+    /**
+     * The maximum size of the host side per device buffer to keep.
+     */
+    public final Operand<TInt64> maxBufferSize;
+
+    public Inputs(GraphOperation op) {
+      super(new MultiDeviceIteratorInit(op), op, Arrays.asList());
+      int inputIndex = 0;
+      dataset = (Operand<? extends TType>) op.input(inputIndex++);
+      multiDeviceIterator = (Operand<? extends TType>) op.input(inputIndex++);
+      maxBufferSize = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorToStringHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorToStringHandle.java
index 99f46b8f444..d65385e4f31 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorToStringHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorToStringHandle.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -74,4 +77,17 @@ public Output<TString> stringHandle() {
   public Output<TString> asOutput() {
     return stringHandle;
   }
+
+  public static class Inputs extends RawOpInputs<MultiDeviceIteratorToStringHandle> {
+    /**
+     * A MultiDeviceIterator resource.
+     */
+    public final Operand<? extends TType> multiDeviceIterator;
+
+    public Inputs(GraphOperation op) {
+      super(new MultiDeviceIteratorToStringHandle(op), op, Arrays.asList());
+      int inputIndex = 0;
+      multiDeviceIterator = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java
index ed6ce16777e..a57c2fc3513 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private NonSerializableDataset(Operation operation) {
    * Factory method to create a class wrapping a new NonSerializableDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of NonSerializableDataset
    */
   @Endpoint(
@@ -90,4 +94,29 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<NonSerializableDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new NonSerializableDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OneShotIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OneShotIterator.java
index b37f927dc6d..a2744d8bacb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OneShotIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OneShotIterator.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -74,8 +78,8 @@ private OneShotIterator(Operation operation) {
    * @param scope current scope
    * @param datasetFactory A function of type {@code () -> DT_VARIANT}, where the returned
    * DT_VARIANT is a dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of OneShotIterator
    */
@@ -174,4 +178,35 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OneShotIterator> {
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new OneShotIterator(op), op, Arrays.asList("output_types", "output_shapes", "container", "shared_name"));
+      int inputIndex = 0;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java
index d3f4ddb5a42..17b48b79f36 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -62,8 +65,8 @@ private OptimizeDataset(Operation operation) {
    * @param optimizationsEnabled A {@code tf.string} vector {@code tf.Tensor} identifying user enabled optimizations.
    * @param optimizationsDisabled A {@code tf.string} vector {@code tf.Tensor} identifying user disabled optimizations.
    * @param optimizationsDefault A {@code tf.string} vector {@code tf.Tensor} identifying optimizations by default.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of OptimizeDataset
    */
@@ -115,7 +118,7 @@ public static Options optimizationConfigs(List<String> optimizationConfigs) {
    * @param optimizationConfigs the optimizationConfigs option
    * @return this Options instance.
    */
-  public static Options optimizationConfigs(String[] optimizationConfigs) {
+  public static Options optimizationConfigs(String... optimizationConfigs) {
     return new Options().optimizationConfigs(optimizationConfigs);
   }
 
@@ -165,4 +168,53 @@ public Options optimizationConfigs(String... optimizationConfigs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OptimizeDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A {@code tf.string} vector {@code tf.Tensor} identifying user enabled optimizations.
+     */
+    public final Operand<TString> optimizationsEnabled;
+
+    /**
+     * A {@code tf.string} vector {@code tf.Tensor} identifying user disabled optimizations.
+     */
+    public final Operand<TString> optimizationsDisabled;
+
+    /**
+     * A {@code tf.string} vector {@code tf.Tensor} identifying optimizations by default.
+     */
+    public final Operand<TString> optimizationsDefault;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The optimizationConfigs attribute
+     */
+    public final String[] optimizationConfigs;
+
+    public Inputs(GraphOperation op) {
+      super(new OptimizeDataset(op), op, Arrays.asList("output_types", "output_shapes", "optimization_configs"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      optimizationsEnabled = (Operand<TString>) op.input(inputIndex++);
+      optimizationsDisabled = (Operand<TString>) op.input(inputIndex++);
+      optimizationsDefault = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      optimizationConfigs = op.attributes().getAttrStringList("optimization_configs");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalFromValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalFromValue.java
index dc91514ef43..87d6a090953 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalFromValue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalFromValue.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,7 +57,7 @@ private OptionalFromValue(Operation operation) {
    * Factory method to create a class wrapping a new OptionalFromValue operation.
    *
    * @param scope current scope
-   * @param components the components value
+   * @param components The components value
    * @return a new instance of OptionalFromValue
    */
   @Endpoint(
@@ -79,4 +83,25 @@ public Output<? extends TType> optional() {
   public Output<TType> asOutput() {
     return (Output<TType>) optional;
   }
+
+  public static class Inputs extends RawOpInputs<OptionalFromValue> {
+    /**
+     * The components input
+     */
+    public final Iterable<Operand<?>> components;
+
+    /**
+     * The ToutputTypes attribute
+     */
+    public final DataType[] ToutputTypes;
+
+    public Inputs(GraphOperation op) {
+      super(new OptionalFromValue(op), op, Arrays.asList("Toutput_types"));
+      int inputIndex = 0;
+      int componentsLength = op.inputListLength("components");
+      components = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, componentsLength));
+      inputIndex += componentsLength;
+      ToutputTypes = op.attributes().getAttrTypeList("Toutput_types");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java
index 2ab14866899..aa3320ef50e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,9 +62,9 @@ private OptionalGetValue(Operation operation) {
    * Factory method to create a class wrapping a new OptionalGetValue operation.
    *
    * @param scope current scope
-   * @param optional the optional value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param optional The optional value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of OptionalGetValue
    */
   @Endpoint(
@@ -94,4 +97,29 @@ public List<Output<?>> components() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) components.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<OptionalGetValue> {
+    /**
+     * The optional input
+     */
+    public final Operand<? extends TType> optional;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new OptionalGetValue(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      optional = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalHasValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalHasValue.java
index 73b80f6e5a8..53dac930b5a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalHasValue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalHasValue.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private OptionalHasValue(Operation operation) {
    * Factory method to create a class wrapping a new OptionalHasValue operation.
    *
    * @param scope current scope
-   * @param optional the optional value
+   * @param optional The optional value
    * @return a new instance of OptionalHasValue
    */
   @Endpoint(
@@ -77,4 +80,17 @@ public Output<TBool> hasValue() {
   public Output<TBool> asOutput() {
     return hasValue;
   }
+
+  public static class Inputs extends RawOpInputs<OptionalHasValue> {
+    /**
+     * The optional input
+     */
+    public final Operand<? extends TType> optional;
+
+    public Inputs(GraphOperation op) {
+      super(new OptionalHasValue(op), op, Arrays.asList());
+      int inputIndex = 0;
+      optional = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalNone.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalNone.java
index 8f19d2f0052..f051ca0c79b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalNone.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalNone.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -76,4 +79,11 @@ public Output<? extends TType> optional() {
   public Output<TType> asOutput() {
     return (Output<TType>) optional;
   }
+
+  public static class Inputs extends RawOpInputs<OptionalNone> {
+    public Inputs(GraphOperation op) {
+      super(new OptionalNone(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java
index ed6d4c382b5..c62b67b68c4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,8 +61,8 @@ private OptionsDataset(Operation operation) {
    * @param scope current scope
    * @param inputDataset A variant tensor representing the input dataset.
    * @param serializedOptions A {@code tf.string} scalar {@code tf.Tensor} of serialized {@code tf.data.Options} protocol buffer.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of OptionsDataset
    */
   @Endpoint(
@@ -93,4 +97,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<OptionsDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A `tf.string` scalar `tf.Tensor` of serialized `tf.data.Options` protocol buffer.
+     */
+    public final String serializedOptions;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new OptionsDataset(op), op, Arrays.asList("serialized_options", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      serializedOptions = op.attributes().getAttrString("serialized_options");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PaddedBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PaddedBatchDataset.java
index 9bd23430f4e..fe1e629e8cd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PaddedBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PaddedBatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -57,7 +61,7 @@ private PaddedBatchDataset(Operation operation) {
    * Factory method to create a class wrapping a new PaddedBatchDatasetV2 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param batchSize A scalar representing the number of elements to accumulate in a
    * batch.
    * @param paddedShapes A list of int64 tensors representing the desired padded shapes
@@ -68,7 +72,7 @@ private PaddedBatchDataset(Operation operation) {
    * each of the outputs.
    * @param dropRemainder A scalar representing whether the last batch should be dropped in case its size
    * is smaller than desired.
-   * @param outputShapes the value of the outputShapes property
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of PaddedBatchDataset
    */
@@ -145,4 +149,69 @@ public Options parallelCopy(Boolean parallelCopy) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<PaddedBatchDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements to accumulate in a
+     * batch.
+     */
+    public final Operand<TInt64> batchSize;
+
+    /**
+     * A list of int64 tensors representing the desired padded shapes
+     * of the corresponding output components. These shapes may be partially
+     * specified, using {@code -1} to indicate that a particular dimension should be
+     * padded to the maximum size of all batch elements.
+     */
+    public final Iterable<Operand<TInt64>> paddedShapes;
+
+    /**
+     * A list of scalars containing the padding value to use for
+     * each of the outputs.
+     */
+    public final Iterable<Operand<?>> paddingValues;
+
+    /**
+     * A scalar representing whether the last batch should be dropped in case its size
+     * is smaller than desired.
+     */
+    public final Operand<TBool> dropRemainder;
+
+    /**
+     * The parallelCopy attribute
+     */
+    public final boolean parallelCopy;
+
+    /**
+     * The ToutputTypes attribute
+     */
+    public final DataType[] ToutputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new PaddedBatchDataset(op), op, Arrays.asList("parallel_copy", "Toutput_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      batchSize = (Operand<TInt64>) op.input(inputIndex++);
+      int paddedShapesLength = op.inputListLength("padded_shapes");
+      paddedShapes = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, paddedShapesLength));
+      inputIndex += paddedShapesLength;
+      int paddingValuesLength = op.inputListLength("padding_values");
+      paddingValues = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, paddingValuesLength));
+      inputIndex += paddingValuesLength;
+      dropRemainder = (Operand<TBool>) op.input(inputIndex++);
+      parallelCopy = op.attributes().getAttrBool("parallel_copy");
+      ToutputTypes = op.attributes().getAttrTypeList("Toutput_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelBatchDataset.java
index 9d80c3b91f7..15805d15774 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelBatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -57,12 +61,12 @@ private ParallelBatchDataset(Operation operation) {
    * Factory method to create a class wrapping a new ParallelBatchDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param batchSize the batchSize value
-   * @param numParallelCalls the numParallelCalls value
-   * @param dropRemainder the dropRemainder value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param batchSize The batchSize value
+   * @param numParallelCalls The numParallelCalls value
+   * @param dropRemainder The dropRemainder value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParallelBatchDataset
    */
@@ -164,4 +168,59 @@ public Options deterministic(String deterministic) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ParallelBatchDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The batchSize input
+     */
+    public final Operand<TInt64> batchSize;
+
+    /**
+     * The numParallelCalls input
+     */
+    public final Operand<TInt64> numParallelCalls;
+
+    /**
+     * The dropRemainder input
+     */
+    public final Operand<TBool> dropRemainder;
+
+    /**
+     * The parallelCopy attribute
+     */
+    public final boolean parallelCopy;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The deterministic attribute
+     */
+    public final String deterministic;
+
+    public Inputs(GraphOperation op) {
+      super(new ParallelBatchDataset(op), op, Arrays.asList("parallel_copy", "output_types", "output_shapes", "deterministic"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      batchSize = (Operand<TInt64>) op.input(inputIndex++);
+      numParallelCalls = (Operand<TInt64>) op.input(inputIndex++);
+      dropRemainder = (Operand<TBool>) op.input(inputIndex++);
+      parallelCopy = op.attributes().getAttrBool("parallel_copy");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      deterministic = op.attributes().getAttrString("deterministic");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java
index 07ac0e6f59a..c5e17ed7388 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -86,8 +90,8 @@ private ParallelInterleaveDataset(Operation operation) {
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    * {@code other_arguments}, to a Dataset variant that contains elements matching
    * {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParallelInterleaveDataset
    */
@@ -177,4 +181,91 @@ public Options deterministic(String deterministic) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ParallelInterleaveDataset> {
+    /**
+     * Dataset that produces a stream of arguments for the function {@code f}.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * Additional arguments to pass to {@code f} beyond those produced by {@code input_dataset}.
+     * Evaluated once when the dataset is instantiated.
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * Number of datasets (each created by applying {@code f} to the elements of
+     * {@code input_dataset}) among which the {@code ParallelInterleaveDatasetV2} will cycle in a
+     * round-robin fashion.
+     */
+    public final Operand<TInt64> cycleLength;
+
+    /**
+     * Number of elements at a time to produce from each interleaved invocation of a
+     * dataset returned by {@code f}.
+     */
+    public final Operand<TInt64> blockLength;
+
+    /**
+     * The number of elements each iterator being interleaved should buffer (similar
+     * to the {@code .prefetch()} transformation for each interleaved iterator).
+     */
+    public final Operand<TInt64> bufferOutputElements;
+
+    /**
+     * Determines the number of iterators to prefetch, allowing buffers to warm up and
+     * data to be pre-fetched without blocking the main thread.
+     */
+    public final Operand<TInt64> prefetchInputElements;
+
+    /**
+     * Determines the number of threads that should be used for fetching data from
+     * input datasets in parallel. The Python API {@code tf.data.experimental.AUTOTUNE}
+     * constant can be used to indicate that the level of parallelism should be autotuned.
+     */
+    public final Operand<TInt64> numParallelCalls;
+
+    /**
+     * A string indicating the op-level determinism to use. Deterministic controls
+     * whether the interleave is allowed to return elements out of order if the next
+     * element to be returned isn't available, but a later element is. Options are
+     * "true", "false", and "default". "default" indicates that determinism should be
+     * decided by the `experimental_deterministic` parameter of `tf.data.Options`.
+     */
+    public final String deterministic;
+
+    /**
+     * Types of the elements of `other_arguments`.
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ParallelInterleaveDataset(op), op, Arrays.asList("deterministic", "Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      cycleLength = (Operand<TInt64>) op.input(inputIndex++);
+      blockLength = (Operand<TInt64>) op.input(inputIndex++);
+      bufferOutputElements = (Operand<TInt64>) op.input(inputIndex++);
+      prefetchInputElements = (Operand<TInt64>) op.input(inputIndex++);
+      numParallelCalls = (Operand<TInt64>) op.input(inputIndex++);
+      deterministic = op.attributes().getAttrString("deterministic");
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java
index e954f33b8ec..455c6b600e9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelMapDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -59,13 +63,13 @@ private ParallelMapDataset(Operation operation) {
    * Factory method to create a class wrapping a new ParallelMapDatasetV2 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
    * @param numParallelCalls The number of concurrent invocations of {@code f} that process
    * elements from {@code input_dataset} in parallel.
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParallelMapDataset
    */
@@ -193,4 +197,68 @@ public Options preserveCardinality(Boolean preserveCardinality) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ParallelMapDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The number of concurrent invocations of {@code f} that process
+     * elements from {@code input_dataset} in parallel.
+     */
+    public final Operand<TInt64> numParallelCalls;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The useInterOpParallelism attribute
+     */
+    public final boolean useInterOpParallelism;
+
+    /**
+     * The deterministic attribute
+     */
+    public final String deterministic;
+
+    /**
+     * The preserveCardinality attribute
+     */
+    public final boolean preserveCardinality;
+
+    public Inputs(GraphOperation op) {
+      super(new ParallelMapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "deterministic", "preserve_cardinality"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      numParallelCalls = (Operand<TInt64>) op.input(inputIndex++);
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      useInterOpParallelism = op.attributes().getAttrBool("use_inter_op_parallelism");
+      deterministic = op.attributes().getAttrString("deterministic");
+      preserveCardinality = op.attributes().getAttrBool("preserve_cardinality");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java
index 16163f215e3..501716524f8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -58,8 +61,8 @@ private ParseExampleDataset(Operation operation) {
    * Factory method to create a class wrapping a new ParseExampleDatasetV2 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param numParallelCalls the numParallelCalls value
+   * @param inputDataset The inputDataset value
+   * @param numParallelCalls The numParallelCalls value
    * @param denseDefaults A dict mapping string keys to {@code Tensor}s.
    * The keys of the dict must match the dense_keys of the feature.
    * @param sparseKeys A list of string keys in the examples features.
@@ -80,8 +83,8 @@ private ParseExampleDataset(Operation operation) {
    * given feature along this dimension.
    * @param outputTypes The type list for the return values.
    * @param outputShapes The list of shapes being produced.
-   * @param raggedValueTypes the value of the raggedValueTypes property
-   * @param raggedSplitTypes the value of the raggedSplitTypes property
+   * @param raggedValueTypes The value of the raggedValueTypes attribute
+   * @param raggedSplitTypes The value of the raggedSplitTypes attribute
    * @param options carries optional attribute values
    * @return a new instance of ParseExampleDataset
    */
@@ -169,7 +172,7 @@ public static Options raggedKeys(List<String> raggedKeys) {
    * @param raggedKeys the raggedKeys option
    * @return this Options instance.
    */
-  public static Options raggedKeys(String[] raggedKeys) {
+  public static Options raggedKeys(String... raggedKeys) {
     return new Options().raggedKeys(raggedKeys);
   }
 
@@ -236,4 +239,116 @@ public Options raggedKeys(String... raggedKeys) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ParseExampleDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The numParallelCalls input
+     */
+    public final Operand<TInt64> numParallelCalls;
+
+    /**
+     * A dict mapping string keys to {@code Tensor}s.
+     * The keys of the dict must match the dense_keys of the feature.
+     */
+    public final Iterable<Operand<?>> denseDefaults;
+
+    /**
+     * A list of string keys in the examples features.
+     * The results for these keys will be returned as `SparseTensor` objects.
+     */
+    public final String[] sparseKeys;
+
+    /**
+     * A list of Ndense string Tensors (scalars).
+     * The keys expected in the Examples features associated with dense values.
+     */
+    public final String[] denseKeys;
+
+    /**
+     * A list of `DTypes` of the same length as `sparse_keys`.
+     * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
+     * and `tf.string` (`BytesList`) are supported.
+     */
+    public final DataType[] sparseTypes;
+
+    /**
+     * A list of DTypes of the same length as `dense_keys`.
+     * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
+     * and `tf.string` (`BytesList`) are supported.
+     */
+    public final DataType[] Tdense;
+
+    /**
+     * List of tuples with the same length as `dense_keys`.
+     * The shape of the data for each dense feature referenced by `dense_keys`.
+     * Required for any input tensors identified by `dense_keys`.  Must be
+     * either fully defined, or may contain an unknown first dimension.
+     * An unknown first dimension means the feature is treated as having
+     * a variable number of blocks, and the output shape along this dimension
+     * is considered unknown at graph build time.  Padding is applied for
+     * minibatch elements smaller than the maximum number of blocks for the
+     * given feature along this dimension.
+     */
+    public final Shape[] denseShapes;
+
+    /**
+     * The type list for the return values.
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The list of shapes being produced.
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * A string indicating the op-level determinism to use. Deterministic controls
+     * whether the dataset is allowed to return elements out of order if the next
+     * element to be returned isn't available, but a later element is. Options are
+     * "true", "false", and "default". "default" indicates that determinism should be
+     * decided by the `experimental_deterministic` parameter of `tf.data.Options`.
+     */
+    public final String deterministic;
+
+    /**
+     * The raggedKeys attribute
+     */
+    public final String[] raggedKeys;
+
+    /**
+     * The raggedValueTypes attribute
+     */
+    public final DataType[] raggedValueTypes;
+
+    /**
+     * The raggedSplitTypes attribute
+     */
+    public final DataType[] raggedSplitTypes;
+
+    public Inputs(GraphOperation op) {
+      super(new ParseExampleDataset(op), op, Arrays.asList("sparse_keys", "dense_keys", "sparse_types", "Tdense", "dense_shapes", "output_types", "output_shapes", "deterministic", "ragged_keys", "ragged_value_types", "ragged_split_types"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numParallelCalls = (Operand<TInt64>) op.input(inputIndex++);
+      int denseDefaultsLength = op.inputListLength("dense_defaults");
+      denseDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, denseDefaultsLength));
+      inputIndex += denseDefaultsLength;
+      sparseKeys = op.attributes().getAttrStringList("sparse_keys");
+      denseKeys = op.attributes().getAttrStringList("dense_keys");
+      sparseTypes = op.attributes().getAttrTypeList("sparse_types");
+      Tdense = op.attributes().getAttrTypeList("Tdense");
+      denseShapes = op.attributes().getAttrShapeList("dense_shapes");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      deterministic = op.attributes().getAttrString("deterministic");
+      raggedKeys = op.attributes().getAttrStringList("ragged_keys");
+      raggedValueTypes = op.attributes().getAttrTypeList("ragged_value_types");
+      raggedSplitTypes = op.attributes().getAttrTypeList("ragged_split_types");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java
index e175f440778..b27ce7b56ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,11 +60,11 @@ private PrefetchDataset(Operation operation) {
    * Factory method to create a class wrapping a new PrefetchDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param bufferSize The maximum number of elements to buffer in an iterator over
    * this dataset.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of PrefetchDataset
    */
@@ -186,4 +190,54 @@ public Options bufferSizeMin(Long bufferSizeMin) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<PrefetchDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The maximum number of elements to buffer in an iterator over
+     * this dataset.
+     */
+    public final Operand<TInt64> bufferSize;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The slackPeriod attribute
+     */
+    public final long slackPeriod;
+
+    /**
+     * The legacyAutotune attribute
+     */
+    public final boolean legacyAutotune;
+
+    /**
+     * The bufferSizeMin attribute
+     */
+    public final long bufferSizeMin;
+
+    public Inputs(GraphOperation op) {
+      super(new PrefetchDataset(op), op, Arrays.asList("output_types", "output_shapes", "slack_period", "legacy_autotune", "buffer_size_min"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      slackPeriod = op.attributes().getAttrInt("slack_period");
+      legacyAutotune = op.attributes().getAttrBool("legacy_autotune");
+      bufferSizeMin = op.attributes().getAttrInt("buffer_size_min");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java
index 73e293fa5f7..637436c7385 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,10 +60,10 @@ private PrivateThreadPoolDataset(Operation operation) {
    * Factory method to create a class wrapping a new PrivateThreadPoolDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param numThreads Identifies the number of threads to use for the private threadpool.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of PrivateThreadPoolDataset
    */
   @Endpoint(
@@ -94,4 +98,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<PrivateThreadPoolDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * Identifies the number of threads to use for the private threadpool.
+     */
+    public final Operand<TInt64> numThreads;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new PrivateThreadPoolDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numThreads = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java
index 3d88d88c4e6..c02dc5045d1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -68,8 +72,8 @@ private RandomDataset(Operation operation) {
    * seed2 is set to be non-zero, the random number generator is seeded
    * by the given seed.  Otherwise, a random seed is used.
    * @param seed2 A second scalar seed to avoid seed collision.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RandomDataset
    */
   @Endpoint(
@@ -103,4 +107,37 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<RandomDataset> {
+    /**
+     * A scalar seed for the random number generator. If either seed or
+     * seed2 is set to be non-zero, the random number generator is seeded
+     * by the given seed.  Otherwise, a random seed is used.
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * A second scalar seed to avoid seed collision.
+     */
+    public final Operand<TInt64> seed2;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      seed2 = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java
index ae0e82544c3..a77dbc0faa1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -59,8 +63,8 @@ private RangeDataset(Operation operation) {
    * @param start corresponds to start in python's xrange().
    * @param stop corresponds to stop in python's xrange().
    * @param step corresponds to step in python's xrange().
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RangeDataset
    */
   @Endpoint(
@@ -95,4 +99,41 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<RangeDataset> {
+    /**
+     * corresponds to start in python's xrange().
+     */
+    public final Operand<TInt64> start;
+
+    /**
+     * corresponds to stop in python's xrange().
+     */
+    public final Operand<TInt64> stop;
+
+    /**
+     * corresponds to step in python's xrange().
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new RangeDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      start = (Operand<TInt64>) op.input(inputIndex++);
+      stop = (Operand<TInt64>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDatasetV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDatasetV2.java
index 1028ca5a6f4..f2f29dfa889 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDatasetV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDatasetV2.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -62,9 +66,9 @@ private RebatchDatasetV2(Operation operation) {
    * @param inputDataset A variant tensor representing the input dataset.
    * @param batchSizes A vector of integers representing the size of batches to produce. These values
    * are cycled through in order.
-   * @param dropRemainder the dropRemainder value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param dropRemainder The dropRemainder value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RebatchDatasetV2
    */
   @Endpoint(
@@ -100,4 +104,42 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<RebatchDatasetV2> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A vector of integers representing the size of batches to produce. These values
+     * are cycled through in order.
+     */
+    public final Operand<TInt64> batchSizes;
+
+    /**
+     * The dropRemainder input
+     */
+    public final Operand<TBool> dropRemainder;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new RebatchDatasetV2(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      batchSizes = (Operand<TInt64>) op.input(inputIndex++);
+      dropRemainder = (Operand<TBool>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ReduceDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ReduceDataset.java
index 1304c04223c..5c5933a4ecc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ReduceDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ReduceDataset.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,9 +29,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -63,12 +66,12 @@ private ReduceDataset(Operation operation) {
    * @param inputDataset A variant tensor representing the input dataset.
    * @param initialState A nested structure of tensors, representing the initial state of the
    * transformation.
-   * @param otherArguments the otherArguments value
+   * @param otherArguments The otherArguments value
    * @param f A function that maps {@code (old_state, input_element)} to {@code new_state}. It must take
    * two arguments and return a nested structures of tensors. The structure of
    * {@code new_state} must match the structure of {@code initial_state}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ReduceDataset
    */
@@ -144,4 +147,64 @@ public Options useInterOpParallelism(Boolean useInterOpParallelism) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ReduceDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A nested structure of tensors, representing the initial state of the
+     * transformation.
+     */
+    public final Iterable<Operand<?>> initialState;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Tstate attribute
+     */
+    public final DataType[] Tstate;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The useInterOpParallelism attribute
+     */
+    public final boolean useInterOpParallelism;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceDataset(op), op, Arrays.asList("Tstate", "Targuments", "output_types", "output_shapes", "use_inter_op_parallelism"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int initialStateLength = op.inputListLength("initial_state");
+      initialState = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, initialStateLength));
+      inputIndex += initialStateLength;
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Tstate = op.attributes().getAttrTypeList("Tstate");
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      useInterOpParallelism = op.attributes().getAttrBool("use_inter_op_parallelism");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RegisterDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RegisterDataset.java
index d06a4615c20..faad87061c8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RegisterDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RegisterDataset.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -53,10 +56,10 @@ private RegisterDataset(Operation operation) {
    * Factory method to create a class wrapping a new RegisterDataset operation.
    *
    * @param scope current scope
-   * @param dataset the dataset value
-   * @param address the address value
-   * @param protocol the protocol value
-   * @param externalStatePolicy the value of the externalStatePolicy property
+   * @param dataset The dataset value
+   * @param address The address value
+   * @param protocol The protocol value
+   * @param externalStatePolicy The value of the externalStatePolicy attribute
    * @return a new instance of RegisterDataset
    */
   @Endpoint(
@@ -85,4 +88,35 @@ public Output<TInt64> datasetId() {
   public Output<TInt64> asOutput() {
     return datasetId;
   }
+
+  public static class Inputs extends RawOpInputs<RegisterDataset> {
+    /**
+     * The dataset input
+     */
+    public final Operand<? extends TType> dataset;
+
+    /**
+     * The address input
+     */
+    public final Operand<TString> address;
+
+    /**
+     * The protocol input
+     */
+    public final Operand<TString> protocol;
+
+    /**
+     * The externalStatePolicy attribute
+     */
+    public final long externalStatePolicy;
+
+    public Inputs(GraphOperation op) {
+      super(new RegisterDataset(op), op, Arrays.asList("external_state_policy"));
+      int inputIndex = 0;
+      dataset = (Operand<? extends TType>) op.input(inputIndex++);
+      address = (Operand<TString>) op.input(inputIndex++);
+      protocol = (Operand<TString>) op.input(inputIndex++);
+      externalStatePolicy = op.attributes().getAttrInt("external_state_policy");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java
index 0aa7b1e0c9d..be3bf8d47fe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,11 +60,11 @@ private RepeatDataset(Operation operation) {
    * Factory method to create a class wrapping a new RepeatDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param count A scalar representing the number of times that {@code input_dataset} should
    * be repeated. A value of {@code -1} indicates that it should be repeated infinitely.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RepeatDataset
    */
   @Endpoint(
@@ -94,4 +98,36 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<RepeatDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of times that {@code input_dataset} should
+     * be repeated. A value of {@code -1} indicates that it should be repeated infinitely.
+     */
+    public final Operand<TInt64> count;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new RepeatDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      count = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java
index af6c4f4bfaa..f114ab2c440 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -62,13 +66,13 @@ private SamplingDataset(Operation operation) {
    * Factory method to create a class wrapping a new SamplingDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param rate A scalar representing the sample rate. Each element of {@code input_dataset} is
    * retained with this probability, independent of all other elements.
    * @param seed A scalar representing seed of random number generator.
    * @param seed2 A scalar representing seed2 of random number generator.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SamplingDataset
    */
   @Endpoint(
@@ -105,4 +109,48 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SamplingDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the sample rate. Each element of {@code input_dataset} is
+     * retained with this probability, independent of all other elements.
+     */
+    public final Operand<TFloat32> rate;
+
+    /**
+     * A scalar representing seed of random number generator.
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * A scalar representing seed2 of random number generator.
+     */
+    public final Operand<TInt64> seed2;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SamplingDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      rate = (Operand<TFloat32>) op.input(inputIndex++);
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      seed2 = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SaveDataset.java
index c034b1bcde2..b74ce0f5c33 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SaveDataset.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -49,10 +53,10 @@ private SaveDataset(Operation operation) {
    * Factory method to create a class wrapping a new SaveDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param path the path value
-   * @param shardFuncOtherArgs the shardFuncOtherArgs value
-   * @param shardFunc the value of the shardFunc property
+   * @param inputDataset The inputDataset value
+   * @param path The path value
+   * @param shardFuncOtherArgs The shardFuncOtherArgs value
+   * @param shardFunc The value of the shardFunc attribute
    * @param options carries optional attribute values
    * @return a new instance of SaveDataset
    */
@@ -133,4 +137,49 @@ public Options useShardFunc(Boolean useShardFunc) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SaveDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The path input
+     */
+    public final Operand<TString> path;
+
+    /**
+     * The shardFuncOtherArgs input
+     */
+    public final Iterable<Operand<?>> shardFuncOtherArgs;
+
+    /**
+     * The compression attribute
+     */
+    public final String compression;
+
+    /**
+     * The useShardFunc attribute
+     */
+    public final boolean useShardFunc;
+
+    /**
+     * The TshardFuncArgs attribute
+     */
+    public final DataType[] TshardFuncArgs;
+
+    public Inputs(GraphOperation op) {
+      super(new SaveDataset(op), op, Arrays.asList("compression", "use_shard_func", "Tshard_func_args"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      path = (Operand<TString>) op.input(inputIndex++);
+      int shardFuncOtherArgsLength = op.inputListLength("shard_func_other_args");
+      shardFuncOtherArgs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, shardFuncOtherArgsLength));
+      inputIndex += shardFuncOtherArgsLength;
+      compression = op.attributes().getAttrString("compression");
+      useShardFunc = op.attributes().getAttrBool("use_shard_func");
+      TshardFuncArgs = op.attributes().getAttrTypeList("Tshard_func_args");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ScanDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ScanDataset.java
index 23b1f1a213a..3507f938ad7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ScanDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ScanDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -56,12 +60,12 @@ private ScanDataset(Operation operation) {
    * Factory method to create a class wrapping a new ScanDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param initialState the initialState value
-   * @param otherArguments the otherArguments value
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param initialState The initialState value
+   * @param otherArguments The otherArguments value
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ScanDataset
    */
@@ -163,4 +167,69 @@ public Options useDefaultDevice(Boolean useDefaultDevice) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ScanDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The initialState input
+     */
+    public final Iterable<Operand<?>> initialState;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Tstate attribute
+     */
+    public final DataType[] Tstate;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The preserveCardinality attribute
+     */
+    public final boolean preserveCardinality;
+
+    /**
+     * The useDefaultDevice attribute
+     */
+    public final boolean useDefaultDevice;
+
+    public Inputs(GraphOperation op) {
+      super(new ScanDataset(op), op, Arrays.asList("Tstate", "Targuments", "output_types", "output_shapes", "preserve_cardinality", "use_default_device"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int initialStateLength = op.inputListLength("initial_state");
+      initialState = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, initialStateLength));
+      inputIndex += initialStateLength;
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Tstate = op.attributes().getAttrTypeList("Tstate");
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      preserveCardinality = op.attributes().getAttrBool("preserve_cardinality");
+      useDefaultDevice = op.attributes().getAttrBool("use_default_device");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SerializeIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SerializeIterator.java
index 23849f93b36..9afe58663a0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SerializeIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SerializeIterator.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -119,4 +122,23 @@ public Options externalStatePolicy(Long externalStatePolicy) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SerializeIterator> {
+    /**
+     * A handle to an iterator resource.
+     */
+    public final Operand<? extends TType> resourceHandle;
+
+    /**
+     * The externalStatePolicy attribute
+     */
+    public final long externalStatePolicy;
+
+    public Inputs(GraphOperation op) {
+      super(new SerializeIterator(op), op, Arrays.asList("external_state_policy"));
+      int inputIndex = 0;
+      resourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      externalStatePolicy = op.attributes().getAttrInt("external_state_policy");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java
index 96f5356c838..7a3fbe5988e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -56,12 +60,12 @@ private SetStatsAggregatorDataset(Operation operation) {
    * Factory method to create a class wrapping a new SetStatsAggregatorDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param statsAggregator the statsAggregator value
-   * @param tag the tag value
-   * @param counterPrefix the counterPrefix value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param statsAggregator The statsAggregator value
+   * @param tag The tag value
+   * @param counterPrefix The counterPrefix value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SetStatsAggregatorDataset
    */
   @Endpoint(
@@ -99,4 +103,47 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SetStatsAggregatorDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The statsAggregator input
+     */
+    public final Operand<? extends TType> statsAggregator;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The counterPrefix input
+     */
+    public final Operand<TString> counterPrefix;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SetStatsAggregatorDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      statsAggregator = (Operand<? extends TType>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      counterPrefix = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java
index 981cbe60944..e380b54d962 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,11 +60,11 @@ private ShardDataset(Operation operation) {
    * Factory method to create a class wrapping a new ShardDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param numShards An integer representing the number of shards operating in parallel.
    * @param index An integer representing the current worker index.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ShardDataset
    */
@@ -135,4 +139,47 @@ public Options requireNonEmpty(Boolean requireNonEmpty) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ShardDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * An integer representing the number of shards operating in parallel.
+     */
+    public final Operand<TInt64> numShards;
+
+    /**
+     * An integer representing the current worker index.
+     */
+    public final Operand<TInt64> index;
+
+    /**
+     * The requireNonEmpty attribute
+     */
+    public final boolean requireNonEmpty;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ShardDataset(op), op, Arrays.asList("require_non_empty", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numShards = (Operand<TInt64>) op.input(inputIndex++);
+      index = (Operand<TInt64>) op.input(inputIndex++);
+      requireNonEmpty = op.attributes().getAttrBool("require_non_empty");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java
index 72178a21672..47d1782ba34 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,14 +60,14 @@ private ShuffleAndRepeatDataset(Operation operation) {
    * Factory method to create a class wrapping a new ShuffleAndRepeatDatasetV2 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param bufferSize the bufferSize value
-   * @param seed the seed value
-   * @param seed2 the seed2 value
-   * @param count the count value
-   * @param seedGenerator the seedGenerator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param bufferSize The bufferSize value
+   * @param seed The seed value
+   * @param seed2 The seed2 value
+   * @param count The count value
+   * @param seedGenerator The seedGenerator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ShuffleAndRepeatDataset
    */
@@ -142,4 +146,65 @@ public Options reshuffleEachIteration(Boolean reshuffleEachIteration) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ShuffleAndRepeatDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The bufferSize input
+     */
+    public final Operand<TInt64> bufferSize;
+
+    /**
+     * The seed input
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * The seed2 input
+     */
+    public final Operand<TInt64> seed2;
+
+    /**
+     * The count input
+     */
+    public final Operand<TInt64> count;
+
+    /**
+     * The seedGenerator input
+     */
+    public final Operand<? extends TType> seedGenerator;
+
+    /**
+     * The reshuffleEachIteration attribute
+     */
+    public final boolean reshuffleEachIteration;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ShuffleAndRepeatDataset(op), op, Arrays.asList("reshuffle_each_iteration", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      seed2 = (Operand<TInt64>) op.input(inputIndex++);
+      count = (Operand<TInt64>) op.input(inputIndex++);
+      seedGenerator = (Operand<? extends TType>) op.input(inputIndex++);
+      reshuffleEachIteration = op.attributes().getAttrBool("reshuffle_each_iteration");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java
index 369f892c0da..dc222f3c559 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,13 +60,13 @@ private ShuffleDataset(Operation operation) {
    * Factory method to create a class wrapping a new ShuffleDatasetV3 operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param bufferSize the bufferSize value
-   * @param seed the seed value
-   * @param seed2 the seed2 value
-   * @param seedGenerator the seedGenerator value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param bufferSize The bufferSize value
+   * @param seed The seed value
+   * @param seed2 The seed2 value
+   * @param seedGenerator The seedGenerator value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ShuffleDataset
    */
@@ -140,4 +144,59 @@ public Options reshuffleEachIteration(Boolean reshuffleEachIteration) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ShuffleDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The bufferSize input
+     */
+    public final Operand<TInt64> bufferSize;
+
+    /**
+     * The seed input
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * The seed2 input
+     */
+    public final Operand<TInt64> seed2;
+
+    /**
+     * The seedGenerator input
+     */
+    public final Operand<? extends TType> seedGenerator;
+
+    /**
+     * The reshuffleEachIteration attribute
+     */
+    public final boolean reshuffleEachIteration;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ShuffleDataset(op), op, Arrays.asList("reshuffle_each_iteration", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      seed2 = (Operand<TInt64>) op.input(inputIndex++);
+      seedGenerator = (Operand<? extends TType>) op.input(inputIndex++);
+      reshuffleEachIteration = op.attributes().getAttrBool("reshuffle_each_iteration");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java
index 5b219586c7e..366b29b17d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,11 +60,11 @@ private SkipDataset(Operation operation) {
    * Factory method to create a class wrapping a new SkipDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param count A scalar representing the number of elements from the {@code input_dataset}
    * that should be skipped.  If count is -1, skips everything.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SkipDataset
    */
   @Endpoint(
@@ -94,4 +98,36 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SkipDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements from the {@code input_dataset}
+     * that should be skipped.  If count is -1, skips everything.
+     */
+    public final Operand<TInt64> count;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SkipDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      count = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java
index 86bc79865a8..9d687853a45 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,10 +60,10 @@ private SleepDataset(Operation operation) {
    * Factory method to create a class wrapping a new SleepDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param sleepMicroseconds the sleepMicroseconds value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param sleepMicroseconds The sleepMicroseconds value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SleepDataset
    */
   @Endpoint(
@@ -94,4 +98,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SleepDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The sleepMicroseconds input
+     */
+    public final Operand<TInt64> sleepMicroseconds;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SleepDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      sleepMicroseconds = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java
index 6c9b47b7a24..4d46ce5a558 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,15 +60,15 @@ private SlidingWindowDataset(Operation operation) {
    * Factory method to create a class wrapping a new SlidingWindowDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param windowSize A scalar representing the number of elements in the
    * sliding window.
    * @param windowShift A scalar representing the steps moving the sliding window
    * forward in one iteration. It must be positive.
    * @param windowStride A scalar representing the stride of the input elements of the sliding window.
    * It must be positive.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SlidingWindowDataset
    */
   @Endpoint(
@@ -101,4 +105,50 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SlidingWindowDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements in the
+     * sliding window.
+     */
+    public final Operand<TInt64> windowSize;
+
+    /**
+     * A scalar representing the steps moving the sliding window
+     * forward in one iteration. It must be positive.
+     */
+    public final Operand<TInt64> windowShift;
+
+    /**
+     * A scalar representing the stride of the input elements of the sliding window.
+     * It must be positive.
+     */
+    public final Operand<TInt64> windowStride;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SlidingWindowDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      windowSize = (Operand<TInt64>) op.input(inputIndex++);
+      windowShift = (Operand<TInt64>) op.input(inputIndex++);
+      windowStride = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDataset.java
index 071a1d9ff0a..45001f8e541 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -63,10 +67,10 @@ private SnapshotDataset(Operation operation) {
    * @param scope current scope
    * @param inputDataset A variant tensor representing the input dataset.
    * @param path The path we should write snapshots to / read snapshots from.
-   * @param readerFuncOtherArgs the readerFuncOtherArgs value
-   * @param shardFuncOtherArgs the shardFuncOtherArgs value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param readerFuncOtherArgs The readerFuncOtherArgs value
+   * @param shardFuncOtherArgs The shardFuncOtherArgs value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param readerFunc Optional. A function to control how to read data from snapshot shards.
    * @param shardFunc Optional. A function to control how to shard data when writing a snapshot.
    * @param options carries optional attribute values
@@ -252,4 +256,93 @@ public Options hash(Long hash) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SnapshotDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The path we should write snapshots to / read snapshots from.
+     */
+    public final Operand<TString> path;
+
+    /**
+     * The readerFuncOtherArgs input
+     */
+    public final Iterable<Operand<?>> readerFuncOtherArgs;
+
+    /**
+     * The shardFuncOtherArgs input
+     */
+    public final Iterable<Operand<?>> shardFuncOtherArgs;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The type of compression to be applied to the saved snapshot files.
+     */
+    public final String compression;
+
+    /**
+     * The readerPrefix attribute
+     */
+    public final String readerPrefix;
+
+    /**
+     * The writerPrefix attribute
+     */
+    public final String writerPrefix;
+
+    /**
+     * The hashValid attribute
+     */
+    public final boolean hashValid;
+
+    /**
+     * The hash attribute
+     */
+    public final long hash;
+
+    /**
+     * The TreaderFuncArgs attribute
+     */
+    public final DataType[] TreaderFuncArgs;
+
+    /**
+     * The TshardFuncArgs attribute
+     */
+    public final DataType[] TshardFuncArgs;
+
+    public Inputs(GraphOperation op) {
+      super(new SnapshotDataset(op), op, Arrays.asList("output_types", "output_shapes", "compression", "reader_prefix", "writer_prefix", "hash_valid", "hash", "Treader_func_args", "Tshard_func_args"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      path = (Operand<TString>) op.input(inputIndex++);
+      int readerFuncOtherArgsLength = op.inputListLength("reader_func_other_args");
+      readerFuncOtherArgs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, readerFuncOtherArgsLength));
+      inputIndex += readerFuncOtherArgsLength;
+      int shardFuncOtherArgsLength = op.inputListLength("shard_func_other_args");
+      shardFuncOtherArgs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, shardFuncOtherArgsLength));
+      inputIndex += shardFuncOtherArgsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      compression = op.attributes().getAttrString("compression");
+      readerPrefix = op.attributes().getAttrString("reader_prefix");
+      writerPrefix = op.attributes().getAttrString("writer_prefix");
+      hashValid = op.attributes().getAttrBool("hash_valid");
+      hash = op.attributes().getAttrInt("hash");
+      TreaderFuncArgs = op.attributes().getAttrTypeList("Treader_func_args");
+      TshardFuncArgs = op.attributes().getAttrTypeList("Tshard_func_args");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDatasetReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDatasetReader.java
index aa33c499b50..0d07f5021ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDatasetReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDatasetReader.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -53,11 +57,11 @@ private SnapshotDatasetReader(Operation operation) {
    * Factory method to create a class wrapping a new SnapshotDatasetReader operation.
    *
    * @param scope current scope
-   * @param shardDir the shardDir value
-   * @param startIndex the startIndex value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
-   * @param version the value of the version property
+   * @param shardDir The shardDir value
+   * @param startIndex The startIndex value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
+   * @param version The value of the version attribute
    * @param options carries optional attribute values
    * @return a new instance of SnapshotDatasetReader
    */
@@ -132,4 +136,47 @@ public Options compression(String compression) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SnapshotDatasetReader> {
+    /**
+     * The shardDir input
+     */
+    public final Operand<TString> shardDir;
+
+    /**
+     * The startIndex input
+     */
+    public final Operand<TInt64> startIndex;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The compression attribute
+     */
+    public final String compression;
+
+    /**
+     * The version attribute
+     */
+    public final long version;
+
+    public Inputs(GraphOperation op) {
+      super(new SnapshotDatasetReader(op), op, Arrays.asList("output_types", "output_shapes", "compression", "version"));
+      int inputIndex = 0;
+      shardDir = (Operand<TString>) op.input(inputIndex++);
+      startIndex = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      compression = op.attributes().getAttrString("compression");
+      version = op.attributes().getAttrInt("version");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotNestedDatasetReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotNestedDatasetReader.java
index db9712a9d14..8fa6cd57f37 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotNestedDatasetReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotNestedDatasetReader.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,9 +55,9 @@ private SnapshotNestedDatasetReader(Operation operation) {
    * Factory method to create a class wrapping a new SnapshotNestedDatasetReader operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputs The inputs value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SnapshotNestedDatasetReader
    */
   @Endpoint(
@@ -87,4 +91,31 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SnapshotNestedDatasetReader> {
+    /**
+     * The inputs input
+     */
+    public final Iterable<Operand<? extends TType>> inputs;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SnapshotNestedDatasetReader(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SparseTensorSliceDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SparseTensorSliceDataset.java
index f9040abd1c4..ba357f78d13 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SparseTensorSliceDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SparseTensorSliceDataset.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -53,9 +57,9 @@ private SparseTensorSliceDataset(Operation operation) {
    * Factory method to create a class wrapping a new SparseTensorSliceDataset operation.
    *
    * @param scope current scope
-   * @param indices the indices value
-   * @param values the values value
-   * @param denseShape the denseShape value
+   * @param indices The indices value
+   * @param values The values value
+   * @param denseShape The denseShape value
    * @return a new instance of SparseTensorSliceDataset
    */
   @Endpoint(
@@ -84,4 +88,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SparseTensorSliceDataset> {
+    /**
+     * The indices input
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * The values input
+     */
+    public final Operand<? extends TType> values;
+
+    /**
+     * The denseShape input
+     */
+    public final Operand<TInt64> denseShape;
+
+    /**
+     * The Tvalues attribute
+     */
+    public final DataType Tvalues;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseTensorSliceDataset(op), op, Arrays.asList("Tvalues"));
+      int inputIndex = 0;
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<? extends TType>) op.input(inputIndex++);
+      denseShape = (Operand<TInt64>) op.input(inputIndex++);
+      Tvalues = op.attributes().getAttrType("Tvalues");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java
index 2b4bb39e58e..7e63d4a1117 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -59,8 +63,8 @@ private SqlDataset(Operation operation) {
    * @param driverName The database type. Currently, the only supported type is 'sqlite'.
    * @param dataSourceName A connection string to connect to the database.
    * @param query A SQL query to execute.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SqlDataset
    */
   @Endpoint(
@@ -96,4 +100,41 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SqlDataset> {
+    /**
+     * The database type. Currently, the only supported type is 'sqlite'.
+     */
+    public final Operand<TString> driverName;
+
+    /**
+     * A connection string to connect to the database.
+     */
+    public final Operand<TString> dataSourceName;
+
+    /**
+     * A SQL query to execute.
+     */
+    public final Operand<TString> query;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SqlDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      driverName = (Operand<TString>) op.input(inputIndex++);
+      dataSourceName = (Operand<TString>) op.input(inputIndex++);
+      query = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorHandle.java
index 0040b1848f8..5e3f2df0d94 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorHandle.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -137,4 +140,23 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StatsAggregatorHandle> {
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new StatsAggregatorHandle(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorSetSummaryWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorSetSummaryWriter.java
index b97c1dd7100..5df60be9489 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorSetSummaryWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/StatsAggregatorSetSummaryWriter.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -42,8 +45,8 @@ private StatsAggregatorSetSummaryWriter(Operation operation) {
    * Factory method to create a class wrapping a new StatsAggregatorSetSummaryWriter operation.
    *
    * @param scope current scope
-   * @param statsAggregator the statsAggregator value
-   * @param summary the summary value
+   * @param statsAggregator The statsAggregator value
+   * @param summary The summary value
    * @return a new instance of StatsAggregatorSetSummaryWriter
    */
   @Endpoint(
@@ -56,4 +59,23 @@ public static StatsAggregatorSetSummaryWriter create(Scope scope,
     opBuilder.addInput(summary.asOutput());
     return new StatsAggregatorSetSummaryWriter(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<StatsAggregatorSetSummaryWriter> {
+    /**
+     * The statsAggregator input
+     */
+    public final Operand<? extends TType> statsAggregator;
+
+    /**
+     * The summary input
+     */
+    public final Operand<? extends TType> summary;
+
+    public Inputs(GraphOperation op) {
+      super(new StatsAggregatorSetSummaryWriter(op), op, Arrays.asList());
+      int inputIndex = 0;
+      statsAggregator = (Operand<? extends TType>) op.input(inputIndex++);
+      summary = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java
index 788dbd06df5..dcd201e8938 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,12 +60,12 @@ private TakeDataset(Operation operation) {
    * Factory method to create a class wrapping a new TakeDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param count A scalar representing the number of elements from the {@code input_dataset}
    * that should be taken. A value of {@code -1} indicates that all of {@code input_dataset}
    * is taken.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TakeDataset
    */
   @Endpoint(
@@ -95,4 +99,37 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TakeDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements from the {@code input_dataset}
+     * that should be taken. A value of {@code -1} indicates that all of {@code input_dataset}
+     * is taken.
+     */
+    public final Operand<TInt64> count;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new TakeDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      count = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeWhileDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeWhileDataset.java
index 1e680f60071..e1fdb783b61 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeWhileDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeWhileDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +28,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -62,12 +66,12 @@ private TakeWhileDataset(Operation operation) {
    * Factory method to create a class wrapping a new TakeWhileDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param otherArguments A list of tensors, typically values that were captured when
    * building a closure for {@code predicate}.
    * @param predicate A function returning a scalar boolean.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TakeWhileDataset
    */
   @Endpoint(
@@ -103,4 +107,44 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TakeWhileDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code predicate}.
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new TakeWhileDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorDataset.java
index b11802e35ba..96406ec3243 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private TensorDataset(Operation operation) {
    * Factory method to create a class wrapping a new TensorDataset operation.
    *
    * @param scope current scope
-   * @param components the components value
-   * @param outputShapes the value of the outputShapes property
+   * @param components The components value
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TensorDataset
    */
   @Endpoint(
@@ -88,4 +92,31 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorDataset> {
+    /**
+     * The components input
+     */
+    public final Iterable<Operand<?>> components;
+
+    /**
+     * The ToutputTypes attribute
+     */
+    public final DataType[] ToutputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorDataset(op), op, Arrays.asList("Toutput_types", "output_shapes"));
+      int inputIndex = 0;
+      int componentsLength = op.inputListLength("components");
+      components = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, componentsLength));
+      inputIndex += componentsLength;
+      ToutputTypes = op.attributes().getAttrTypeList("Toutput_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorSliceDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorSliceDataset.java
index 420694899a5..cffdcc7140b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorSliceDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TensorSliceDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private TensorSliceDataset(Operation operation) {
    * Factory method to create a class wrapping a new TensorSliceDataset operation.
    *
    * @param scope current scope
-   * @param components the components value
-   * @param outputShapes the value of the outputShapes property
+   * @param components The components value
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TensorSliceDataset
    */
   @Endpoint(
@@ -88,4 +92,31 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TensorSliceDataset> {
+    /**
+     * The components input
+     */
+    public final Iterable<Operand<?>> components;
+
+    /**
+     * The ToutputTypes attribute
+     */
+    public final DataType[] ToutputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorSliceDataset(op), op, Arrays.asList("Toutput_types", "output_shapes"));
+      int inputIndex = 0;
+      int componentsLength = op.inputListLength("components");
+      components = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, componentsLength));
+      inputIndex += componentsLength;
+      ToutputTypes = op.attributes().getAttrTypeList("Toutput_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TextLineDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TextLineDataset.java
index b1076784e89..1c64b7a5913 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TextLineDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TextLineDataset.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -87,4 +90,31 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TextLineDataset> {
+    /**
+     * A scalar or a vector containing the name(s) of the file(s) to be
+     * read.
+     */
+    public final Operand<TString> filenames;
+
+    /**
+     * A scalar containing either (i) the empty string (no
+     * compression), (ii) &quot;ZLIB&quot;, or (iii) &quot;GZIP&quot;.
+     */
+    public final Operand<TString> compressionType;
+
+    /**
+     * A scalar containing the number of bytes to buffer.
+     */
+    public final Operand<TInt64> bufferSize;
+
+    public Inputs(GraphOperation op) {
+      super(new TextLineDataset(op), op, Arrays.asList());
+      int inputIndex = 0;
+      filenames = (Operand<TString>) op.input(inputIndex++);
+      compressionType = (Operand<TString>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TfRecordDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TfRecordDataset.java
index 431e2a7db47..87345662d72 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TfRecordDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TfRecordDataset.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -88,4 +91,32 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TfRecordDataset> {
+    /**
+     * A scalar or vector containing the name(s) of the file(s) to be
+     * read.
+     */
+    public final Operand<TString> filenames;
+
+    /**
+     * A scalar containing either (i) the empty string (no
+     * compression), (ii) &quot;ZLIB&quot;, or (iii) &quot;GZIP&quot;.
+     */
+    public final Operand<TString> compressionType;
+
+    /**
+     * A scalar representing the number of bytes to buffer. A value of
+     * 0 means no buffering will be performed.
+     */
+    public final Operand<TInt64> bufferSize;
+
+    public Inputs(GraphOperation op) {
+      super(new TfRecordDataset(op), op, Arrays.asList());
+      int inputIndex = 0;
+      filenames = (Operand<TString>) op.input(inputIndex++);
+      compressionType = (Operand<TString>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java
index 85aec5ab605..c9ff2b00969 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,10 +59,10 @@ private ThreadPoolDataset(Operation operation) {
    * Factory method to create a class wrapping a new ThreadPoolDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param threadPool A resource produced by the ThreadPoolHandle op.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ThreadPoolDataset
    */
   @Endpoint(
@@ -93,4 +97,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ThreadPoolDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A resource produced by the ThreadPoolHandle op.
+     */
+    public final Operand<? extends TType> threadPool;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ThreadPoolDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      threadPool = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolHandle.java
index 2ac0bcfd414..17d867e8b8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolHandle.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -173,4 +176,44 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ThreadPoolHandle> {
+    /**
+     * The number of threads in the thread pool.
+     */
+    public final long numThreads;
+
+    /**
+     * The maximum degree of parallelism to use within operations that execute on this
+     * threadpool.
+     */
+    public final long maxIntraOpParallelism;
+
+    /**
+     * A human-readable name for the threads that may be visible in some
+     * visualizations.
+     * threadpool.
+     */
+    public final String displayName;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new ThreadPoolHandle(op), op, Arrays.asList("num_threads", "max_intra_op_parallelism", "display_name", "container", "shared_name"));
+      int inputIndex = 0;
+      numThreads = op.attributes().getAttrInt("num_threads");
+      maxIntraOpParallelism = op.attributes().getAttrInt("max_intra_op_parallelism");
+      displayName = op.attributes().getAttrString("display_name");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java
index 6d22e02d68f..0abf0d19313 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private UnbatchDataset(Operation operation) {
    * Factory method to create a class wrapping a new UnbatchDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of UnbatchDataset
    */
   @Endpoint(
@@ -90,4 +94,29 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<UnbatchDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new UnbatchDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UncompressElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UncompressElement.java
index 168ea7488f7..a48c055083a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UncompressElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UncompressElement.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +58,9 @@ private UncompressElement(Operation operation) {
    * Factory method to create a class wrapping a new UncompressElement operation.
    *
    * @param scope current scope
-   * @param compressed the compressed value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param compressed The compressed value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of UncompressElement
    */
   @Endpoint(
@@ -90,4 +93,29 @@ public List<Output<?>> components() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) components.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<UncompressElement> {
+    /**
+     * The compressed input
+     */
+    public final Operand<? extends TType> compressed;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new UncompressElement(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      compressed = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java
index f8919551a23..86feaca406d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private UniqueDataset(Operation operation) {
    * Factory method to create a class wrapping a new UniqueDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of UniqueDataset
    */
   @Endpoint(
@@ -90,4 +94,29 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<UniqueDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new UniqueDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnwrapDatasetVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnwrapDatasetVariant.java
index 12ffdcb7f9d..eb4ed977823 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnwrapDatasetVariant.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnwrapDatasetVariant.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private UnwrapDatasetVariant(Operation operation) {
    * Factory method to create a class wrapping a new UnwrapDatasetVariant operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of UnwrapDatasetVariant
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<UnwrapDatasetVariant> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new UnwrapDatasetVariant(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java
index eefcbf8970c..adce99206cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -92,7 +96,7 @@ private WindowDataset(Operation operation) {
    * Factory method to create a class wrapping a new WindowDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param sizeOutput An integer scalar, representing the number of elements
    * of the input dataset to combine into a window. Must be positive.
    * @param shift An integer scalar, representing the number of input elements
@@ -103,8 +107,8 @@ private WindowDataset(Operation operation) {
    * &quot;retain every input element&quot;.
    * @param dropRemainder A Boolean scalar, representing whether the last window should be
    * dropped if its size is smaller than {@code window_size}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of WindowDataset
    */
   @Endpoint(
@@ -143,4 +147,59 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<WindowDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * An integer scalar, representing the number of elements
+     * of the input dataset to combine into a window. Must be positive.
+     */
+    public final Operand<TInt64> sizeOutput;
+
+    /**
+     * An integer scalar, representing the number of input elements
+     * by which the window moves in each iteration.  Defaults to {@code size}.
+     * Must be positive.
+     */
+    public final Operand<TInt64> shift;
+
+    /**
+     * An integer scalar, representing the stride of the input elements
+     * in the sliding window. Must be positive. The default value of 1 means
+     * &quot;retain every input element&quot;.
+     */
+    public final Operand<TInt64> stride;
+
+    /**
+     * A Boolean scalar, representing whether the last window should be
+     * dropped if its size is smaller than {@code window_size}.
+     */
+    public final Operand<TBool> dropRemainder;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new WindowDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt64>) op.input(inputIndex++);
+      shift = (Operand<TInt64>) op.input(inputIndex++);
+      stride = (Operand<TInt64>) op.input(inputIndex++);
+      dropRemainder = (Operand<TBool>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WrapDatasetVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WrapDatasetVariant.java
index dcc6efc6332..5a52404b85e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WrapDatasetVariant.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WrapDatasetVariant.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private WrapDatasetVariant(Operation operation) {
    * Factory method to create a class wrapping a new WrapDatasetVariant operation.
    *
    * @param scope current scope
-   * @param inputHandle the inputHandle value
+   * @param inputHandle The inputHandle value
    * @return a new instance of WrapDatasetVariant
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> outputHandle() {
   public Output<TType> asOutput() {
     return (Output<TType>) outputHandle;
   }
+
+  public static class Inputs extends RawOpInputs<WrapDatasetVariant> {
+    /**
+     * The inputHandle input
+     */
+    public final Operand<? extends TType> inputHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new WrapDatasetVariant(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java
index 46a341e0d33..874b24717a5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,8 +64,8 @@ private ZipDataset(Operation operation) {
    *
    * @param scope current scope
    * @param inputDatasets List of {@code N} variant Tensors representing datasets to be zipped together.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ZipDataset
    */
   @Endpoint(
@@ -94,4 +98,31 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ZipDataset> {
+    /**
+     * List of {@code N} variant Tensors representing datasets to be zipped together.
+     */
+    public final Iterable<Operand<? extends TType>> inputDatasets;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ZipDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      int inputDatasetsLength = op.inputListLength("input_datasets");
+      inputDatasets = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, inputDatasetsLength));
+      inputIndex += inputDatasetsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java
index 1a7829d5102..f2c7acf738f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -52,10 +56,10 @@ private AssertNextDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalAssertNextDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param transformations the transformations value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param transformations The transformations value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of AssertNextDataset
    */
   @Endpoint(
@@ -90,4 +94,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<AssertNextDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The transformations input
+     */
+    public final Operand<TString> transformations;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new AssertNextDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      transformations = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java
index dfbe0d4e060..69e5e5a2ba2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -61,8 +65,8 @@ private AutoShardDataset(Operation operation) {
    * @param inputDataset A variant tensor representing the input dataset.
    * @param numWorkers A scalar representing the number of workers to distribute this dataset across.
    * @param index A scalar representing the index of the current worker out of num_workers.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of AutoShardDataset
    */
@@ -137,4 +141,47 @@ public Options autoShardPolicy(Long autoShardPolicy) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AutoShardDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of workers to distribute this dataset across.
+     */
+    public final Operand<TInt64> numWorkers;
+
+    /**
+     * A scalar representing the index of the current worker out of num_workers.
+     */
+    public final Operand<TInt64> index;
+
+    /**
+     * The autoShardPolicy attribute
+     */
+    public final long autoShardPolicy;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new AutoShardDataset(op), op, Arrays.asList("auto_shard_policy", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numWorkers = (Operand<TInt64>) op.input(inputIndex++);
+      index = (Operand<TInt64>) op.input(inputIndex++);
+      autoShardPolicy = op.attributes().getAttrInt("auto_shard_policy");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java
index 7c77fc6e331..13fb1165700 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -52,10 +56,10 @@ private BytesProducedStatsDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalBytesProducedStatsDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param tag the tag value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param tag The tag value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of BytesProducedStatsDataset
    */
   @Endpoint(
@@ -89,4 +93,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<BytesProducedStatsDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new BytesProducedStatsDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CSVDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CSVDataset.java
index 6a0450a2e61..996e8d5744e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CSVDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CSVDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -54,16 +58,16 @@ private CSVDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalCSVDataset operation.
    *
    * @param scope current scope
-   * @param filenames the filenames value
-   * @param compressionType the compressionType value
-   * @param bufferSize the bufferSize value
-   * @param header the header value
-   * @param fieldDelim the fieldDelim value
-   * @param useQuoteDelim the useQuoteDelim value
-   * @param naValue the naValue value
-   * @param selectCols the selectCols value
-   * @param recordDefaults the recordDefaults value
-   * @param outputShapes the value of the outputShapes property
+   * @param filenames The filenames value
+   * @param compressionType The compressionType value
+   * @param bufferSize The bufferSize value
+   * @param header The header value
+   * @param fieldDelim The fieldDelim value
+   * @param useQuoteDelim The useQuoteDelim value
+   * @param naValue The naValue value
+   * @param selectCols The selectCols value
+   * @param recordDefaults The recordDefaults value
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of CSVDataset
    */
   @Endpoint(
@@ -105,4 +109,79 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<CSVDataset> {
+    /**
+     * The filenames input
+     */
+    public final Operand<TString> filenames;
+
+    /**
+     * The compressionType input
+     */
+    public final Operand<TString> compressionType;
+
+    /**
+     * The bufferSize input
+     */
+    public final Operand<TInt64> bufferSize;
+
+    /**
+     * The header input
+     */
+    public final Operand<TBool> header;
+
+    /**
+     * The fieldDelim input
+     */
+    public final Operand<TString> fieldDelim;
+
+    /**
+     * The useQuoteDelim input
+     */
+    public final Operand<TBool> useQuoteDelim;
+
+    /**
+     * The naValue input
+     */
+    public final Operand<TString> naValue;
+
+    /**
+     * The selectCols input
+     */
+    public final Operand<TInt64> selectCols;
+
+    /**
+     * The recordDefaults input
+     */
+    public final Iterable<Operand<?>> recordDefaults;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new CSVDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      filenames = (Operand<TString>) op.input(inputIndex++);
+      compressionType = (Operand<TString>) op.input(inputIndex++);
+      bufferSize = (Operand<TInt64>) op.input(inputIndex++);
+      header = (Operand<TBool>) op.input(inputIndex++);
+      fieldDelim = (Operand<TString>) op.input(inputIndex++);
+      useQuoteDelim = (Operand<TBool>) op.input(inputIndex++);
+      naValue = (Operand<TString>) op.input(inputIndex++);
+      selectCols = (Operand<TInt64>) op.input(inputIndex++);
+      int recordDefaultsLength = op.inputListLength("record_defaults");
+      recordDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, recordDefaultsLength));
+      inputIndex += recordDefaultsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java
index 53549e4ef72..a6d593bda51 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,10 +55,10 @@ private ChooseFastestDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalChooseFastestDataset operation.
    *
    * @param scope current scope
-   * @param inputDatasets the inputDatasets value
-   * @param numExperiments the value of the numExperiments property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDatasets The inputDatasets value
+   * @param numExperiments The value of the numExperiments attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ChooseFastestDataset
    */
   @Endpoint(
@@ -89,4 +93,37 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ChooseFastestDataset> {
+    /**
+     * The inputDatasets input
+     */
+    public final Iterable<Operand<? extends TType>> inputDatasets;
+
+    /**
+     * The numExperiments attribute
+     */
+    public final long numExperiments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ChooseFastestDataset(op), op, Arrays.asList("num_experiments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      int inputDatasetsLength = op.inputListLength("input_datasets");
+      inputDatasets = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, inputDatasetsLength));
+      inputIndex += inputDatasetsLength;
+      numExperiments = op.attributes().getAttrInt("num_experiments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetCardinality.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetCardinality.java
index 7efa5d34525..d1c6050a755 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetCardinality.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetCardinality.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -75,4 +78,17 @@ public Output<TInt64> cardinality() {
   public Output<TInt64> asOutput() {
     return cardinality;
   }
+
+  public static class Inputs extends RawOpInputs<DatasetCardinality> {
+    /**
+     * A variant tensor representing the dataset to return cardinality for.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    public Inputs(GraphOperation op) {
+      super(new DatasetCardinality(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetToTFRecord.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetToTFRecord.java
index 5a82c0ece34..6ad2bd5ec12 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetToTFRecord.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DatasetToTFRecord.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -60,4 +63,30 @@ public static DatasetToTFRecord create(Scope scope, Operand<? extends TType> inp
     opBuilder.addInput(compressionType.asOutput());
     return new DatasetToTFRecord(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DatasetToTFRecord> {
+    /**
+     * A variant tensor representing the dataset to write.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar string tensor representing the filename to use.
+     */
+    public final Operand<TString> filename;
+
+    /**
+     * A scalar string tensor containing either (i) the empty string (no
+     * compression), (ii) &quot;ZLIB&quot;, or (iii) &quot;GZIP&quot;.
+     */
+    public final Operand<TString> compressionType;
+
+    public Inputs(GraphOperation op) {
+      super(new DatasetToTFRecord(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      filename = (Operand<TString>) op.input(inputIndex++);
+      compressionType = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java
index 3cf5ef82177..ae25c651a41 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -58,8 +62,8 @@ private DenseToSparseBatchDataset(Operation operation) {
    * @param rowShape A vector representing the dense shape of each row in the produced
    * SparseTensor. The shape may be partially specified, using {@code -1} to indicate
    * that a particular dimension should use the maximum size of all batch elements.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of DenseToSparseBatchDataset
    */
   @Endpoint(
@@ -95,4 +99,44 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<DenseToSparseBatchDataset> {
+    /**
+     * A handle to an input dataset. Must have a single component.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements to accumulate in a
+     * batch.
+     */
+    public final Operand<TInt64> batchSize;
+
+    /**
+     * A vector representing the dense shape of each row in the produced
+     * SparseTensor. The shape may be partially specified, using {@code -1} to indicate
+     * that a particular dimension should use the maximum size of all batch elements.
+     */
+    public final Operand<TInt64> rowShape;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new DenseToSparseBatchDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      batchSize = (Operand<TInt64>) op.input(inputIndex++);
+      rowShape = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java
index ac6de0d5dc6..04d9e0bad91 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private DirectedInterleaveDataset(Operation operation) {
    * {@code N} data inputs should produce the next output element.
    * @param dataInputDatasets {@code N} datasets with the same type that will be interleaved according to
    * the values of {@code selector_input_dataset}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of DirectedInterleaveDataset
    */
   @Endpoint(
@@ -92,4 +96,39 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<DirectedInterleaveDataset> {
+    /**
+     * A dataset of scalar {@code DT_INT64} elements that determines which of the
+     * {@code N} data inputs should produce the next output element.
+     */
+    public final Operand<? extends TType> selectorInputDataset;
+
+    /**
+     * {@code N} datasets with the same type that will be interleaved according to
+     * the values of {@code selector_input_dataset}.
+     */
+    public final Iterable<Operand<? extends TType>> dataInputDatasets;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new DirectedInterleaveDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      selectorInputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int dataInputDatasetsLength = op.inputListLength("data_input_datasets");
+      dataInputDatasets = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, dataInputDatasetsLength));
+      inputIndex += dataInputDatasetsLength;
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByReducerDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByReducerDataset.java
index 7529ad3c740..735a080bd78 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByReducerDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByReducerDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -69,8 +73,8 @@ private GroupByReducerDataset(Operation operation) {
    * @param reduceFunc A function mapping the current reducer state and an element of {@code input_dataset},
    * concatenated with {@code reduce_func_other_arguments} to a new reducer state.
    * @param finalizeFunc A function mapping the final reducer state to an output element.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GroupByReducerDataset
    */
   @Endpoint(
@@ -115,4 +119,89 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<GroupByReducerDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code key_func}.
+     */
+    public final Iterable<Operand<?>> keyFuncOtherArguments;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code init_func}.
+     */
+    public final Iterable<Operand<?>> initFuncOtherArguments;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code reduce_func}.
+     */
+    public final Iterable<Operand<?>> reduceFuncOtherArguments;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code finalize_func}.
+     */
+    public final Iterable<Operand<?>> finalizeFuncOtherArguments;
+
+    /**
+     * The TkeyFuncOtherArguments attribute
+     */
+    public final DataType[] TkeyFuncOtherArguments;
+
+    /**
+     * The TinitFuncOtherArguments attribute
+     */
+    public final DataType[] TinitFuncOtherArguments;
+
+    /**
+     * The TreduceFuncOtherArguments attribute
+     */
+    public final DataType[] TreduceFuncOtherArguments;
+
+    /**
+     * The TfinalizeFuncOtherArguments attribute
+     */
+    public final DataType[] TfinalizeFuncOtherArguments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new GroupByReducerDataset(op), op, Arrays.asList("Tkey_func_other_arguments", "Tinit_func_other_arguments", "Treduce_func_other_arguments", "Tfinalize_func_other_arguments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int keyFuncOtherArgumentsLength = op.inputListLength("key_func_other_arguments");
+      keyFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, keyFuncOtherArgumentsLength));
+      inputIndex += keyFuncOtherArgumentsLength;
+      int initFuncOtherArgumentsLength = op.inputListLength("init_func_other_arguments");
+      initFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, initFuncOtherArgumentsLength));
+      inputIndex += initFuncOtherArgumentsLength;
+      int reduceFuncOtherArgumentsLength = op.inputListLength("reduce_func_other_arguments");
+      reduceFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, reduceFuncOtherArgumentsLength));
+      inputIndex += reduceFuncOtherArgumentsLength;
+      int finalizeFuncOtherArgumentsLength = op.inputListLength("finalize_func_other_arguments");
+      finalizeFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, finalizeFuncOtherArgumentsLength));
+      inputIndex += finalizeFuncOtherArgumentsLength;
+      TkeyFuncOtherArguments = op.attributes().getAttrTypeList("Tkey_func_other_arguments");
+      TinitFuncOtherArguments = op.attributes().getAttrTypeList("Tinit_func_other_arguments");
+      TreduceFuncOtherArguments = op.attributes().getAttrTypeList("Treduce_func_other_arguments");
+      TfinalizeFuncOtherArguments = op.attributes().getAttrTypeList("Tfinalize_func_other_arguments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByWindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByWindowDataset.java
index 167a637ae37..7b4bd4e1333 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByWindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/GroupByWindowDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,16 +57,16 @@ private GroupByWindowDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalGroupByWindowDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param keyFuncOtherArguments the keyFuncOtherArguments value
-   * @param reduceFuncOtherArguments the reduceFuncOtherArguments value
-   * @param windowSizeFuncOtherArguments the windowSizeFuncOtherArguments value
+   * @param inputDataset The inputDataset value
+   * @param keyFuncOtherArguments The keyFuncOtherArguments value
+   * @param reduceFuncOtherArguments The reduceFuncOtherArguments value
+   * @param windowSizeFuncOtherArguments The windowSizeFuncOtherArguments value
    * @param keyFunc A function mapping an element of {@code input_dataset}, concatenated
    * with {@code key_func_other_arguments} to a scalar value of type DT_INT64.
-   * @param reduceFunc the value of the reduceFunc property
-   * @param windowSizeFunc the value of the windowSizeFunc property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param reduceFunc The value of the reduceFunc attribute
+   * @param windowSizeFunc The value of the windowSizeFunc attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of GroupByWindowDataset
    */
   @Endpoint(
@@ -104,4 +108,71 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<GroupByWindowDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The keyFuncOtherArguments input
+     */
+    public final Iterable<Operand<?>> keyFuncOtherArguments;
+
+    /**
+     * The reduceFuncOtherArguments input
+     */
+    public final Iterable<Operand<?>> reduceFuncOtherArguments;
+
+    /**
+     * The windowSizeFuncOtherArguments input
+     */
+    public final Iterable<Operand<?>> windowSizeFuncOtherArguments;
+
+    /**
+     * The TkeyFuncOtherArguments attribute
+     */
+    public final DataType[] TkeyFuncOtherArguments;
+
+    /**
+     * The TreduceFuncOtherArguments attribute
+     */
+    public final DataType[] TreduceFuncOtherArguments;
+
+    /**
+     * The TwindowSizeFuncOtherArguments attribute
+     */
+    public final DataType[] TwindowSizeFuncOtherArguments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new GroupByWindowDataset(op), op, Arrays.asList("Tkey_func_other_arguments", "Treduce_func_other_arguments", "Twindow_size_func_other_arguments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int keyFuncOtherArgumentsLength = op.inputListLength("key_func_other_arguments");
+      keyFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, keyFuncOtherArgumentsLength));
+      inputIndex += keyFuncOtherArgumentsLength;
+      int reduceFuncOtherArgumentsLength = op.inputListLength("reduce_func_other_arguments");
+      reduceFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, reduceFuncOtherArgumentsLength));
+      inputIndex += reduceFuncOtherArgumentsLength;
+      int windowSizeFuncOtherArgumentsLength = op.inputListLength("window_size_func_other_arguments");
+      windowSizeFuncOtherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, windowSizeFuncOtherArgumentsLength));
+      inputIndex += windowSizeFuncOtherArgumentsLength;
+      TkeyFuncOtherArguments = op.attributes().getAttrTypeList("Tkey_func_other_arguments");
+      TreduceFuncOtherArguments = op.attributes().getAttrTypeList("Treduce_func_other_arguments");
+      TwindowSizeFuncOtherArguments = op.attributes().getAttrTypeList("Twindow_size_func_other_arguments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java
index f53e17499bc..995d5514c4a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,9 +55,9 @@ private IgnoreErrorsDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalIgnoreErrorsDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of IgnoreErrorsDataset
    */
@@ -125,4 +129,35 @@ public Options logWarning(Boolean logWarning) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<IgnoreErrorsDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The logWarning attribute
+     */
+    public final boolean logWarning;
+
+    public Inputs(GraphOperation op) {
+      super(new IgnoreErrorsDataset(op), op, Arrays.asList("output_types", "output_shapes", "log_warning"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      logWarning = op.attributes().getAttrBool("log_warning");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IteratorGetDevice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IteratorGetDevice.java
index 3058f0435f2..d8232ba0743 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IteratorGetDevice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IteratorGetDevice.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -48,7 +51,7 @@ private IteratorGetDevice(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalIteratorGetDevice operation.
    *
    * @param scope current scope
-   * @param resource the resource value
+   * @param resource The resource value
    * @return a new instance of IteratorGetDevice
    */
   @Endpoint(
@@ -73,4 +76,17 @@ public Output<TString> device() {
   public Output<TString> asOutput() {
     return device;
   }
+
+  public static class Inputs extends RawOpInputs<IteratorGetDevice> {
+    /**
+     * The resource input
+     */
+    public final Operand<? extends TType> resource;
+
+    public Inputs(GraphOperation op) {
+      super(new IteratorGetDevice(op), op, Arrays.asList());
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java
index 9f16e3a897e..5a772ac68c6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -52,10 +56,10 @@ private LatencyStatsDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalLatencyStatsDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param tag the tag value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param tag The tag value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of LatencyStatsDataset
    */
   @Endpoint(
@@ -89,4 +93,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<LatencyStatsDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new LatencyStatsDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java
index 70be4842be2..a19e2f1dc41 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -52,9 +56,9 @@ private LmdbDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalLMDBDataset operation.
    *
    * @param scope current scope
-   * @param filenames the filenames value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param filenames The filenames value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of LmdbDataset
    */
   @Endpoint(
@@ -87,4 +91,29 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<LmdbDataset> {
+    /**
+     * The filenames input
+     */
+    public final Operand<TString> filenames;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new LmdbDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      filenames = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapAndBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapAndBatchDataset.java
index 558a9dcfc73..81165535555 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapAndBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapAndBatchDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -70,8 +74,8 @@ private MapAndBatchDataset(Operation operation) {
    * @param dropRemainder A scalar representing whether the last batch should be dropped in case its size
    * is smaller than desired.
    * @param f A function to apply to the outputs of {@code input_dataset}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapAndBatchDataset
    */
@@ -150,4 +154,73 @@ public Options preserveCardinality(Boolean preserveCardinality) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapAndBatchDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A list of tensors, typically values that were captured when building a closure
+     * for {@code f}.
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * A scalar representing the number of elements to accumulate in a
+     * batch. It determines the number of concurrent invocations of {@code f} that process
+     * elements from {@code input_dataset} in parallel.
+     */
+    public final Operand<TInt64> batchSize;
+
+    /**
+     * A scalar representing the maximum number of parallel invocations of the {@code map_fn}
+     * function. Applying the {@code map_fn} on consecutive input elements in parallel has
+     * the potential to improve input pipeline throughput.
+     */
+    public final Operand<TInt64> numParallelCalls;
+
+    /**
+     * A scalar representing whether the last batch should be dropped in case its size
+     * is smaller than desired.
+     */
+    public final Operand<TBool> dropRemainder;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The preserveCardinality attribute
+     */
+    public final boolean preserveCardinality;
+
+    public Inputs(GraphOperation op) {
+      super(new MapAndBatchDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "preserve_cardinality"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      batchSize = (Operand<TInt64>) op.input(inputIndex++);
+      numParallelCalls = (Operand<TInt64>) op.input(inputIndex++);
+      dropRemainder = (Operand<TBool>) op.input(inputIndex++);
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      preserveCardinality = op.attributes().getAttrBool("preserve_cardinality");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java
index 0e62ebd5e11..dac1b4bbc4b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MapDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -52,11 +56,11 @@ private MapDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalMapDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of MapDataset
    */
@@ -157,4 +161,55 @@ public Options preserveCardinality(Boolean preserveCardinality) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MapDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The useInterOpParallelism attribute
+     */
+    public final boolean useInterOpParallelism;
+
+    /**
+     * The preserveCardinality attribute
+     */
+    public final boolean preserveCardinality;
+
+    public Inputs(GraphOperation op) {
+      super(new MapDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "use_inter_op_parallelism", "preserve_cardinality"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      useInterOpParallelism = op.attributes().getAttrBool("use_inter_op_parallelism");
+      preserveCardinality = op.attributes().getAttrBool("preserve_cardinality");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MatchingFilesDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MatchingFilesDataset.java
index ab878c00539..d56e2d11450 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MatchingFilesDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MatchingFilesDataset.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -49,7 +52,7 @@ private MatchingFilesDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalMatchingFilesDataset operation.
    *
    * @param scope current scope
-   * @param patterns the patterns value
+   * @param patterns The patterns value
    * @return a new instance of MatchingFilesDataset
    */
   @Endpoint(
@@ -75,4 +78,17 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<MatchingFilesDataset> {
+    /**
+     * The patterns input
+     */
+    public final Operand<TString> patterns;
+
+    public Inputs(GraphOperation op) {
+      super(new MatchingFilesDataset(op), op, Arrays.asList());
+      int inputIndex = 0;
+      patterns = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java
index 9cb10df0fa7..a934b3641f2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -52,10 +56,10 @@ private MaxIntraOpParallelismDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalMaxIntraOpParallelismDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param maxIntraOpParallelism Identifies the maximum intra-op parallelism to use.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of MaxIntraOpParallelismDataset
    */
   @Endpoint(
@@ -90,4 +94,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<MaxIntraOpParallelismDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * Identifies the maximum intra-op parallelism to use.
+     */
+    public final Operand<TInt64> maxIntraOpParallelism;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxIntraOpParallelismDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      maxIntraOpParallelism = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java
index 3f181e88877..a8098c45132 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,9 +55,9 @@ private NonSerializableDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalNonSerializableDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of NonSerializableDataset
    */
   @Endpoint(
@@ -86,4 +90,29 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<NonSerializableDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new NonSerializableDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParallelInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParallelInterleaveDataset.java
index 7d12f7468dc..67dfc418202 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParallelInterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParallelInterleaveDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -60,18 +64,18 @@ private ParallelInterleaveDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalParallelInterleaveDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param otherArguments the otherArguments value
-   * @param cycleLength the cycleLength value
-   * @param blockLength the blockLength value
-   * @param sloppy the sloppy value
-   * @param bufferOutputElements the bufferOutputElements value
-   * @param prefetchInputElements the prefetchInputElements value
+   * @param inputDataset The inputDataset value
+   * @param otherArguments The otherArguments value
+   * @param cycleLength The cycleLength value
+   * @param blockLength The blockLength value
+   * @param sloppy The sloppy value
+   * @param bufferOutputElements The bufferOutputElements value
+   * @param prefetchInputElements The prefetchInputElements value
    * @param f A function mapping elements of {@code input_dataset}, concatenated with
    * {@code other_arguments}, to a Dataset variant that contains elements matching
    * {@code output_types} and {@code output_shapes}.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ParallelInterleaveDataset
    */
   @Endpoint(
@@ -114,4 +118,73 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ParallelInterleaveDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The cycleLength input
+     */
+    public final Operand<TInt64> cycleLength;
+
+    /**
+     * The blockLength input
+     */
+    public final Operand<TInt64> blockLength;
+
+    /**
+     * The sloppy input
+     */
+    public final Operand<TBool> sloppy;
+
+    /**
+     * The bufferOutputElements input
+     */
+    public final Operand<TInt64> bufferOutputElements;
+
+    /**
+     * The prefetchInputElements input
+     */
+    public final Operand<TInt64> prefetchInputElements;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ParallelInterleaveDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      cycleLength = (Operand<TInt64>) op.input(inputIndex++);
+      blockLength = (Operand<TInt64>) op.input(inputIndex++);
+      sloppy = (Operand<TBool>) op.input(inputIndex++);
+      bufferOutputElements = (Operand<TInt64>) op.input(inputIndex++);
+      prefetchInputElements = (Operand<TInt64>) op.input(inputIndex++);
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java
index 07382c698c9..8805d0ebf5e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -52,8 +56,8 @@ private ParseExampleDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalParseExampleDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param numParallelCalls the numParallelCalls value
+   * @param inputDataset The inputDataset value
+   * @param numParallelCalls The numParallelCalls value
    * @param denseDefaults A dict mapping string keys to {@code Tensor}s.
    * The keys of the dict must match the dense_keys of the feature.
    * @param sparseKeys A list of string keys in the examples features.
@@ -165,4 +169,94 @@ public Options sloppy(Boolean sloppy) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ParseExampleDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The numParallelCalls input
+     */
+    public final Operand<TInt64> numParallelCalls;
+
+    /**
+     * A dict mapping string keys to {@code Tensor}s.
+     * The keys of the dict must match the dense_keys of the feature.
+     */
+    public final Iterable<Operand<?>> denseDefaults;
+
+    /**
+     * A list of string keys in the examples features.
+     * The results for these keys will be returned as `SparseTensor` objects.
+     */
+    public final String[] sparseKeys;
+
+    /**
+     * A list of Ndense string Tensors (scalars).
+     * The keys expected in the Examples features associated with dense values.
+     */
+    public final String[] denseKeys;
+
+    /**
+     * A list of `DTypes` of the same length as `sparse_keys`.
+     * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
+     * and `tf.string` (`BytesList`) are supported.
+     */
+    public final DataType[] sparseTypes;
+
+    /**
+     * A list of DTypes of the same length as `dense_keys`.
+     * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`),
+     * and `tf.string` (`BytesList`) are supported.
+     */
+    public final DataType[] Tdense;
+
+    /**
+     * List of tuples with the same length as `dense_keys`.
+     * The shape of the data for each dense feature referenced by `dense_keys`.
+     * Required for any input tensors identified by `dense_keys`.  Must be
+     * either fully defined, or may contain an unknown first dimension.
+     * An unknown first dimension means the feature is treated as having
+     * a variable number of blocks, and the output shape along this dimension
+     * is considered unknown at graph build time.  Padding is applied for
+     * minibatch elements smaller than the maximum number of blocks for the
+     * given feature along this dimension.
+     */
+    public final Shape[] denseShapes;
+
+    /**
+     * The type list for the return values.
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The list of shapes being produced.
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The sloppy attribute
+     */
+    public final boolean sloppy;
+
+    public Inputs(GraphOperation op) {
+      super(new ParseExampleDataset(op), op, Arrays.asList("sparse_keys", "dense_keys", "sparse_types", "Tdense", "dense_shapes", "output_types", "output_shapes", "sloppy"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numParallelCalls = (Operand<TInt64>) op.input(inputIndex++);
+      int denseDefaultsLength = op.inputListLength("dense_defaults");
+      denseDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, denseDefaultsLength));
+      inputIndex += denseDefaultsLength;
+      sparseKeys = op.attributes().getAttrStringList("sparse_keys");
+      denseKeys = op.attributes().getAttrStringList("dense_keys");
+      sparseTypes = op.attributes().getAttrTypeList("sparse_types");
+      Tdense = op.attributes().getAttrTypeList("Tdense");
+      denseShapes = op.attributes().getAttrShapeList("dense_shapes");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      sloppy = op.attributes().getAttrBool("sloppy");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java
index 5a00063f195..36aafe3272e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -52,10 +56,10 @@ private PrivateThreadPoolDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalPrivateThreadPoolDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param numThreads Identifies the number of threads to use for the private threadpool.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of PrivateThreadPoolDataset
    */
   @Endpoint(
@@ -90,4 +94,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<PrivateThreadPoolDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * Identifies the number of threads to use for the private threadpool.
+     */
+    public final Operand<TInt64> numThreads;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new PrivateThreadPoolDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numThreads = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java
index aa9519d9f7a..416f4ce7d62 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -56,8 +60,8 @@ private RandomDataset(Operation operation) {
    * seed2 is set to be non-zero, the random number generator is seeded
    * by the given seed.  Otherwise, a random seed is used.
    * @param seed2 A second scalar seed to avoid seed collision.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of RandomDataset
    */
   @Endpoint(
@@ -91,4 +95,37 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<RandomDataset> {
+    /**
+     * A scalar seed for the random number generator. If either seed or
+     * seed2 is set to be non-zero, the random number generator is seeded
+     * by the given seed.  Otherwise, a random seed is used.
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * A second scalar seed to avoid seed collision.
+     */
+    public final Operand<TInt64> seed2;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      seed2 = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java
index b6916632de5..1ae694d9914 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -58,8 +62,8 @@ private RebatchDataset(Operation operation) {
    * @param numReplicas A scalar representing the number of replicas to distribute this batch across. As
    * a result of this transformation the current batch size would end up being
    * divided  by this parameter.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of RebatchDataset
    */
@@ -133,4 +137,43 @@ public Options useFallback(Boolean useFallback) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RebatchDataset> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of replicas to distribute this batch across. As
+     * a result of this transformation the current batch size would end up being
+     * divided  by this parameter.
+     */
+    public final Operand<TInt64> numReplicas;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The useFallback attribute
+     */
+    public final boolean useFallback;
+
+    public Inputs(GraphOperation op) {
+      super(new RebatchDataset(op), op, Arrays.asList("output_types", "output_shapes", "use_fallback"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      numReplicas = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      useFallback = op.attributes().getAttrBool("use_fallback");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ScanDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ScanDataset.java
index 83d1e9d00ff..b02550f116a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ScanDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ScanDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -52,12 +56,12 @@ private ScanDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalScanDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param initialState the initialState value
-   * @param otherArguments the otherArguments value
-   * @param f the value of the f property
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param initialState The initialState value
+   * @param otherArguments The otherArguments value
+   * @param f The value of the f attribute
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @param options carries optional attribute values
    * @return a new instance of ScanDataset
    */
@@ -133,4 +137,63 @@ public Options preserveCardinality(Boolean preserveCardinality) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ScanDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The initialState input
+     */
+    public final Iterable<Operand<?>> initialState;
+
+    /**
+     * The otherArguments input
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Tstate attribute
+     */
+    public final DataType[] Tstate;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The preserveCardinality attribute
+     */
+    public final boolean preserveCardinality;
+
+    public Inputs(GraphOperation op) {
+      super(new ScanDataset(op), op, Arrays.asList("Tstate", "Targuments", "output_types", "output_shapes", "preserve_cardinality"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int initialStateLength = op.inputListLength("initial_state");
+      initialState = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, initialStateLength));
+      inputIndex += initialStateLength;
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Tstate = op.attributes().getAttrTypeList("Tstate");
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      preserveCardinality = op.attributes().getAttrBool("preserve_cardinality");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java
index 48cb4200150..6bcf9d87e29 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -52,12 +56,12 @@ private SetStatsAggregatorDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalSetStatsAggregatorDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param statsAggregator the statsAggregator value
-   * @param tag the tag value
-   * @param counterPrefix the counterPrefix value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param statsAggregator The statsAggregator value
+   * @param tag The tag value
+   * @param counterPrefix The counterPrefix value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SetStatsAggregatorDataset
    */
   @Endpoint(
@@ -95,4 +99,47 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SetStatsAggregatorDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The statsAggregator input
+     */
+    public final Operand<? extends TType> statsAggregator;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The counterPrefix input
+     */
+    public final Operand<TString> counterPrefix;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SetStatsAggregatorDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      statsAggregator = (Operand<? extends TType>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      counterPrefix = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java
index f491ee77fa1..ae879e0fbf4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -52,10 +56,10 @@ private SleepDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalSleepDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param sleepMicroseconds the sleepMicroseconds value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param sleepMicroseconds The sleepMicroseconds value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SleepDataset
    */
   @Endpoint(
@@ -90,4 +94,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SleepDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The sleepMicroseconds input
+     */
+    public final Operand<TInt64> sleepMicroseconds;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SleepDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      sleepMicroseconds = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java
index 78d282bf214..7939710ff4a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -52,15 +56,15 @@ private SlidingWindowDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalSlidingWindowDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param windowSize A scalar representing the number of elements in the
    * sliding window.
    * @param windowShift A scalar representing the steps moving the sliding window
    * forward in one iteration. It must be positive.
    * @param windowStride A scalar representing the stride of the input elements of the sliding window.
    * It must be positive.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SlidingWindowDataset
    */
   @Endpoint(
@@ -97,4 +101,50 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SlidingWindowDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A scalar representing the number of elements in the
+     * sliding window.
+     */
+    public final Operand<TInt64> windowSize;
+
+    /**
+     * A scalar representing the steps moving the sliding window
+     * forward in one iteration. It must be positive.
+     */
+    public final Operand<TInt64> windowShift;
+
+    /**
+     * A scalar representing the stride of the input elements of the sliding window.
+     * It must be positive.
+     */
+    public final Operand<TInt64> windowStride;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SlidingWindowDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      windowSize = (Operand<TInt64>) op.input(inputIndex++);
+      windowShift = (Operand<TInt64>) op.input(inputIndex++);
+      windowStride = (Operand<TInt64>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java
index e5e46b1bdf3..3a62b4c17bd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -55,8 +59,8 @@ private SqlDataset(Operation operation) {
    * @param driverName The database type. Currently, the only supported type is 'sqlite'.
    * @param dataSourceName A connection string to connect to the database.
    * @param query A SQL query to execute.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of SqlDataset
    */
   @Endpoint(
@@ -92,4 +96,41 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<SqlDataset> {
+    /**
+     * The database type. Currently, the only supported type is 'sqlite'.
+     */
+    public final Operand<TString> driverName;
+
+    /**
+     * A connection string to connect to the database.
+     */
+    public final Operand<TString> dataSourceName;
+
+    /**
+     * A SQL query to execute.
+     */
+    public final Operand<TString> query;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new SqlDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      driverName = (Operand<TString>) op.input(inputIndex++);
+      dataSourceName = (Operand<TString>) op.input(inputIndex++);
+      query = (Operand<TString>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorHandle.java
index c39b34e4b66..ce6bc4bd54b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorHandle.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -137,4 +140,23 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StatsAggregatorHandle> {
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new StatsAggregatorHandle(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSummary.java
index cd3b21e170d..61aeec7600b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSummary.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -48,7 +51,7 @@ private StatsAggregatorSummary(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalStatsAggregatorSummary operation.
    *
    * @param scope current scope
-   * @param iterator the iterator value
+   * @param iterator The iterator value
    * @return a new instance of StatsAggregatorSummary
    */
   @Endpoint(
@@ -73,4 +76,17 @@ public Output<TString> summary() {
   public Output<TString> asOutput() {
     return summary;
   }
+
+  public static class Inputs extends RawOpInputs<StatsAggregatorSummary> {
+    /**
+     * The iterator input
+     */
+    public final Operand<? extends TType> iterator;
+
+    public Inputs(GraphOperation op) {
+      super(new StatsAggregatorSummary(op), op, Arrays.asList());
+      int inputIndex = 0;
+      iterator = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/TakeWhileDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/TakeWhileDataset.java
index b4390229eb2..f11aa6444dd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/TakeWhileDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/TakeWhileDataset.java
@@ -17,8 +17,10 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -58,12 +62,12 @@ private TakeWhileDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalTakeWhileDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param otherArguments A list of tensors, typically values that were captured when
    * building a closure for {@code predicate}.
    * @param predicate A function returning a scalar boolean.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of TakeWhileDataset
    */
   @Endpoint(
@@ -99,4 +103,44 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<TakeWhileDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A list of tensors, typically values that were captured when
+     * building a closure for {@code predicate}.
+     */
+    public final Iterable<Operand<?>> otherArguments;
+
+    /**
+     * The Targuments attribute
+     */
+    public final DataType[] Targuments;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new TakeWhileDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      int otherArgumentsLength = op.inputListLength("other_arguments");
+      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
+      inputIndex += otherArgumentsLength;
+      Targuments = op.attributes().getAttrTypeList("Targuments");
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java
index 467f53a61af..379c0a245a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,10 +55,10 @@ private ThreadPoolDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalThreadPoolDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @param threadPool A resource produced by the ThreadPoolHandle op.
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of ThreadPoolDataset
    */
   @Endpoint(
@@ -89,4 +93,35 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<ThreadPoolDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * A resource produced by the ThreadPoolHandle op.
+     */
+    public final Operand<? extends TType> threadPool;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ThreadPoolDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      threadPool = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolHandle.java
index 1635a481604..27a66b8df1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolHandle.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -173,4 +176,44 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ThreadPoolHandle> {
+    /**
+     * The number of threads in the thread pool.
+     */
+    public final long numThreads;
+
+    /**
+     * The maximum degree of parallelism to use within operations that execute on this
+     * threadpool.
+     */
+    public final long maxIntraOpParallelism;
+
+    /**
+     * A human-readable name for the threads that may be visible in some
+     * visualizations.
+     * threadpool.
+     */
+    public final String displayName;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new ThreadPoolHandle(op), op, Arrays.asList("num_threads", "max_intra_op_parallelism", "display_name", "container", "shared_name"));
+      int inputIndex = 0;
+      numThreads = op.attributes().getAttrInt("num_threads");
+      maxIntraOpParallelism = op.attributes().getAttrInt("max_intra_op_parallelism");
+      displayName = op.attributes().getAttrString("display_name");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java
index dfd9dbbc8d9..b427d4e576b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,9 +55,9 @@ private UnbatchDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalUnbatchDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of UnbatchDataset
    */
   @Endpoint(
@@ -86,4 +90,29 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<UnbatchDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new UnbatchDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java
index 224d8c5758b..6d81f2ab1a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.data.experimental;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,9 +55,9 @@ private UniqueDataset(Operation operation) {
    * Factory method to create a class wrapping a new ExperimentalUniqueDataset operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
-   * @param outputTypes the value of the outputTypes property
-   * @param outputShapes the value of the outputShapes property
+   * @param inputDataset The inputDataset value
+   * @param outputTypes The value of the outputTypes attribute
+   * @param outputShapes The value of the outputShapes attribute
    * @return a new instance of UniqueDataset
    */
   @Endpoint(
@@ -86,4 +90,29 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<UniqueDataset> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    /**
+     * The outputTypes attribute
+     */
+    public final DataType[] outputTypes;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new UniqueDataset(op), op, Arrays.asList("output_types", "output_shapes"));
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+      outputTypes = op.attributes().getAttrTypeList("output_types");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java
index 48fb6f1a702..644bc1091de 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.debugging;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private CheckNumerics(Operation operation) {
    * Factory method to create a class wrapping a new CheckNumericsV2 operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
+   * @param tensor The tensor value
    * @param message Prefix of the error message.
    * @param <T> data type for {@code CheckNumericsV2} output and operands
    * @return a new instance of CheckNumerics
@@ -82,4 +86,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CheckNumerics<T>> {
+    /**
+     * The tensor input
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Prefix of the error message.
+     */
+    public final String message;
+
+    public Inputs(GraphOperation op) {
+      super(new CheckNumerics<>(op), op, Arrays.asList("T", "message"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      message = op.attributes().getAttrString("message");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java
index 1038acbc9f3..e72c3442a7d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.debugging;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -52,7 +56,7 @@ private DebugGradientIdentity(Operation operation) {
    * Factory method to create a class wrapping a new DebugGradientIdentity operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code DebugGradientIdentity} output and operands
    * @return a new instance of DebugGradientIdentity
    */
@@ -78,4 +82,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DebugGradientIdentity<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DebugGradientIdentity<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java
index b80cfd3951f..1546bc11128 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.debugging;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -52,7 +56,7 @@ private DebugGradientRefIdentity(Operation operation) {
    * Factory method to create a class wrapping a new DebugGradientRefIdentity operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code DebugGradientRefIdentity} output and operands
    * @return a new instance of DebugGradientRefIdentity
    */
@@ -79,4 +83,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DebugGradientRefIdentity<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DebugGradientRefIdentity<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java
index 066e18c068e..01167c395e6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -162,7 +165,7 @@ public static Options debugUrls(List<String> debugUrls) {
    * @param debugUrls List of URLs to debug targets, e.g., file:///foo/tfdbg_dump.
    * @return this Options instance.
    */
-  public static Options debugUrls(String[] debugUrls) {
+  public static Options debugUrls(String... debugUrls) {
     return new Options().debugUrls(debugUrls);
   }
 
@@ -312,4 +315,68 @@ public Options tfdbgRunId(String tfdbgRunId) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DebugIdentity<T>> {
+    /**
+     * Input tensor, non-Reference type
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A tfdbg-generated ID for the context that the op belongs to,
+     *   e.g., a concrete compiled tf.function.
+     */
+    public final String tfdbgContextId;
+
+    /**
+     * Optional. Name of the op that the debug op is concerned with.
+     *   Used only for single-tensor trace.
+     */
+    public final String opName;
+
+    /**
+     * Optional. Output slot index of the tensor that the debug op
+     *   is concerned with. Used only for single-tensor trace.
+     */
+    public final long outputSlot;
+
+    /**
+     * TensorDebugMode enum value. See debug_event.proto for details.
+     */
+    public final long tensorDebugMode;
+
+    /**
+     * List of URLs to debug targets, e.g., file:///foo/tfdbg_dump.
+     */
+    public final String[] debugUrls;
+
+    /**
+     * The circularBufferSize attribute
+     */
+    public final long circularBufferSize;
+
+    /**
+     * The tfdbgRunId attribute
+     */
+    public final String tfdbgRunId;
+
+    public Inputs(GraphOperation op) {
+      super(new DebugIdentity<>(op), op, Arrays.asList("T", "tfdbg_context_id", "op_name", "output_slot", "tensor_debug_mode", "debug_urls", "circular_buffer_size", "tfdbg_run_id"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      tfdbgContextId = op.attributes().getAttrString("tfdbg_context_id");
+      opName = op.attributes().getAttrString("op_name");
+      outputSlot = op.attributes().getAttrInt("output_slot");
+      tensorDebugMode = op.attributes().getAttrInt("tensor_debug_mode");
+      debugUrls = op.attributes().getAttrStringList("debug_urls");
+      circularBufferSize = op.attributes().getAttrInt("circular_buffer_size");
+      tfdbgRunId = op.attributes().getAttrString("tfdbg_run_id");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java
index 0ebdb1005cd..9925d851593 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -123,7 +126,7 @@ public static Options debugUrls(List<String> debugUrls) {
    * file:///foo/tfdbg_dump, grpc:://localhost:11011.
    * @return this Options instance.
    */
-  public static Options debugUrls(String[] debugUrls) {
+  public static Options debugUrls(String... debugUrls) {
     return new Options().debugUrls(debugUrls);
   }
 
@@ -233,4 +236,53 @@ public Options gatedGrpc(Boolean gatedGrpc) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DebugNanCount> {
+    /**
+     * Input tensor, non-Reference type.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The deviceName attribute
+     */
+    public final String deviceName;
+
+    /**
+     * Name of the input tensor.
+     */
+    public final String tensorName;
+
+    /**
+     * List of URLs to debug targets, e.g.,
+     *   file:///foo/tfdbg_dump, grpc:://localhost:11011.
+     */
+    public final String[] debugUrls;
+
+    /**
+     *  Whether this op will be gated. If any of the debug_urls of this
+     *   debug node is of the grpc:// scheme, when the value of this attribute is set
+     *   to True, the data will not actually be sent via the grpc stream unless this
+     *   debug op has been enabled at the debug_url. If all of the debug_urls of this
+     *   debug node are of the grpc:// scheme and the debug op is enabled at none of
+     *   them, the output will be an empty Tensor.
+     */
+    public final boolean gatedGrpc;
+
+    public Inputs(GraphOperation op) {
+      super(new DebugNanCount(op), op, Arrays.asList("T", "device_name", "tensor_name", "debug_urls", "gated_grpc"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      deviceName = op.attributes().getAttrString("device_name");
+      tensorName = op.attributes().getAttrString("tensor_name");
+      debugUrls = op.attributes().getAttrStringList("debug_urls");
+      gatedGrpc = op.attributes().getAttrBool("gated_grpc");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java
index 34ab74a640f..6dd55b043fc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.debugging;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -259,4 +263,94 @@ public Options tensorId(Long tensorId) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DebugNumericsSummary<?>> {
+    /**
+     * Input tensor, to be summarized by the op.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * Optional. The type of the output. Can be float32 or float64 (default: float32).
+     */
+    public final DataType outputDtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Tensor debug mode: the mode in which the input tensor is summarized
+     *   by the op. See the TensorDebugMode enum in
+     *   tensorflow/core/protobuf/debug_event.proto for details.
+     *
+     * Supported values:
+     *   2 (CURT_HEALTH): Output a float32/64 tensor of shape [2]. The 1st
+     *   element is the tensor_id, if provided, and -1 otherwise. The 2nd
+     *   element is a bit which is set to 1 if the input tensor has an
+     *   infinity or nan value, or zero otherwise.
+     *
+     *   3 (CONCISE_HEALTH): Output a float32/64 tensor of shape [5]. The 1st
+     *   element is the tensor_id, if provided, and -1 otherwise. The
+     *   remaining four slots are the total number of elements, -infs,
+     *   +infs, and nans in the input tensor respectively.
+     *
+     *   4 (FULL_HEALTH): Output a float32/64 tensor of shape [11]. The 1st
+     *   element is the tensor_id, if provided, and -1 otherwise. The 2nd
+     *   element is the device_id, if provided, and -1 otherwise. The 3rd
+     *   element holds the datatype value of the input tensor as according
+     *   to the enumerated type in tensorflow/core/framework/types.proto.
+     *   The remaining elements hold the total number of elements, -infs,
+     *   +infs, nans, negative finite numbers, zeros, and positive finite
+     *   numbers in the input tensor respectively.
+     *
+     *   5 (SHAPE): Output a float32/64 tensor of shape [10]. The 1st
+     *   element is the tensor_id, if provided, and -1 otherwise. The 2nd
+     *   element holds the datatype value of the input tensor as according
+     *   to the enumerated type in tensorflow/core/framework/types.proto.
+     *   The 3rd element holds the rank of the tensor. The 4th element holds
+     *   the number of elements within the tensor. Finally the remaining 6
+     *   elements hold the shape of the tensor. If the rank of the tensor
+     *   is lower than 6, the shape is right padded with zeros. If the rank
+     *   is greater than 6, the head of the shape is truncated.
+     *
+     *   6 (FULL_NUMERICS): Output a float32/64 tensor of shape [22]. The 1st
+     *   element is the tensor_id, if provided, and -1 otherwise. The 2nd
+     *   element is the device_id, if provided, and -1 otherwise. The 3rd
+     *   element holds the datatype value of the input tensor as according
+     *   to the enumerated type in tensorflow/core/framework/types.proto.
+     *   The 4th element holds the rank of the tensor. The 5th to 11th
+     *   elements hold the shape of the tensor. If the rank of the tensor
+     *   is lower than 6, the shape is right padded with zeros. If the rank
+     *   is greater than 6, the head of the shape is truncated. The 12th to
+     *   18th elements hold the number of elements, -infs, +infs, nans,
+     *   denormal floats, negative finite numbers, zeros, and positive
+     *   finite numbers in the input tensor respectively. The final four
+     *   elements hold the min value, max value, mean, and variance of the
+     *   input tensor.
+     *
+     *   8 (REDUCE_INF_NAN_THREE_SLOTS): Output a float32/64 tensor of shape
+     *   [3]. The 1st element is -inf if any elements of the input tensor
+     *   is -inf, or zero otherwise. The 2nd element is +inf if any elements
+     *   of the input tensor is +inf, or zero otherwise.  The 3rd element is
+     *   nan if any element of the input tensor is nan, or zero otherwise.
+     */
+    public final long tensorDebugMode;
+
+    /**
+     * Optional. An integer identifier for the tensor being summarized by this op.
+     */
+    public final long tensorId;
+
+    public Inputs(GraphOperation op) {
+      super(new DebugNumericsSummary<>(op), op, Arrays.asList("output_dtype", "T", "tensor_debug_mode", "tensor_id"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      outputDtype = op.attributes().getAttrType("output_dtype");
+      T = op.attributes().getAttrType("T");
+      tensorDebugMode = op.attributes().getAttrInt("tensor_debug_mode");
+      tensorId = op.attributes().getAttrInt("tensor_id");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java
index 72bc90a364c..fe38870830d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.distribute;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -59,10 +63,10 @@ private NcclAllReduce(Operation operation) {
    * Factory method to create a class wrapping a new NcclAllReduce operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param reduction the value of the reduction property
-   * @param numDevices the value of the numDevices property
-   * @param sharedName the value of the sharedName property
+   * @param input The input value
+   * @param reduction The value of the reduction attribute
+   * @param numDevices The value of the numDevices attribute
+   * @param sharedName The value of the sharedName attribute
    * @param <T> data type for {@code NcclAllReduce} output and operands
    * @return a new instance of NcclAllReduce
    */
@@ -92,4 +96,41 @@ public Output<T> data() {
   public Output<T> asOutput() {
     return data;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NcclAllReduce<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The reduction attribute
+     */
+    public final String reduction;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The numDevices attribute
+     */
+    public final long numDevices;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new NcclAllReduce<>(op), op, Arrays.asList("reduction", "T", "num_devices", "shared_name"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      reduction = op.attributes().getAttrString("reduction");
+      T = op.attributes().getAttrType("T");
+      numDevices = op.attributes().getAttrInt("num_devices");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java
index 0b34c24a7cc..79c330beaa1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.distribute;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -56,8 +60,8 @@ private NcclBroadcast(Operation operation) {
    * Factory method to create a class wrapping a new NcclBroadcast operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param shape the value of the shape property
+   * @param input The input value
+   * @param shape The value of the shape attribute
    * @param <T> data type for {@code NcclBroadcast} output and operands
    * @return a new instance of NcclBroadcast
    */
@@ -85,4 +89,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NcclBroadcast<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The shape attribute
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new NcclBroadcast<>(op), op, Arrays.asList("T", "shape"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java
index 2204b1c0a72..759c6ea5a92 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.distribute;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -56,8 +60,8 @@ private NcclReduce(Operation operation) {
    * Factory method to create a class wrapping a new NcclReduce operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param reduction the value of the reduction property
+   * @param input The input value
+   * @param reduction The value of the reduction attribute
    * @param <T> data type for {@code NcclReduce} output and operands
    * @return a new instance of NcclReduce
    */
@@ -85,4 +89,31 @@ public Output<T> data() {
   public Output<T> asOutput() {
     return data;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NcclReduce<T>> {
+    /**
+     * The input input
+     */
+    public final Iterable<Operand<T>> input;
+
+    /**
+     * The reduction attribute
+     */
+    public final String reduction;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new NcclReduce<>(op), op, Arrays.asList("reduction", "T"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      reduction = op.attributes().getAttrString("reduction");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java
index 56c385236bf..a7de0ccc4e0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.dtypes;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -67,7 +71,7 @@ private AsString(Operation operation) {
    * Factory method to create a class wrapping a new AsString operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @return a new instance of AsString
    */
@@ -245,4 +249,58 @@ public Options fill(String fill) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AsString> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The post-decimal precision to use for floating point numbers.
+     * Only used if precision > -1.
+     */
+    public final long precision;
+
+    /**
+     * Use scientific notation for floating point numbers.
+     */
+    public final boolean scientific;
+
+    /**
+     * Use shortest representation (either scientific or standard) for
+     * floating point numbers.
+     */
+    public final boolean shortest;
+
+    /**
+     * Pad pre-decimal numbers to this width.
+     * Applies to both floating point and integer numbers.
+     * Only used if width > -1.
+     */
+    public final long width;
+
+    /**
+     * The value to pad if width > -1.  If empty, pads with spaces.
+     * Another typical value is '0'.  String cannot be longer than 1 character.
+     */
+    public final String fill;
+
+    public Inputs(GraphOperation op) {
+      super(new AsString(op), op, Arrays.asList("T", "precision", "scientific", "shortest", "width", "fill"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      precision = op.attributes().getAttrInt("precision");
+      scientific = op.attributes().getAttrBool("scientific");
+      shortest = op.attributes().getAttrBool("shortest");
+      width = op.attributes().getAttrInt("width");
+      fill = op.attributes().getAttrString("fill");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java
index 38e5860f94a..cc9cbb10ec2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.dtypes;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,8 +58,8 @@ private Cast(Operation operation) {
    * Factory method to create a class wrapping a new Cast operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param DstT the value of the DstT property
+   * @param x The x value
+   * @param DstT The value of the DstT attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code Cast} output and operands
    * @return a new instance of Cast
@@ -122,4 +126,35 @@ public Options Truncate(Boolean Truncate) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Cast<?>> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TType> x;
+
+    /**
+     * The SrcT attribute
+     */
+    public final DataType SrcT;
+
+    /**
+     * The DstT attribute
+     */
+    public final DataType DstT;
+
+    /**
+     * The Truncate attribute
+     */
+    public final boolean Truncate;
+
+    public Inputs(GraphOperation op) {
+      super(new Cast<>(op), op, Arrays.asList("SrcT", "DstT", "Truncate"));
+      int inputIndex = 0;
+      x = (Operand<? extends TType>) op.input(inputIndex++);
+      SrcT = op.attributes().getAttrType("SrcT");
+      DstT = op.attributes().getAttrType("DstT");
+      Truncate = op.attributes().getAttrBool("Truncate");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java
index c7fdf63b966..86d216c50c0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.dtypes;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -66,9 +70,9 @@ private Complex(Operation operation) {
    * Factory method to create a class wrapping a new Complex operation.
    *
    * @param scope current scope
-   * @param real the real value
-   * @param imag the imag value
-   * @param Tout the value of the Tout property
+   * @param real The real value
+   * @param imag The imag value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Complex} output and operands
    * @param <T> data type for {@code Complex} output and operands
    * @return a new instance of Complex
@@ -98,4 +102,35 @@ public Output<U> out() {
   public Output<U> asOutput() {
     return out;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Complex<?>> {
+    /**
+     * The real input
+     */
+    public final Operand<T> real;
+
+    /**
+     * The imag input
+     */
+    public final Operand<T> imag;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new Complex<>(op), op, Arrays.asList("T", "Tout"));
+      int inputIndex = 0;
+      real = (Operand<T>) op.input(inputIndex++);
+      imag = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/ToBool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/ToBool.java
index 3fac763c3eb..44ac418d3d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/ToBool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/ToBool.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.dtypes;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -63,7 +67,7 @@ private ToBool(Operation operation) {
    * Factory method to create a class wrapping a new ToBool operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of ToBool
    */
   @Endpoint(
@@ -88,4 +92,23 @@ public Output<TBool> output() {
   public Output<TBool> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ToBool> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ToBool(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesAggregateStats.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesAggregateStats.java
index 80f669c35d3..7b0529beffe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesAggregateStats.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesAggregateStats.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -87,4 +90,47 @@ public Output<TFloat32> statsSummary() {
   public Output<TFloat32> asOutput() {
     return statsSummary;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesAggregateStats> {
+    /**
+     * int32; Rank 1 Tensor containing node ids for each example, shape [batch_size].
+     */
+    public final Operand<TInt32> nodeIds;
+
+    /**
+     * float32; Rank 2 Tensor (shape=[batch_size, logits_dimension]) with gradients for each example.
+     */
+    public final Operand<TFloat32> gradients;
+
+    /**
+     * float32; Rank 2 Tensor (shape=[batch_size, hessian_dimension]) with hessians for each example.
+     */
+    public final Operand<TFloat32> hessians;
+
+    /**
+     * int32; Rank 2 feature Tensors (shape=[batch_size, feature_dimension]).
+     */
+    public final Operand<TInt32> feature;
+
+    /**
+     * int; the maximum number of splits possible in the whole tree.
+     */
+    public final long maxSplits;
+
+    /**
+     * int; equals to the maximum possible value of bucketized feature.
+     */
+    public final long numBuckets;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesAggregateStats(op), op, Arrays.asList("max_splits", "num_buckets"));
+      int inputIndex = 0;
+      nodeIds = (Operand<TInt32>) op.input(inputIndex++);
+      gradients = (Operand<TFloat32>) op.input(inputIndex++);
+      hessians = (Operand<TFloat32>) op.input(inputIndex++);
+      feature = (Operand<TInt32>) op.input(inputIndex++);
+      maxSplits = op.attributes().getAttrInt("max_splits");
+      numBuckets = op.attributes().getAttrInt("num_buckets");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesBucketize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesBucketize.java
index b0a7183f681..c9e18b2a292 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesBucketize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesBucketize.java
@@ -20,12 +20,14 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -87,4 +89,28 @@ public List<Output<TInt32>> buckets() {
   public Iterator<Operand<TInt32>> iterator() {
     return (Iterator) buckets.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesBucketize> {
+    /**
+     * float; List of Rank 1 Tensor each containing float values for a single feature.
+     */
+    public final Iterable<Operand<TFloat32>> floatValues;
+
+    /**
+     * float; List of Rank 1 Tensors each containing the bucket boundaries for a single
+     * feature.
+     */
+    public final Iterable<Operand<TFloat32>> bucketBoundaries;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesBucketize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      int floatValuesLength = op.inputListLength("float_values");
+      floatValues = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, floatValuesLength));
+      inputIndex += floatValuesLength;
+      int bucketBoundariesLength = op.inputListLength("bucket_boundaries");
+      bucketBoundaries = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, bucketBoundariesLength));
+      inputIndex += bucketBoundariesLength;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplit.java
index 01eb21bba88..8979b37a37c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplit.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -201,4 +204,60 @@ public Options splitType(String splitType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesCalculateBestFeatureSplit> {
+    /**
+     * A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within {@code stats_summary_list}. The nodes are iterated between the two nodes specified by the tensor, as like {@code for node_id in range(node_id_range[0], node_id_range[1])} (Note that the last index node_id_range[1] is exclusive).
+     */
+    public final Operand<TInt32> nodeIdRange;
+
+    /**
+     * A Rank 4 tensor (#shape=[max_splits, feature_dims, bucket, stats_dims]) for accumulated stats summary (gradient/hessian) per node, per dimension, per buckets for each feature.
+     * The first dimension of the tensor is the maximum number of splits, and thus not all elements of it will be used, but only the indexes specified by node_ids will be used.
+     */
+    public final Operand<TFloat32> statsSummary;
+
+    /**
+     * l1 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l1;
+
+    /**
+     * l2 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l2;
+
+    /**
+     * adjustment to the gain, per leaf based.
+     */
+    public final Operand<TFloat32> treeComplexity;
+
+    /**
+     * minimum avg of hessians in a node before required for the node to be considered for splitting.
+     */
+    public final Operand<TFloat32> minNodeWeight;
+
+    /**
+     * The dimension of logit, i.e., number of classes.
+     */
+    public final long logitsDimension;
+
+    /**
+     * A string indicating if this Op should perform inequality split or equality split.
+     */
+    public final String splitType;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesCalculateBestFeatureSplit(op), op, Arrays.asList("logits_dimension", "split_type"));
+      int inputIndex = 0;
+      nodeIdRange = (Operand<TInt32>) op.input(inputIndex++);
+      statsSummary = (Operand<TFloat32>) op.input(inputIndex++);
+      l1 = (Operand<TFloat32>) op.input(inputIndex++);
+      l2 = (Operand<TFloat32>) op.input(inputIndex++);
+      treeComplexity = (Operand<TFloat32>) op.input(inputIndex++);
+      minNodeWeight = (Operand<TFloat32>) op.input(inputIndex++);
+      logitsDimension = op.attributes().getAttrInt("logits_dimension");
+      splitType = op.attributes().getAttrString("split_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplitV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplitV2.java
index 666b544d323..d733c5f82bc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplitV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestFeatureSplitV2.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -180,4 +183,68 @@ public Output<TFloat32> rightNodeContribs() {
   public Output<TString> splitWithDefaultDirections() {
     return splitWithDefaultDirections;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesCalculateBestFeatureSplitV2> {
+    /**
+     * A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within {@code stats_summary_list}. The nodes are iterated between the two nodes specified by the tensor, as like {@code for node_id in range(node_id_range[0], node_id_range[1])} (Note that the last index node_id_range[1] is exclusive).
+     */
+    public final Operand<TInt32> nodeIdRange;
+
+    /**
+     * A list of Rank 4 tensor (#shape=[max_splits, feature_dims, bucket, stats_dims]) for accumulated stats summary (gradient/hessian) per node, per dimension, per buckets for each feature.
+     * The first dimension of the tensor is the maximum number of splits, and thus not all elements of it will be used, but only the indexes specified by node_ids will be used.
+     */
+    public final Iterable<Operand<TFloat32>> statsSummariesList;
+
+    /**
+     * A Rank 1 tensor indicating if this Op should perform inequality split or equality split per feature.
+     */
+    public final Operand<TString> splitTypes;
+
+    /**
+     * Rank 1 tensor with ids for each feature. This is the real id of the feature.
+     */
+    public final Operand<TInt32> candidateFeatureIds;
+
+    /**
+     * l1 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l1;
+
+    /**
+     * l2 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l2;
+
+    /**
+     * adjustment to the gain, per leaf based.
+     */
+    public final Operand<TFloat32> treeComplexity;
+
+    /**
+     * minimum avg of hessians in a node before required for the node to be considered for splitting.
+     */
+    public final Operand<TFloat32> minNodeWeight;
+
+    /**
+     * The dimension of logit, i.e., number of classes.
+     */
+    public final long logitsDimension;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesCalculateBestFeatureSplitV2(op), op, Arrays.asList("logits_dimension"));
+      int inputIndex = 0;
+      nodeIdRange = (Operand<TInt32>) op.input(inputIndex++);
+      int statsSummariesListLength = op.inputListLength("stats_summaries_list");
+      statsSummariesList = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, statsSummariesListLength));
+      inputIndex += statsSummariesListLength;
+      splitTypes = (Operand<TString>) op.input(inputIndex++);
+      candidateFeatureIds = (Operand<TInt32>) op.input(inputIndex++);
+      l1 = (Operand<TFloat32>) op.input(inputIndex++);
+      l2 = (Operand<TFloat32>) op.input(inputIndex++);
+      treeComplexity = (Operand<TFloat32>) op.input(inputIndex++);
+      minNodeWeight = (Operand<TFloat32>) op.input(inputIndex++);
+      logitsDimension = op.attributes().getAttrInt("logits_dimension");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestGainsPerFeature.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestGainsPerFeature.java
index ea1a95a6d51..4d77413901b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestGainsPerFeature.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCalculateBestGainsPerFeature.java
@@ -19,12 +19,14 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -150,4 +152,55 @@ public List<Output<TFloat32>> leftNodeContribsList() {
   public List<Output<TFloat32>> rightNodeContribsList() {
     return rightNodeContribsList;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesCalculateBestGainsPerFeature> {
+    /**
+     * A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within {@code stats_summary_list}. The nodes are iterated between the two nodes specified by the tensor, as like {@code for node_id in range(node_id_range[0], node_id_range[1])} (Note that the last index node_id_range[1] is exclusive).
+     */
+    public final Operand<TInt32> nodeIdRange;
+
+    /**
+     * A list of Rank 3 tensor (#shape=[max_splits, bucket, 2]) for accumulated stats summary (gradient/hessian) per node per buckets for each feature. The first dimension of the tensor is the maximum number of splits, and thus not all elements of it will be used, but only the indexes specified by node_ids will be used.
+     */
+    public final Iterable<Operand<TFloat32>> statsSummaryList;
+
+    /**
+     * l1 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l1;
+
+    /**
+     * l2 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l2;
+
+    /**
+     * adjustment to the gain, per leaf based.
+     */
+    public final Operand<TFloat32> treeComplexity;
+
+    /**
+     * minimum avg of hessians in a node before required for the node to be considered for splitting.
+     */
+    public final Operand<TFloat32> minNodeWeight;
+
+    /**
+     * the number of nodes that can be split in the whole tree. Used as a dimension of output tensors.
+     */
+    public final long maxSplits;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesCalculateBestGainsPerFeature(op), op, Arrays.asList("max_splits"));
+      int inputIndex = 0;
+      nodeIdRange = (Operand<TInt32>) op.input(inputIndex++);
+      int statsSummaryListLength = op.inputListLength("stats_summary_list");
+      statsSummaryList = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, statsSummaryListLength));
+      inputIndex += statsSummaryListLength;
+      l1 = (Operand<TFloat32>) op.input(inputIndex++);
+      l2 = (Operand<TFloat32>) op.input(inputIndex++);
+      treeComplexity = (Operand<TFloat32>) op.input(inputIndex++);
+      minNodeWeight = (Operand<TFloat32>) op.input(inputIndex++);
+      maxSplits = op.attributes().getAttrInt("max_splits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCenterBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCenterBias.java
index dd45c6709a5..320bebfbc4c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCenterBias.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCenterBias.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -84,4 +87,41 @@ public Output<TBool> continueCentering() {
   public Output<TBool> asOutput() {
     return continueCentering;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesCenterBias> {
+    /**
+     * Handle to the tree ensemble.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * A tensor with shape=[logits_dimension] with mean of gradients for a first node.
+     */
+    public final Operand<TFloat32> meanGradients;
+
+    /**
+     * A tensor with shape=[logits_dimension] mean of hessians for a first node.
+     */
+    public final Operand<TFloat32> meanHessians;
+
+    /**
+     * l1 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l1;
+
+    /**
+     * l2 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l2;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesCenterBias(op), op, Arrays.asList());
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      meanGradients = (Operand<TFloat32>) op.input(inputIndex++);
+      meanHessians = (Operand<TFloat32>) op.input(inputIndex++);
+      l1 = (Operand<TFloat32>) op.input(inputIndex++);
+      l2 = (Operand<TFloat32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateEnsemble.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateEnsemble.java
index 0793a9d4dad..31df4690605 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateEnsemble.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateEnsemble.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -61,4 +64,29 @@ public static BoostedTreesCreateEnsemble create(Scope scope,
     opBuilder.addInput(treeEnsembleSerialized.asOutput());
     return new BoostedTreesCreateEnsemble(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesCreateEnsemble> {
+    /**
+     * Handle to the tree ensemble resource to be created.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * Token to use as the initial value of the resource stamp.
+     */
+    public final Operand<TInt64> stampToken;
+
+    /**
+     * Serialized proto of the tree ensemble.
+     */
+    public final Operand<TString> treeEnsembleSerialized;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesCreateEnsemble(op), op, Arrays.asList());
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      stampToken = (Operand<TInt64>) op.input(inputIndex++);
+      treeEnsembleSerialized = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateQuantileStreamResource.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateQuantileStreamResource.java
index 0fa016c985c..9d5a68ea32d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateQuantileStreamResource.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesCreateQuantileStreamResource.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -100,4 +103,35 @@ public Options maxElements(Long maxElements) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesCreateQuantileStreamResource> {
+    /**
+     * resource; Handle to quantile stream resource.
+     */
+    public final Operand<? extends TType> quantileStreamResourceHandle;
+
+    /**
+     * float; The required approximation error of the stream resource.
+     */
+    public final Operand<TFloat32> epsilon;
+
+    /**
+     * int; The number of streams managed by the resource that shares the same epsilon.
+     */
+    public final Operand<TInt64> numStreams;
+
+    /**
+     * int; The maximum number of data points that can be fed to the stream.
+     */
+    public final long maxElements;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesCreateQuantileStreamResource(op), op, Arrays.asList("max_elements"));
+      int inputIndex = 0;
+      quantileStreamResourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      epsilon = (Operand<TFloat32>) op.input(inputIndex++);
+      numStreams = (Operand<TInt64>) op.input(inputIndex++);
+      maxElements = op.attributes().getAttrInt("max_elements");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesDeserializeEnsemble.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesDeserializeEnsemble.java
index 40af63f7302..fbeb4604ca7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesDeserializeEnsemble.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesDeserializeEnsemble.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -62,4 +65,29 @@ public static BoostedTreesDeserializeEnsemble create(Scope scope,
     opBuilder.addInput(treeEnsembleSerialized.asOutput());
     return new BoostedTreesDeserializeEnsemble(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesDeserializeEnsemble> {
+    /**
+     * Handle to the tree ensemble.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * Token to use as the new value of the resource stamp.
+     */
+    public final Operand<TInt64> stampToken;
+
+    /**
+     * Serialized proto of the ensemble.
+     */
+    public final Operand<TString> treeEnsembleSerialized;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesDeserializeEnsemble(op), op, Arrays.asList());
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      stampToken = (Operand<TInt64>) op.input(inputIndex++);
+      treeEnsembleSerialized = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesEnsembleResourceHandleOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesEnsembleResourceHandleOp.java
index 5d9a5b8687a..8fffb3d912a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesEnsembleResourceHandleOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesEnsembleResourceHandleOp.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -137,4 +140,23 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesEnsembleResourceHandleOp> {
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesEnsembleResourceHandleOp(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesExampleDebugOutputs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesExampleDebugOutputs.java
index 4576b2e4bb5..0a8a5b87ca1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesExampleDebugOutputs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesExampleDebugOutputs.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -53,7 +56,7 @@ private BoostedTreesExampleDebugOutputs(Operation operation) {
    * Factory method to create a class wrapping a new BoostedTreesExampleDebugOutputs operation.
    *
    * @param scope current scope
-   * @param treeEnsembleHandle the treeEnsembleHandle value
+   * @param treeEnsembleHandle The treeEnsembleHandle value
    * @param bucketizedFeatures A list of rank 1 Tensors containing bucket id for each
    * feature.
    * @param logitsDimension scalar, dimension of the logits, to be used for constructing the protos in
@@ -86,4 +89,33 @@ public Output<TString> examplesDebugOutputsSerialized() {
   public Output<TString> asOutput() {
     return examplesDebugOutputsSerialized;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesExampleDebugOutputs> {
+    /**
+     * The treeEnsembleHandle input
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * A list of rank 1 Tensors containing bucket id for each
+     * feature.
+     */
+    public final Iterable<Operand<TInt32>> bucketizedFeatures;
+
+    /**
+     * scalar, dimension of the logits, to be used for constructing the protos in
+     * examples_debug_outputs_serialized.
+     */
+    public final long logitsDimension;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesExampleDebugOutputs(op), op, Arrays.asList("logits_dimension"));
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      int bucketizedFeaturesLength = op.inputListLength("bucketized_features");
+      bucketizedFeatures = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, bucketizedFeaturesLength));
+      inputIndex += bucketizedFeaturesLength;
+      logitsDimension = op.attributes().getAttrInt("logits_dimension");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesFlushQuantileSummaries.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesFlushQuantileSummaries.java
index a3db29c7ec7..04ff2d43bd4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesFlushQuantileSummaries.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesFlushQuantileSummaries.java
@@ -20,11 +20,13 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -58,7 +60,7 @@ private BoostedTreesFlushQuantileSummaries(Operation operation) {
    *
    * @param scope current scope
    * @param quantileStreamResourceHandle resource handle referring to a QuantileStreamResource.
-   * @param numFeatures the value of the numFeatures property
+   * @param numFeatures The value of the numFeatures attribute
    * @return a new instance of BoostedTreesFlushQuantileSummaries
    */
   @Endpoint(
@@ -86,4 +88,17 @@ public List<Output<TFloat32>> summaries() {
   public Iterator<Operand<TFloat32>> iterator() {
     return (Iterator) summaries.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesFlushQuantileSummaries> {
+    /**
+     * resource handle referring to a QuantileStreamResource.
+     */
+    public final Operand<? extends TType> quantileStreamResourceHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesFlushQuantileSummaries(op), op, Arrays.asList());
+      int inputIndex = 0;
+      quantileStreamResourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesGetEnsembleStates.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesGetEnsembleStates.java
index 66c95e96655..47da16b400c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesGetEnsembleStates.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesGetEnsembleStates.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -119,4 +122,17 @@ public Output<TInt32> numAttemptedLayers() {
   public Output<TInt32> lastLayerNodesRange() {
     return lastLayerNodesRange;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesGetEnsembleStates> {
+    /**
+     * Handle to the tree ensemble.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesGetEnsembleStates(op), op, Arrays.asList());
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeQuantileSummaries.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeQuantileSummaries.java
index ad40fc7f30f..b94831dbbe8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeQuantileSummaries.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeQuantileSummaries.java
@@ -20,12 +20,14 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -89,4 +91,31 @@ public List<Output<TFloat32>> summaries() {
   public Iterator<Operand<TFloat32>> iterator() {
     return (Iterator) summaries.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesMakeQuantileSummaries> {
+    /**
+     * float; List of Rank 1 Tensors each containing values for a single feature.
+     */
+    public final Iterable<Operand<TFloat32>> floatValues;
+
+    /**
+     * float; Rank 1 Tensor with weights per instance.
+     */
+    public final Operand<TFloat32> exampleWeights;
+
+    /**
+     * float; The required maximum approximation error.
+     */
+    public final Operand<TFloat32> epsilon;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesMakeQuantileSummaries(op), op, Arrays.asList());
+      int inputIndex = 0;
+      int floatValuesLength = op.inputListLength("float_values");
+      floatValues = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, floatValuesLength));
+      inputIndex += floatValuesLength;
+      exampleWeights = (Operand<TFloat32>) op.input(inputIndex++);
+      epsilon = (Operand<TFloat32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeStatsSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeStatsSummary.java
index 4827fd7cbcc..62268ff047f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeStatsSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesMakeStatsSummary.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -87,4 +90,49 @@ public Output<TFloat32> statsSummary() {
   public Output<TFloat32> asOutput() {
     return statsSummary;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesMakeStatsSummary> {
+    /**
+     * int32 Rank 1 Tensor containing node ids, which each example falls into for the requested layer.
+     */
+    public final Operand<TInt32> nodeIds;
+
+    /**
+     * float32; Rank 2 Tensor (shape=[#examples, 1]) for gradients.
+     */
+    public final Operand<TFloat32> gradients;
+
+    /**
+     * float32; Rank 2 Tensor (shape=[#examples, 1]) for hessians.
+     */
+    public final Operand<TFloat32> hessians;
+
+    /**
+     * int32 list of Rank 1 Tensors, each containing the bucketized feature (for each feature column).
+     */
+    public final Iterable<Operand<TInt32>> bucketizedFeaturesList;
+
+    /**
+     * int; the maximum number of splits possible in the whole tree.
+     */
+    public final long maxSplits;
+
+    /**
+     * int; equals to the maximum possible value of bucketized feature.
+     */
+    public final long numBuckets;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesMakeStatsSummary(op), op, Arrays.asList("max_splits", "num_buckets"));
+      int inputIndex = 0;
+      nodeIds = (Operand<TInt32>) op.input(inputIndex++);
+      gradients = (Operand<TFloat32>) op.input(inputIndex++);
+      hessians = (Operand<TFloat32>) op.input(inputIndex++);
+      int bucketizedFeaturesListLength = op.inputListLength("bucketized_features_list");
+      bucketizedFeaturesList = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, bucketizedFeaturesListLength));
+      inputIndex += bucketizedFeaturesListLength;
+      maxSplits = op.attributes().getAttrInt("max_splits");
+      numBuckets = op.attributes().getAttrInt("num_buckets");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesPredict.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesPredict.java
index 0ac4d12e6ee..292fbb00e52 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesPredict.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesPredict.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -52,7 +55,7 @@ private BoostedTreesPredict(Operation operation) {
    * Factory method to create a class wrapping a new BoostedTreesPredict operation.
    *
    * @param scope current scope
-   * @param treeEnsembleHandle the treeEnsembleHandle value
+   * @param treeEnsembleHandle The treeEnsembleHandle value
    * @param bucketizedFeatures A list of rank 1 Tensors containing bucket id for each
    * feature.
    * @param logitsDimension scalar, dimension of the logits, to be used for partial logits
@@ -84,4 +87,33 @@ public Output<TFloat32> logits() {
   public Output<TFloat32> asOutput() {
     return logits;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesPredict> {
+    /**
+     * The treeEnsembleHandle input
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * A list of rank 1 Tensors containing bucket id for each
+     * feature.
+     */
+    public final Iterable<Operand<TInt32>> bucketizedFeatures;
+
+    /**
+     * scalar, dimension of the logits, to be used for partial logits
+     * shape.
+     */
+    public final long logitsDimension;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesPredict(op), op, Arrays.asList("logits_dimension"));
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      int bucketizedFeaturesLength = op.inputListLength("bucketized_features");
+      bucketizedFeatures = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, bucketizedFeaturesLength));
+      inputIndex += bucketizedFeaturesLength;
+      logitsDimension = op.attributes().getAttrInt("logits_dimension");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceAddSummaries.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceAddSummaries.java
index 954e39d5ad7..ccc5869c5ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceAddSummaries.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceAddSummaries.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -62,4 +65,25 @@ public static BoostedTreesQuantileStreamResourceAddSummaries create(Scope scope,
     opBuilder.addInputList(Operands.asOutputs(summaries));
     return new BoostedTreesQuantileStreamResourceAddSummaries(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesQuantileStreamResourceAddSummaries> {
+    /**
+     * resource handle referring to a QuantileStreamResource.
+     */
+    public final Operand<? extends TType> quantileStreamResourceHandle;
+
+    /**
+     * string; List of Rank 2 Tensor each containing the summaries for a single feature.
+     */
+    public final Iterable<Operand<TFloat32>> summaries;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesQuantileStreamResourceAddSummaries(op), op, Arrays.asList());
+      int inputIndex = 0;
+      quantileStreamResourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      int summariesLength = op.inputListLength("summaries");
+      summaries = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, summariesLength));
+      inputIndex += summariesLength;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceDeserialize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceDeserialize.java
index b5468eabcdd..264d083247c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceDeserialize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceDeserialize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -60,4 +63,25 @@ public static BoostedTreesQuantileStreamResourceDeserialize create(Scope scope,
     opBuilder.addInputList(Operands.asOutputs(bucketBoundaries));
     return new BoostedTreesQuantileStreamResourceDeserialize(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesQuantileStreamResourceDeserialize> {
+    /**
+     * resource handle referring to a QuantileStreamResource.
+     */
+    public final Operand<? extends TType> quantileStreamResourceHandle;
+
+    /**
+     * float; List of Rank 1 Tensors each containing the bucket boundaries for a feature.
+     */
+    public final Iterable<Operand<TFloat32>> bucketBoundaries;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesQuantileStreamResourceDeserialize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      quantileStreamResourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      int bucketBoundariesLength = op.inputListLength("bucket_boundaries");
+      bucketBoundaries = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, bucketBoundariesLength));
+      inputIndex += bucketBoundariesLength;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceFlush.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceFlush.java
index 6fada5bf903..cdad72ec124 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceFlush.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceFlush.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -108,4 +111,34 @@ public Options generateQuantiles(Boolean generateQuantiles) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesQuantileStreamResourceFlush> {
+    /**
+     * resource handle referring to a QuantileStreamResource.
+     */
+    public final Operand<? extends TType> quantileStreamResourceHandle;
+
+    /**
+     * int; approximate number of buckets unless using generate_quantiles.
+     */
+    public final Operand<TInt64> numBuckets;
+
+    /**
+     * bool; If True, the output will be the num_quantiles for each stream where the ith
+     * entry is the ith quantile of the input with an approximation error of epsilon.
+     * Duplicate values may be present.
+     * If False, the output will be the points in the histogram that we got which roughly
+     * translates to 1/epsilon boundaries and without any duplicates.
+     * Default to False.
+     */
+    public final boolean generateQuantiles;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesQuantileStreamResourceFlush(op), op, Arrays.asList("generate_quantiles"));
+      int inputIndex = 0;
+      quantileStreamResourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      numBuckets = (Operand<TInt64>) op.input(inputIndex++);
+      generateQuantiles = op.attributes().getAttrBool("generate_quantiles");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceGetBucketBoundaries.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceGetBucketBoundaries.java
index c615b19b3ec..90146726c58 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceGetBucketBoundaries.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceGetBucketBoundaries.java
@@ -20,11 +20,13 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -85,4 +87,17 @@ public List<Output<TFloat32>> bucketBoundaries() {
   public Iterator<Operand<TFloat32>> iterator() {
     return (Iterator) bucketBoundaries.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesQuantileStreamResourceGetBucketBoundaries> {
+    /**
+     * resource handle referring to a QuantileStreamResource.
+     */
+    public final Operand<? extends TType> quantileStreamResourceHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesQuantileStreamResourceGetBucketBoundaries(op), op, Arrays.asList());
+      int inputIndex = 0;
+      quantileStreamResourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceHandleOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceHandleOp.java
index 48af0041d87..2d9cc1649f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceHandleOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesQuantileStreamResourceHandleOp.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -137,4 +140,23 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesQuantileStreamResourceHandleOp> {
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesQuantileStreamResourceHandleOp(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSerializeEnsemble.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSerializeEnsemble.java
index b3c0bee4eb8..bcec982dda1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSerializeEnsemble.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSerializeEnsemble.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -82,4 +85,17 @@ public Output<TInt64> stampToken() {
   public Output<TString> treeEnsembleSerialized() {
     return treeEnsembleSerialized;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesSerializeEnsemble> {
+    /**
+     * Handle to the tree ensemble.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesSerializeEnsemble(op), op, Arrays.asList());
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseAggregateStats.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseAggregateStats.java
index 7b6cae32a40..1a0ae09deb0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseAggregateStats.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseAggregateStats.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -123,4 +126,65 @@ public Output<TFloat32> statsSummaryValues() {
   public Output<TInt32> statsSummaryShape() {
     return statsSummaryShape;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesSparseAggregateStats> {
+    /**
+     * int32; Rank 1 Tensor containing node ids for each example, shape [batch_size].
+     */
+    public final Operand<TInt32> nodeIds;
+
+    /**
+     * float32; Rank 2 Tensor (shape=[batch_size, logits_dimension]) with gradients for each example.
+     */
+    public final Operand<TFloat32> gradients;
+
+    /**
+     * float32; Rank 2 Tensor (shape=[batch_size, hessian_dimension]) with hessians for each example.
+     */
+    public final Operand<TFloat32> hessians;
+
+    /**
+     * int32; Rank 2 indices of feature sparse Tensors (shape=[number of sparse entries, 2]).
+     * Number of sparse entries across all instances from the batch. The first value is
+     * the index of the instance, the second is dimension of the feature. The second axis
+     * can only have 2 values, i.e., the input dense version of Tensor can only be matrix.
+     */
+    public final Operand<TInt32> featureIndices;
+
+    /**
+     * int32; Rank 1 values of feature sparse Tensors (shape=[number of sparse entries]).
+     * Number of sparse entries across all instances from the batch. The first value is
+     * the index of the instance, the second is dimension of the feature.
+     */
+    public final Operand<TInt32> featureValues;
+
+    /**
+     * int32; Rank 1 dense shape of feature sparse Tensors (shape=[2]).
+     * The first axis can only have 2 values, [batch_size, feature_dimension].
+     */
+    public final Operand<TInt32> featureShape;
+
+    /**
+     * int; the maximum number of splits possible in the whole tree.
+     */
+    public final long maxSplits;
+
+    /**
+     * int; equals to the maximum possible value of bucketized feature + 1.
+     */
+    public final long numBuckets;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesSparseAggregateStats(op), op, Arrays.asList("max_splits", "num_buckets"));
+      int inputIndex = 0;
+      nodeIds = (Operand<TInt32>) op.input(inputIndex++);
+      gradients = (Operand<TFloat32>) op.input(inputIndex++);
+      hessians = (Operand<TFloat32>) op.input(inputIndex++);
+      featureIndices = (Operand<TInt32>) op.input(inputIndex++);
+      featureValues = (Operand<TInt32>) op.input(inputIndex++);
+      featureShape = (Operand<TInt32>) op.input(inputIndex++);
+      maxSplits = op.attributes().getAttrInt("max_splits");
+      numBuckets = op.attributes().getAttrInt("num_buckets");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseCalculateBestFeatureSplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseCalculateBestFeatureSplit.java
index b5e90ffdb83..a05b6234b12 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseCalculateBestFeatureSplit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesSparseCalculateBestFeatureSplit.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -207,4 +210,72 @@ public Options splitType(String splitType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesSparseCalculateBestFeatureSplit> {
+    /**
+     * A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within {@code stats_summary_list}. The nodes are iterated between the two nodes specified by the tensor, as like {@code for node_id in range(node_id_range[0], node_id_range[1])} (Note that the last index node_id_range[1] is exclusive).
+     */
+    public final Operand<TInt32> nodeIdRange;
+
+    /**
+     * A Rank 2 int64 tensor of dense shape [N, 4] (N specifies the number of non-zero values) for accumulated stats summary (gradient/hessian) per node per bucket for each feature. The second dimension contains node id, feature dimension, bucket id, and stats dim.
+     * stats dim is the sum of logits dimension and hessian dimension, hessian dimension can either be logits dimension if diagonal hessian is used, or logits dimension^2 if full hessian is used.
+     */
+    public final Operand<TInt32> statsSummaryIndices;
+
+    /**
+     * A Rank 1 float tensor of dense shape [N] (N specifies the number of non-zero values), which supplies the values for each element in summary_indices.
+     */
+    public final Operand<TFloat32> statsSummaryValues;
+
+    /**
+     * A Rank 1 float tensor of dense shape [4], which specifies the dense shape of the sparse tensor, which is [num tree nodes, feature dimensions, num buckets, stats dim].
+     */
+    public final Operand<TInt32> statsSummaryShape;
+
+    /**
+     * l1 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l1;
+
+    /**
+     * l2 regularization factor on leaf weights, per instance based.
+     */
+    public final Operand<TFloat32> l2;
+
+    /**
+     * adjustment to the gain, per leaf based.
+     */
+    public final Operand<TFloat32> treeComplexity;
+
+    /**
+     * minimum avg of hessians in a node before required for the node to be considered for splitting.
+     */
+    public final Operand<TFloat32> minNodeWeight;
+
+    /**
+     * The dimension of logit, i.e., number of classes.
+     */
+    public final long logitsDimension;
+
+    /**
+     * A string indicating if this Op should perform inequality split or equality split.
+     */
+    public final String splitType;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesSparseCalculateBestFeatureSplit(op), op, Arrays.asList("logits_dimension", "split_type"));
+      int inputIndex = 0;
+      nodeIdRange = (Operand<TInt32>) op.input(inputIndex++);
+      statsSummaryIndices = (Operand<TInt32>) op.input(inputIndex++);
+      statsSummaryValues = (Operand<TFloat32>) op.input(inputIndex++);
+      statsSummaryShape = (Operand<TInt32>) op.input(inputIndex++);
+      l1 = (Operand<TFloat32>) op.input(inputIndex++);
+      l2 = (Operand<TFloat32>) op.input(inputIndex++);
+      treeComplexity = (Operand<TFloat32>) op.input(inputIndex++);
+      minNodeWeight = (Operand<TFloat32>) op.input(inputIndex++);
+      logitsDimension = op.attributes().getAttrInt("logits_dimension");
+      splitType = op.attributes().getAttrString("split_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesTrainingPredict.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesTrainingPredict.java
index ea3356846b7..e3114aacc16 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesTrainingPredict.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesTrainingPredict.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -59,7 +62,7 @@ private BoostedTreesTrainingPredict(Operation operation) {
    * Factory method to create a class wrapping a new BoostedTreesTrainingPredict operation.
    *
    * @param scope current scope
-   * @param treeEnsembleHandle the treeEnsembleHandle value
+   * @param treeEnsembleHandle The treeEnsembleHandle value
    * @param cachedTreeIds Rank 1 Tensor containing cached tree ids which is the starting
    * tree of prediction.
    * @param cachedNodeIds Rank 1 Tensor containing cached node id which is the starting
@@ -113,4 +116,47 @@ public Output<TInt32> treeIds() {
   public Output<TInt32> nodeIds() {
     return nodeIds;
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesTrainingPredict> {
+    /**
+     * The treeEnsembleHandle input
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * Rank 1 Tensor containing cached tree ids which is the starting
+     * tree of prediction.
+     */
+    public final Operand<TInt32> cachedTreeIds;
+
+    /**
+     * Rank 1 Tensor containing cached node id which is the starting
+     * node of prediction.
+     */
+    public final Operand<TInt32> cachedNodeIds;
+
+    /**
+     * A list of rank 1 Tensors containing bucket id for each
+     * feature.
+     */
+    public final Iterable<Operand<TInt32>> bucketizedFeatures;
+
+    /**
+     * scalar, dimension of the logits, to be used for partial logits
+     * shape.
+     */
+    public final long logitsDimension;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesTrainingPredict(op), op, Arrays.asList("logits_dimension"));
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      cachedTreeIds = (Operand<TInt32>) op.input(inputIndex++);
+      cachedNodeIds = (Operand<TInt32>) op.input(inputIndex++);
+      int bucketizedFeaturesLength = op.inputListLength("bucketized_features");
+      bucketizedFeatures = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, bucketizedFeaturesLength));
+      inputIndex += bucketizedFeaturesLength;
+      logitsDimension = op.attributes().getAttrInt("logits_dimension");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsemble.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsemble.java
index 69b68815545..f4e436613e2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsemble.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsemble.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -88,4 +91,89 @@ public static BoostedTreesUpdateEnsemble create(Scope scope,
     opBuilder.setAttr("pruning_mode", pruningMode);
     return new BoostedTreesUpdateEnsemble(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesUpdateEnsemble> {
+    /**
+     * Handle to the ensemble variable.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * Rank 1 tensor with ids for each feature. This is the real id of
+     * the feature that will be used in the split.
+     */
+    public final Operand<TInt32> featureIds;
+
+    /**
+     * List of rank 1 tensors representing the nodes for which this feature
+     * has a split.
+     */
+    public final Iterable<Operand<TInt32>> nodeIds;
+
+    /**
+     * List of rank 1 tensors representing the gains for each of the feature's
+     * split.
+     */
+    public final Iterable<Operand<TFloat32>> gains;
+
+    /**
+     * List of rank 1 tensors representing the thesholds for each of the
+     * feature's split.
+     */
+    public final Iterable<Operand<TInt32>> thresholds;
+
+    /**
+     * List of rank 2 tensors with left leaf contribs for each of
+     * the feature's splits. Will be added to the previous node values to constitute
+     * the values of the left nodes.
+     */
+    public final Iterable<Operand<TFloat32>> leftNodeContribs;
+
+    /**
+     * List of rank 2 tensors with right leaf contribs for each
+     * of the feature's splits. Will be added to the previous node values to constitute
+     * the values of the right nodes.
+     */
+    public final Iterable<Operand<TFloat32>> rightNodeContribs;
+
+    /**
+     * Max depth of the tree to build.
+     */
+    public final Operand<TInt32> maxDepth;
+
+    /**
+     * shrinkage const for each new tree.
+     */
+    public final Operand<TFloat32> learningRate;
+
+    /**
+     * 0-No pruning, 1-Pre-pruning, 2-Post-pruning.
+     */
+    public final long pruningMode;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesUpdateEnsemble(op), op, Arrays.asList("pruning_mode"));
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      featureIds = (Operand<TInt32>) op.input(inputIndex++);
+      int nodeIdsLength = op.inputListLength("node_ids");
+      nodeIds = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, nodeIdsLength));
+      inputIndex += nodeIdsLength;
+      int gainsLength = op.inputListLength("gains");
+      gains = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, gainsLength));
+      inputIndex += gainsLength;
+      int thresholdsLength = op.inputListLength("thresholds");
+      thresholds = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, thresholdsLength));
+      inputIndex += thresholdsLength;
+      int leftNodeContribsLength = op.inputListLength("left_node_contribs");
+      leftNodeContribs = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, leftNodeContribsLength));
+      inputIndex += leftNodeContribsLength;
+      int rightNodeContribsLength = op.inputListLength("right_node_contribs");
+      rightNodeContribs = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, rightNodeContribsLength));
+      inputIndex += rightNodeContribsLength;
+      maxDepth = (Operand<TInt32>) op.input(inputIndex++);
+      learningRate = (Operand<TFloat32>) op.input(inputIndex++);
+      pruningMode = op.attributes().getAttrInt("pruning_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsembleV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsembleV2.java
index e4ba8d4a353..ba73b86fac6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsembleV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/BoostedTreesUpdateEnsembleV2.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -163,4 +166,113 @@ public Options numGroups(Long numGroups) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BoostedTreesUpdateEnsembleV2> {
+    /**
+     * Handle to the ensemble variable.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    /**
+     * Rank 1 tensor with ids for each feature. This is the real id of
+     * the feature that will be used in the split.
+     */
+    public final Iterable<Operand<TInt32>> featureIds;
+
+    /**
+     * List of rank 1 tensors representing the dimension in each feature.
+     */
+    public final Iterable<Operand<TInt32>> dimensionIds;
+
+    /**
+     * List of rank 1 tensors representing the nodes for which this feature
+     * has a split.
+     */
+    public final Iterable<Operand<TInt32>> nodeIds;
+
+    /**
+     * List of rank 1 tensors representing the gains for each of the feature's
+     * split.
+     */
+    public final Iterable<Operand<TFloat32>> gains;
+
+    /**
+     * List of rank 1 tensors representing the thesholds for each of the
+     * feature's split.
+     */
+    public final Iterable<Operand<TInt32>> thresholds;
+
+    /**
+     * List of rank 2 tensors with left leaf contribs for each of
+     * the feature's splits. Will be added to the previous node values to constitute
+     * the values of the left nodes.
+     */
+    public final Iterable<Operand<TFloat32>> leftNodeContribs;
+
+    /**
+     * List of rank 2 tensors with right leaf contribs for each
+     * of the feature's splits. Will be added to the previous node values to constitute
+     * the values of the right nodes.
+     */
+    public final Iterable<Operand<TFloat32>> rightNodeContribs;
+
+    /**
+     * List of rank 1 tensors representing the split type for each feature.
+     */
+    public final Iterable<Operand<TString>> splitTypes;
+
+    /**
+     * Max depth of the tree to build.
+     */
+    public final Operand<TInt32> maxDepth;
+
+    /**
+     * shrinkage const for each new tree.
+     */
+    public final Operand<TFloat32> learningRate;
+
+    /**
+     * 0-No pruning, 1-Pre-pruning, 2-Post-pruning.
+     */
+    public final Operand<TInt32> pruningMode;
+
+    /**
+     * scalar, dimension of the logits
+     */
+    public final long logitsDimension;
+
+    public Inputs(GraphOperation op) {
+      super(new BoostedTreesUpdateEnsembleV2(op), op, Arrays.asList("logits_dimension"));
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      int featureIdsLength = op.inputListLength("feature_ids");
+      featureIds = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, featureIdsLength));
+      inputIndex += featureIdsLength;
+      int dimensionIdsLength = op.inputListLength("dimension_ids");
+      dimensionIds = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, dimensionIdsLength));
+      inputIndex += dimensionIdsLength;
+      int nodeIdsLength = op.inputListLength("node_ids");
+      nodeIds = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, nodeIdsLength));
+      inputIndex += nodeIdsLength;
+      int gainsLength = op.inputListLength("gains");
+      gains = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, gainsLength));
+      inputIndex += gainsLength;
+      int thresholdsLength = op.inputListLength("thresholds");
+      thresholds = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, thresholdsLength));
+      inputIndex += thresholdsLength;
+      int leftNodeContribsLength = op.inputListLength("left_node_contribs");
+      leftNodeContribs = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, leftNodeContribsLength));
+      inputIndex += leftNodeContribsLength;
+      int rightNodeContribsLength = op.inputListLength("right_node_contribs");
+      rightNodeContribs = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, rightNodeContribsLength));
+      inputIndex += rightNodeContribsLength;
+      int splitTypesLength = op.inputListLength("split_types");
+      splitTypes = Arrays.asList((Operand<TString>[]) op.inputList(inputIndex, splitTypesLength));
+      inputIndex += splitTypesLength;
+      maxDepth = (Operand<TInt32>) op.input(inputIndex++);
+      learningRate = (Operand<TFloat32>) op.input(inputIndex++);
+      pruningMode = (Operand<TInt32>) op.input(inputIndex++);
+      logitsDimension = op.attributes().getAttrInt("logits_dimension");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesEnsembleInitialized.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesEnsembleInitialized.java
index 98ca381fce6..24e8f90f713 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesEnsembleInitialized.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesEnsembleInitialized.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -74,4 +77,17 @@ public Output<TBool> isInitialized() {
   public Output<TBool> asOutput() {
     return isInitialized;
   }
+
+  public static class Inputs extends RawOpInputs<IsBoostedTreesEnsembleInitialized> {
+    /**
+     * Handle to the tree ensemble resource.
+     */
+    public final Operand<? extends TType> treeEnsembleHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new IsBoostedTreesEnsembleInitialized(op), op, Arrays.asList());
+      int inputIndex = 0;
+      treeEnsembleHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesQuantileStreamResourceInitialized.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesQuantileStreamResourceInitialized.java
index 0fce945d36f..9a15583349a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesQuantileStreamResourceInitialized.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/estimator/IsBoostedTreesQuantileStreamResourceInitialized.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.estimator;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -75,4 +78,17 @@ public Output<TBool> isInitialized() {
   public Output<TBool> asOutput() {
     return isInitialized;
   }
+
+  public static class Inputs extends RawOpInputs<IsBoostedTreesQuantileStreamResourceInitialized> {
+    /**
+     * resource; The reference to quantile stream resource handle.
+     */
+    public final Operand<? extends TType> quantileStreamResourceHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new IsBoostedTreesQuantileStreamResourceInitialized(op), op, Arrays.asList());
+      int inputIndex = 0;
+      quantileStreamResourceHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java
index 151f7ddee9e..3e234b8c767 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -90,4 +94,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AdjustContrast<T>> {
+    /**
+     * Images to adjust.  At least 3-D.
+     */
+    public final Operand<T> images;
+
+    /**
+     * A float multiplier for adjusting contrast.
+     */
+    public final Operand<TFloat32> contrastFactor;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AdjustContrast<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      contrastFactor = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java
index 747f8f12713..99a4e8a28f6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -88,4 +92,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AdjustHue<T>> {
+    /**
+     * Images to adjust.  At least 3-D.
+     */
+    public final Operand<T> images;
+
+    /**
+     * A float delta to add to the hue.
+     */
+    public final Operand<TFloat32> delta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AdjustHue<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      delta = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java
index 0de6e84071b..42949c86350 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -88,4 +92,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AdjustSaturation<T>> {
+    /**
+     * Images to adjust.  At least 3-D.
+     */
+    public final Operand<T> images;
+
+    /**
+     * A float scale to add to the saturation.
+     */
+    public final Operand<TFloat32> scale;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AdjustSaturation<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      scale = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java
index 5357f75dd95..ffe6982c45b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -224,4 +227,73 @@ public Options clipBoxes(Boolean clipBoxes) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<CombinedNonMaxSuppression> {
+    /**
+     * A 4-D float tensor of shape {@code [batch_size, num_boxes, q, 4]}. If {@code q} is 1 then
+     * same boxes are used for all classes otherwise, if {@code q} is equal to number of
+     * classes, class-specific boxes are used.
+     */
+    public final Operand<TFloat32> boxes;
+
+    /**
+     * A 3-D float tensor of shape {@code [batch_size, num_boxes, num_classes]}
+     * representing a single score corresponding to each box (each row of boxes).
+     */
+    public final Operand<TFloat32> scores;
+
+    /**
+     * A scalar integer tensor representing the maximum number of
+     * boxes to be selected by non max suppression per class
+     */
+    public final Operand<TInt32> maxOutputSizePerClass;
+
+    /**
+     * An int32 scalar representing the maximum number of boxes retained over all
+     * classes. Note that setting this value to a large number may result in OOM error
+     * depending on the system workload.
+     */
+    public final Operand<TInt32> maxTotalSize;
+
+    /**
+     * A 0-D float tensor representing the threshold for deciding whether
+     * boxes overlap too much with respect to IOU.
+     */
+    public final Operand<TFloat32> iouThreshold;
+
+    /**
+     * A 0-D float tensor representing the threshold for deciding when to remove
+     * boxes based on score.
+     */
+    public final Operand<TFloat32> scoreThreshold;
+
+    /**
+     * If false, the output nmsed boxes, scores and classes
+     * are padded/clipped to `max_total_size`. If true, the
+     * output nmsed boxes, scores and classes are padded to be of length
+     * `max_size_per_class`*`num_classes`, unless it exceeds `max_total_size` in
+     * which case it is clipped to `max_total_size`. Defaults to false.
+     */
+    public final boolean padPerClass;
+
+    /**
+     * If true, assume the box coordinates are between [0, 1] and clip the output boxes
+     * if they fall beyond [0, 1]. If false, do not do clipping and output the box
+     * coordinates as it is.
+     */
+    public final boolean clipBoxes;
+
+    public Inputs(GraphOperation op) {
+      super(new CombinedNonMaxSuppression(op), op, Arrays.asList("pad_per_class", "clip_boxes"));
+      int inputIndex = 0;
+      boxes = (Operand<TFloat32>) op.input(inputIndex++);
+      scores = (Operand<TFloat32>) op.input(inputIndex++);
+      maxOutputSizePerClass = (Operand<TInt32>) op.input(inputIndex++);
+      maxTotalSize = (Operand<TInt32>) op.input(inputIndex++);
+      iouThreshold = (Operand<TFloat32>) op.input(inputIndex++);
+      scoreThreshold = (Operand<TFloat32>) op.input(inputIndex++);
+      padPerClass = op.attributes().getAttrBool("pad_per_class");
+      clipBoxes = op.attributes().getAttrBool("clip_boxes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java
index 4d6f9761230..bafdeda6193 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -183,4 +187,69 @@ public Options extrapolationValue(Float extrapolationValue) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<CropAndResize> {
+    /**
+     * A 4-D tensor of shape {@code [batch, image_height, image_width, depth]}.
+     * Both {@code image_height} and {@code image_width} need to be positive.
+     */
+    public final Operand<? extends TNumber> image;
+
+    /**
+     * A 2-D tensor of shape {@code [num_boxes, 4]}. The {@code i}-th row of the tensor
+     * specifies the coordinates of a box in the {@code box_ind[i]} image and is specified
+     * in normalized coordinates {@code [y1, x1, y2, x2]}. A normalized coordinate value of
+     * {@code y} is mapped to the image coordinate at {@code y * (image_height - 1)}, so as the
+     * {@code [0, 1]} interval of normalized image height is mapped to
+     * {@code [0, image_height - 1]} in image height coordinates. We do allow {@code y1} &gt; {@code y2}, in
+     * which case the sampled crop is an up-down flipped version of the original
+     * image. The width dimension is treated similarly. Normalized coordinates
+     * outside the {@code [0, 1]} range are allowed, in which case we use
+     * {@code extrapolation_value} to extrapolate the input image values.
+     */
+    public final Operand<TFloat32> boxes;
+
+    /**
+     * A 1-D tensor of shape {@code [num_boxes]} with int32 values in {@code [0, batch)}.
+     * The value of {@code box_ind[i]} specifies the image that the {@code i}-th box refers to.
+     */
+    public final Operand<TInt32> boxInd;
+
+    /**
+     * A 1-D tensor of 2 elements, {@code size = [crop_height, crop_width]}. All
+     * cropped image patches are resized to this size. The aspect ratio of the image
+     * content is not preserved. Both {@code crop_height} and {@code crop_width} need to be
+     * positive.
+     */
+    public final Operand<TInt32> cropSize;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A string specifying the sampling method for resizing. It can be either
+     * `"bilinear"` or `"nearest"` and default to `"bilinear"`. Currently two sampling
+     * methods are supported: Bilinear and Nearest Neighbor.
+     */
+    public final String method;
+
+    /**
+     * Value used for extrapolation, when applicable.
+     */
+    public final float extrapolationValue;
+
+    public Inputs(GraphOperation op) {
+      super(new CropAndResize(op), op, Arrays.asList("T", "method", "extrapolation_value"));
+      int inputIndex = 0;
+      image = (Operand<? extends TNumber>) op.input(inputIndex++);
+      boxes = (Operand<TFloat32>) op.input(inputIndex++);
+      boxInd = (Operand<TInt32>) op.input(inputIndex++);
+      cropSize = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      method = op.attributes().getAttrString("method");
+      extrapolationValue = op.attributes().getAttrFloat("extrapolation_value");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java
index a43190b7447..fb4da6130e8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -134,4 +138,55 @@ public Options method(String method) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<CropAndResizeGradBoxes> {
+    /**
+     * A 4-D tensor of shape {@code [num_boxes, crop_height, crop_width, depth]}.
+     */
+    public final Operand<TFloat32> grads;
+
+    /**
+     * A 4-D tensor of shape {@code [batch, image_height, image_width, depth]}.
+     * Both {@code image_height} and {@code image_width} need to be positive.
+     */
+    public final Operand<? extends TNumber> image;
+
+    /**
+     * A 2-D tensor of shape {@code [num_boxes, 4]}. The {@code i}-th row of the tensor
+     * specifies the coordinates of a box in the {@code box_ind[i]} image and is specified
+     * in normalized coordinates {@code [y1, x1, y2, x2]}. A normalized coordinate value of
+     * {@code y} is mapped to the image coordinate at {@code y * (image_height - 1)}, so as the
+     * {@code [0, 1]} interval of normalized image height is mapped to
+     * {@code [0, image_height - 1] in image height coordinates. We do allow y1 > y2, in which case the sampled crop is an up-down flipped version of the original image. The width dimension is treated similarly. Normalized coordinates outside the }[0, 1]{@code range are allowed, in which case we use}extrapolation_value` to extrapolate the input image values.
+     */
+    public final Operand<TFloat32> boxes;
+
+    /**
+     * A 1-D tensor of shape {@code [num_boxes]} with int32 values in {@code [0, batch)}.
+     * The value of {@code box_ind[i]} specifies the image that the {@code i}-th box refers to.
+     */
+    public final Operand<TInt32> boxInd;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A string specifying the interpolation method. Only 'bilinear' is
+     * supported for now.
+     */
+    public final String method;
+
+    public Inputs(GraphOperation op) {
+      super(new CropAndResizeGradBoxes(op), op, Arrays.asList("T", "method"));
+      int inputIndex = 0;
+      grads = (Operand<TFloat32>) op.input(inputIndex++);
+      image = (Operand<? extends TNumber>) op.input(inputIndex++);
+      boxes = (Operand<TFloat32>) op.input(inputIndex++);
+      boxInd = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      method = op.attributes().getAttrString("method");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java
index 48b350c1c6a..0f664e36fad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -68,7 +72,7 @@ private CropAndResizeGradImage(Operation operation) {
    * @param imageSize A 1-D tensor with value {@code [batch, image_height, image_width, depth]}
    * containing the original image size. Both {@code image_height} and {@code image_width} need
    * to be positive.
-   * @param T the value of the T property
+   * @param T The value of the T attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CropAndResizeGradImage} output and operands
    * @return a new instance of CropAndResizeGradImage
@@ -141,4 +145,56 @@ public Options method(String method) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<CropAndResizeGradImage<?>> {
+    /**
+     * A 4-D tensor of shape {@code [num_boxes, crop_height, crop_width, depth]}.
+     */
+    public final Operand<TFloat32> grads;
+
+    /**
+     * A 2-D tensor of shape {@code [num_boxes, 4]}. The {@code i}-th row of the tensor
+     * specifies the coordinates of a box in the {@code box_ind[i]} image and is specified
+     * in normalized coordinates {@code [y1, x1, y2, x2]}. A normalized coordinate value of
+     * {@code y} is mapped to the image coordinate at {@code y * (image_height - 1)}, so as the
+     * {@code [0, 1]} interval of normalized image height is mapped to
+     * {@code [0, image_height - 1] in image height coordinates. We do allow y1 > y2, in which case the sampled crop is an up-down flipped version of the original image. The width dimension is treated similarly. Normalized coordinates outside the }[0, 1]{@code range are allowed, in which case we use}extrapolation_value` to extrapolate the input image values.
+     */
+    public final Operand<TFloat32> boxes;
+
+    /**
+     * A 1-D tensor of shape {@code [num_boxes]} with int32 values in {@code [0, batch)}.
+     * The value of {@code box_ind[i]} specifies the image that the {@code i}-th box refers to.
+     */
+    public final Operand<TInt32> boxInd;
+
+    /**
+     * A 1-D tensor with value {@code [batch, image_height, image_width, depth]}
+     * containing the original image size. Both {@code image_height} and {@code image_width} need
+     * to be positive.
+     */
+    public final Operand<TInt32> imageSize;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A string specifying the interpolation method. Only 'bilinear' is
+     * supported for now.
+     */
+    public final String method;
+
+    public Inputs(GraphOperation op) {
+      super(new CropAndResizeGradImage<>(op), op, Arrays.asList("T", "method"));
+      int inputIndex = 0;
+      grads = (Operand<TFloat32>) op.input(inputIndex++);
+      boxes = (Operand<TFloat32>) op.input(inputIndex++);
+      boxInd = (Operand<TInt32>) op.input(inputIndex++);
+      imageSize = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      method = op.attributes().getAttrString("method");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java
index 21e551ab39f..3ddd568feb4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -279,4 +282,66 @@ public Options dctMethod(String dctMethod) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeAndCropJpeg> {
+    /**
+     * 0-D.  The JPEG-encoded image.
+     */
+    public final Operand<TString> contents;
+
+    /**
+     * 1-D.  The crop window: [crop_y, crop_x, crop_height, crop_width].
+     */
+    public final Operand<TInt32> cropWindow;
+
+    /**
+     * Number of color channels for the decoded image.
+     */
+    public final long channels;
+
+    /**
+     * Downscaling ratio.
+     */
+    public final long ratio;
+
+    /**
+     * If true use a slower but nicer upscaling of the
+     * chroma planes (yuv420/422 only).
+     */
+    public final boolean fancyUpscaling;
+
+    /**
+     * If true try to recover an image from truncated input.
+     */
+    public final boolean tryRecoverTruncated;
+
+    /**
+     * The minimum required fraction of lines before a truncated
+     * input is accepted.
+     */
+    public final float acceptableFraction;
+
+    /**
+     * string specifying a hint about the algorithm used for
+     * decompression.  Defaults to "" which maps to a system-specific
+     * default.  Currently valid values are ["INTEGER_FAST",
+     * "INTEGER_ACCURATE"].  The hint may be ignored (e.g., the internal
+     * jpeg library changes to a version that does not have that specific
+     * option.)
+     */
+    public final String dctMethod;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeAndCropJpeg(op), op, Arrays.asList("channels", "ratio", "fancy_upscaling", "try_recover_truncated", "acceptable_fraction", "dct_method"));
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+      cropWindow = (Operand<TInt32>) op.input(inputIndex++);
+      channels = op.attributes().getAttrInt("channels");
+      ratio = op.attributes().getAttrInt("ratio");
+      fancyUpscaling = op.attributes().getAttrBool("fancy_upscaling");
+      tryRecoverTruncated = op.attributes().getAttrBool("try_recover_truncated");
+      acceptableFraction = op.attributes().getAttrFloat("acceptable_fraction");
+      dctMethod = op.attributes().getAttrString("dct_method");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeBmp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeBmp.java
index 922f9912a13..12995a44d7d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeBmp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeBmp.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -124,4 +127,23 @@ public Options channels(Long channels) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeBmp> {
+    /**
+     * 0-D.  The BMP-encoded image.
+     */
+    public final Operand<TString> contents;
+
+    /**
+     * The channels attribute
+     */
+    public final long channels;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeBmp(op), op, Arrays.asList("channels"));
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+      channels = op.attributes().getAttrInt("channels");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeGif.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeGif.java
index 1007eba6b56..f9ea2e04703 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeGif.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeGif.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -85,4 +88,17 @@ public Output<TUint8> image() {
   public Output<TUint8> asOutput() {
     return image;
   }
+
+  public static class Inputs extends RawOpInputs<DecodeGif> {
+    /**
+     * 0-D.  The GIF-encoded image.
+     */
+    public final Operand<TString> contents;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeGif(op), op, Arrays.asList());
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java
index 375b6eb693d..6a1720d52bf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.TUint8;
 import org.tensorflow.types.family.TNumber;
@@ -188,4 +192,38 @@ public Options expandAnimations(Boolean expandAnimations) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeImage<?>> {
+    /**
+     * 0-D. The encoded image bytes.
+     */
+    public final Operand<TString> contents;
+
+    /**
+     * Number of color channels for the decoded image.
+     */
+    public final long channels;
+
+    /**
+     * The desired DType of the returned Tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * Controls the output shape of the returned op. If True, the returned op will
+     * produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D tensor for all
+     * GIFs, whether animated or not. If, False, the returned op will produce a 3-D
+     * tensor for all file types and will truncate animated GIFs to the first frame.
+     */
+    public final boolean expandAnimations;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeImage<>(op), op, Arrays.asList("channels", "dtype", "expand_animations"));
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+      channels = op.attributes().getAttrInt("channels");
+      dtype = op.attributes().getAttrType("dtype");
+      expandAnimations = op.attributes().getAttrBool("expand_animations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java
index 48241719071..ecf649a14c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -275,4 +278,60 @@ public Options dctMethod(String dctMethod) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeJpeg> {
+    /**
+     * 0-D.  The JPEG-encoded image.
+     */
+    public final Operand<TString> contents;
+
+    /**
+     * Number of color channels for the decoded image.
+     */
+    public final long channels;
+
+    /**
+     * Downscaling ratio.
+     */
+    public final long ratio;
+
+    /**
+     * If true use a slower but nicer upscaling of the
+     * chroma planes (yuv420/422 only).
+     */
+    public final boolean fancyUpscaling;
+
+    /**
+     * If true try to recover an image from truncated input.
+     */
+    public final boolean tryRecoverTruncated;
+
+    /**
+     * The minimum required fraction of lines before a truncated
+     * input is accepted.
+     */
+    public final float acceptableFraction;
+
+    /**
+     * string specifying a hint about the algorithm used for
+     * decompression.  Defaults to "" which maps to a system-specific
+     * default.  Currently valid values are ["INTEGER_FAST",
+     * "INTEGER_ACCURATE"].  The hint may be ignored (e.g., the internal
+     * jpeg library changes to a version that does not have that specific
+     * option.)
+     */
+    public final String dctMethod;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeJpeg(op), op, Arrays.asList("channels", "ratio", "fancy_upscaling", "try_recover_truncated", "acceptable_fraction", "dct_method"));
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+      channels = op.attributes().getAttrInt("channels");
+      ratio = op.attributes().getAttrInt("ratio");
+      fancyUpscaling = op.attributes().getAttrBool("fancy_upscaling");
+      tryRecoverTruncated = op.attributes().getAttrBool("try_recover_truncated");
+      acceptableFraction = op.attributes().getAttrFloat("acceptable_fraction");
+      dctMethod = op.attributes().getAttrString("dct_method");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java
index 30beedadb3d..d0e58936125 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.TUint8;
 import org.tensorflow.types.family.TNumber;
@@ -70,7 +74,7 @@ private DecodePng(Operation operation) {
    *
    * @param scope current scope
    * @param contents 0-D.  The PNG-encoded image.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DecodePng} output and operands
    * @return a new instance of DecodePng
@@ -153,4 +157,29 @@ public Options channels(Long channels) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodePng<?>> {
+    /**
+     * 0-D.  The PNG-encoded image.
+     */
+    public final Operand<TString> contents;
+
+    /**
+     * Number of color channels for the decoded image.
+     */
+    public final long channels;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodePng<>(op), op, Arrays.asList("channels", "dtype"));
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+      channels = op.attributes().getAttrInt("channels");
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java
index 9ed95d1cb4f..44bc9156c06 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -96,4 +100,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<DrawBoundingBoxes<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, depth]}. A batch of images.
+     */
+    public final Operand<T> images;
+
+    /**
+     * 3-D with shape {@code [batch, num_bounding_boxes, 4]} containing bounding
+     * boxes.
+     */
+    public final Operand<TFloat32> boxes;
+
+    /**
+     * 2-D. A list of RGBA colors to cycle through for the boxes.
+     */
+    public final Operand<TFloat32> colors;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DrawBoundingBoxes<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      boxes = (Operand<TFloat32>) op.input(inputIndex++);
+      colors = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java
index 3fd8f3c3e0f..dd8f13b3189 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -342,4 +345,72 @@ public Options xmpMetadata(String xmpMetadata) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EncodeJpeg> {
+    /**
+     * 3-D with shape {@code [height, width, channels]}.
+     */
+    public final Operand<TUint8> image;
+
+    /**
+     * Per pixel image format.
+     */
+    public final String format;
+
+    /**
+     * Quality of the compression from 0 to 100 (higher is better and slower).
+     */
+    public final long quality;
+
+    /**
+     * If True, create a JPEG that loads progressively (coarse to fine).
+     */
+    public final boolean progressive;
+
+    /**
+     * If True, spend CPU/RAM to reduce size with no quality change.
+     */
+    public final boolean optimizeSize;
+
+    /**
+     * See http://en.wikipedia.org/wiki/Chroma_subsampling.
+     */
+    public final boolean chromaDownsampling;
+
+    /**
+     * Unit used to specify `x_density` and `y_density`:
+     * pixels per inch (`'in'`) or centimeter (`'cm'`).
+     */
+    public final String densityUnit;
+
+    /**
+     * Horizontal pixels per density unit.
+     */
+    public final long xDensity;
+
+    /**
+     * Vertical pixels per density unit.
+     */
+    public final long yDensity;
+
+    /**
+     * If not empty, embed this XMP metadata in the image header.
+     */
+    public final String xmpMetadata;
+
+    public Inputs(GraphOperation op) {
+      super(new EncodeJpeg(op), op, Arrays.asList("format", "quality", "progressive", "optimize_size", "chroma_downsampling", "density_unit", "x_density", "y_density", "xmp_metadata"));
+      int inputIndex = 0;
+      image = (Operand<TUint8>) op.input(inputIndex++);
+      format = op.attributes().getAttrString("format");
+      quality = op.attributes().getAttrInt("quality");
+      progressive = op.attributes().getAttrBool("progressive");
+      optimizeSize = op.attributes().getAttrBool("optimize_size");
+      chromaDownsampling = op.attributes().getAttrBool("chroma_downsampling");
+      densityUnit = op.attributes().getAttrString("density_unit");
+      xDensity = op.attributes().getAttrInt("x_density");
+      yDensity = op.attributes().getAttrInt("y_density");
+      xmpMetadata = op.attributes().getAttrString("xmp_metadata");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpegVariableQuality.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpegVariableQuality.java
index 1a9960ab6ad..7b2b8faef21 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpegVariableQuality.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpegVariableQuality.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -83,4 +86,23 @@ public Output<TString> contents() {
   public Output<TString> asOutput() {
     return contents;
   }
+
+  public static class Inputs extends RawOpInputs<EncodeJpegVariableQuality> {
+    /**
+     * Images to adjust.  At least 3-D.
+     */
+    public final Operand<TUint8> images;
+
+    /**
+     * An int quality to encode to.
+     */
+    public final Operand<TInt32> quality;
+
+    public Inputs(GraphOperation op) {
+      super(new EncodeJpegVariableQuality(op), op, Arrays.asList());
+      int inputIndex = 0;
+      images = (Operand<TUint8>) op.input(inputIndex++);
+      quality = (Operand<TInt32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java
index 21823f42582..81d56bc23a5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -128,4 +132,29 @@ public Options compression(Long compression) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EncodePng> {
+    /**
+     * 3-D with shape {@code [height, width, channels]}.
+     */
+    public final Operand<? extends TNumber> image;
+
+    /**
+     * Compression level.
+     */
+    public final long compression;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new EncodePng(op), op, Arrays.asList("compression", "T"));
+      int inputIndex = 0;
+      image = (Operand<? extends TNumber>) op.input(inputIndex++);
+      compression = op.attributes().getAttrInt("compression");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java
index d90f89c2b05..45677ff83f1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -229,4 +232,62 @@ public Options noise(String noise) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ExtractGlimpse> {
+    /**
+     * A 4-D float tensor of shape {@code [batch_size, height, width, channels]}.
+     */
+    public final Operand<TFloat32> input;
+
+    /**
+     * A 1-D tensor of 2 elements containing the size of the glimpses
+     * to extract.  The glimpse height must be specified first, following
+     * by the glimpse width.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * A 2-D integer tensor of shape {@code [batch_size, 2]} containing
+     * the y, x locations of the center of each window.
+     */
+    public final Operand<TFloat32> offsets;
+
+    /**
+     * indicates if the offset coordinates are centered relative to
+     * the image, in which case the (0, 0) offset is relative to the center
+     * of the input images. If false, the (0,0) offset corresponds to the
+     * upper left corner of the input images.
+     */
+    public final boolean centered;
+
+    /**
+     * indicates if the offset coordinates are normalized.
+     */
+    public final boolean normalized;
+
+    /**
+     * indicates if the noise should be generated using a
+     * uniform distribution or a Gaussian distribution.
+     */
+    public final boolean uniformNoise;
+
+    /**
+     * indicates if the noise should `uniform`, `gaussian`, or
+     * `zero`. The default is `uniform` which means the noise type
+     * will be decided by `uniform_noise`.
+     */
+    public final String noise;
+
+    public Inputs(GraphOperation op) {
+      super(new ExtractGlimpse(op), op, Arrays.asList("centered", "normalized", "uniform_noise", "noise"));
+      int inputIndex = 0;
+      input = (Operand<TFloat32>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      offsets = (Operand<TFloat32>) op.input(inputIndex++);
+      centered = op.attributes().getAttrBool("centered");
+      normalized = op.attributes().getAttrBool("normalized");
+      uniformNoise = op.attributes().getAttrBool("uniform_noise");
+      noise = op.attributes().getAttrString("noise");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java
index 28c178721c6..80353b0ab42 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -109,4 +113,53 @@ public Output<T> patches() {
   public Output<T> asOutput() {
     return patches;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ExtractImagePatches<T>> {
+    /**
+     * 4-D Tensor with shape {@code [batch, in_rows, in_cols, depth]}.
+     */
+    public final Operand<T> images;
+
+    /**
+     * The size of the sliding window for each dimension of `images`.
+     */
+    public final long[] ksizes;
+
+    /**
+     * How far the centers of two consecutive patches are in
+     * the images. Must be: `[1, stride_rows, stride_cols, 1]`.
+     */
+    public final long[] strides;
+
+    /**
+     * Must be: `[1, rate_rows, rate_cols, 1]`. This is the
+     * input stride, specifying how far two consecutive patch samples are in the
+     * input. Equivalent to extracting patches with
+     * `patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)`, followed by
+     * subsampling them spatially by a factor of `rates`. This is equivalent to
+     * `rate` in dilated (a.k.a. Atrous) convolutions.
+     */
+    public final long[] rates;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new ExtractImagePatches<>(op), op, Arrays.asList("ksizes", "strides", "rates", "T", "padding"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      ksizes = op.attributes().getAttrIntList("ksizes");
+      strides = op.attributes().getAttrIntList("strides");
+      rates = op.attributes().getAttrIntList("rates");
+      T = op.attributes().getAttrType("T");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java
index 880ee3722cd..d5c7f09060c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
@@ -101,4 +105,24 @@ public Output<T> imageShape() {
   public Output<T> asOutput() {
     return imageShape;
   }
+
+  public static class Inputs extends RawOpInputs<ExtractJpegShape<?>> {
+    /**
+     * 0-D. The JPEG-encoded image.
+     */
+    public final Operand<TString> contents;
+
+    /**
+     * (Optional) The output type of the operation (int32 or int64).
+     * Defaults to int32.
+     */
+    public final DataType outputType;
+
+    public Inputs(GraphOperation op) {
+      super(new ExtractJpegShape<>(op), op, Arrays.asList("output_type"));
+      int inputIndex = 0;
+      contents = (Operand<TString>) op.input(inputIndex++);
+      outputType = op.attributes().getAttrType("output_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/GenerateBoundingBoxProposals.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/GenerateBoundingBoxProposals.java
index 0607171e993..d0548098263 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/GenerateBoundingBoxProposals.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/GenerateBoundingBoxProposals.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -150,4 +153,60 @@ public Options postNmsTopn(Long postNmsTopn) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<GenerateBoundingBoxProposals> {
+    /**
+     * A 4-D float tensor of shape {@code [num_images, height, width, num_achors]} containing scores of the boxes for given anchors, can be unsorted.
+     */
+    public final Operand<TFloat32> scores;
+
+    /**
+     * A 4-D float tensor of shape {@code [num_images, height, width, 4 x num_anchors]}. encoding boxes with respec to each anchor.
+     * Coordinates are given in the form [dy, dx, dh, dw].
+     */
+    public final Operand<TFloat32> bboxDeltas;
+
+    /**
+     * A 2-D float tensor of shape {@code [num_images, 5]} containing image information Height, Width, Scale.
+     */
+    public final Operand<TFloat32> imageInfo;
+
+    /**
+     * A 2-D float tensor of shape {@code [num_anchors, 4]} describing the anchor boxes. Boxes are formatted in the form [y1, x1, y2, x2].
+     */
+    public final Operand<TFloat32> anchors;
+
+    /**
+     * A scalar float tensor for non-maximal-suppression threshold.
+     */
+    public final Operand<TFloat32> nmsThreshold;
+
+    /**
+     * A scalar int tensor for the number of top scoring boxes to be used as input.
+     */
+    public final Operand<TInt32> preNmsTopn;
+
+    /**
+     * A scalar float tensor. Any box that has a smaller size than min_size will be discarded.
+     */
+    public final Operand<TFloat32> minSize;
+
+    /**
+     * An integer. Maximum number of rois in the output.
+     */
+    public final long postNmsTopn;
+
+    public Inputs(GraphOperation op) {
+      super(new GenerateBoundingBoxProposals(op), op, Arrays.asList("post_nms_topn"));
+      int inputIndex = 0;
+      scores = (Operand<TFloat32>) op.input(inputIndex++);
+      bboxDeltas = (Operand<TFloat32>) op.input(inputIndex++);
+      imageInfo = (Operand<TFloat32>) op.input(inputIndex++);
+      anchors = (Operand<TFloat32>) op.input(inputIndex++);
+      nmsThreshold = (Operand<TFloat32>) op.input(inputIndex++);
+      preNmsTopn = (Operand<TInt32>) op.input(inputIndex++);
+      minSize = (Operand<TFloat32>) op.input(inputIndex++);
+      postNmsTopn = op.attributes().getAttrInt("post_nms_topn");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java
index 16a7bc54010..8bbb40efb55 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -83,4 +87,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<HsvToRgb<T>> {
+    /**
+     * 1-D or higher rank. HSV data to convert. Last dimension must be size 3.
+     */
+    public final Operand<T> images;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new HsvToRgb<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java
index e7e270e7584..9312eaed59f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -132,4 +136,49 @@ public Options fillMode(String fillMode) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ImageProjectiveTransformV2<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> images;
+
+    /**
+     * 2-D Tensor, {@code [batch, 8]} or {@code [1, 8]} matrix, where each row corresponds to a 3 x 3
+     * projective transformation matrix, with the last entry assumed to be 1. If there
+     * is one row, the same transformation will be applied to all images.
+     */
+    public final Operand<TFloat32> transforms;
+
+    /**
+     * 1-D Tensor [new_height, new_width].
+     */
+    public final Operand<TInt32> outputShape;
+
+    /**
+     * Input dtype.
+     */
+    public final DataType dtype;
+
+    /**
+     * Interpolation method, "NEAREST" or "BILINEAR".
+     */
+    public final String interpolation;
+
+    /**
+     * Fill mode, "REFLECT", "WRAP", or "CONSTANT".
+     */
+    public final String fillMode;
+
+    public Inputs(GraphOperation op) {
+      super(new ImageProjectiveTransformV2<>(op), op, Arrays.asList("dtype", "interpolation", "fill_mode"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      transforms = (Operand<TFloat32>) op.input(inputIndex++);
+      outputShape = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      interpolation = op.attributes().getAttrString("interpolation");
+      fillMode = op.attributes().getAttrString("fill_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java
index 463275fda01..229c0eaf656 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV3.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -134,4 +138,55 @@ public Options fillMode(String fillMode) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ImageProjectiveTransformV3<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> images;
+
+    /**
+     * 2-D Tensor, {@code [batch, 8]} or {@code [1, 8]} matrix, where each row corresponds to a 3 x 3
+     * projective transformation matrix, with the last entry assumed to be 1. If there
+     * is one row, the same transformation will be applied to all images.
+     */
+    public final Operand<TFloat32> transforms;
+
+    /**
+     * 1-D Tensor [new_height, new_width].
+     */
+    public final Operand<TInt32> outputShape;
+
+    /**
+     * float, the value to be filled when fill_mode is constant&quot;.
+     */
+    public final Operand<TFloat32> fillValue;
+
+    /**
+     * Input dtype.
+     */
+    public final DataType dtype;
+
+    /**
+     * Interpolation method, "NEAREST" or "BILINEAR".
+     */
+    public final String interpolation;
+
+    /**
+     * Fill mode, "REFLECT", "WRAP", "CONSTANT", or "NEAREST".
+     */
+    public final String fillMode;
+
+    public Inputs(GraphOperation op) {
+      super(new ImageProjectiveTransformV3<>(op), op, Arrays.asList("dtype", "interpolation", "fill_mode"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      transforms = (Operand<TFloat32>) op.input(inputIndex++);
+      outputShape = (Operand<TInt32>) op.input(inputIndex++);
+      fillValue = (Operand<TFloat32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      interpolation = op.attributes().getAttrString("interpolation");
+      fillMode = op.attributes().getAttrString("fill_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NearestNeighbors.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NearestNeighbors.java
index 36ce8f31151..d8b061bc045 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NearestNeighbors.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NearestNeighbors.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -91,4 +94,30 @@ public Output<TInt64> nearestCenterIndices() {
   public Output<TFloat32> nearestCenterDistances() {
     return nearestCenterDistances;
   }
+
+  public static class Inputs extends RawOpInputs<NearestNeighbors> {
+    /**
+     * Matrix of shape (n, d). Rows are assumed to be input points.
+     */
+    public final Operand<TFloat32> points;
+
+    /**
+     * Matrix of shape (m, d). Rows are assumed to be centers.
+     */
+    public final Operand<TFloat32> centers;
+
+    /**
+     * Number of nearest centers to return for each point. If k is larger than m, then
+     * only m centers are returned.
+     */
+    public final Operand<TInt64> k;
+
+    public Inputs(GraphOperation op) {
+      super(new NearestNeighbors(op), op, Arrays.asList());
+      int inputIndex = 0;
+      points = (Operand<TFloat32>) op.input(inputIndex++);
+      centers = (Operand<TFloat32>) op.input(inputIndex++);
+      k = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java
index 907ed3a5055..910c2048d7f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -185,4 +189,66 @@ public Options padToMaxOutputSize(Boolean padToMaxOutputSize) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NonMaxSuppression<T>> {
+    /**
+     * A 2-D float tensor of shape {@code [num_boxes, 4]}.
+     */
+    public final Operand<T> boxes;
+
+    /**
+     * A 1-D float tensor of shape {@code [num_boxes]} representing a single
+     * score corresponding to each box (each row of boxes).
+     */
+    public final Operand<T> scores;
+
+    /**
+     * A scalar integer tensor representing the maximum number of
+     * boxes to be selected by non max suppression.
+     */
+    public final Operand<TInt32> maxOutputSize;
+
+    /**
+     * A 0-D float tensor representing the threshold for deciding whether
+     * boxes overlap too much with respect to IOU.
+     */
+    public final Operand<T> iouThreshold;
+
+    /**
+     * A 0-D float tensor representing the threshold for deciding when to remove
+     * boxes based on score.
+     */
+    public final Operand<T> scoreThreshold;
+
+    /**
+     * A 0-D float tensor representing the sigma parameter for Soft NMS; see Bodla et
+     * al (c.f. https://arxiv.org/abs/1704.04503).  When {@code soft_nms_sigma=0.0} (which
+     * is default), we fall back to standard (hard) NMS.
+     */
+    public final Operand<T> softNmsSigma;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the output `selected_indices` is padded to be of length
+     * `max_output_size`. Defaults to false.
+     */
+    public final boolean padToMaxOutputSize;
+
+    public Inputs(GraphOperation op) {
+      super(new NonMaxSuppression<>(op), op, Arrays.asList("T", "pad_to_max_output_size"));
+      int inputIndex = 0;
+      boxes = (Operand<T>) op.input(inputIndex++);
+      scores = (Operand<T>) op.input(inputIndex++);
+      maxOutputSize = (Operand<TInt32>) op.input(inputIndex++);
+      iouThreshold = (Operand<T>) op.input(inputIndex++);
+      scoreThreshold = (Operand<T>) op.input(inputIndex++);
+      softNmsSigma = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      padToMaxOutputSize = op.attributes().getAttrBool("pad_to_max_output_size");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppressionWithOverlaps.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppressionWithOverlaps.java
index c5ebfebdb71..f12b180716f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppressionWithOverlaps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppressionWithOverlaps.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -105,4 +108,46 @@ public Output<TInt32> selectedIndices() {
   public Output<TInt32> asOutput() {
     return selectedIndices;
   }
+
+  public static class Inputs extends RawOpInputs<NonMaxSuppressionWithOverlaps> {
+    /**
+     * A 2-D float tensor of shape {@code [num_boxes, num_boxes]} representing
+     * the n-by-n box overlap values.
+     */
+    public final Operand<TFloat32> overlaps;
+
+    /**
+     * A 1-D float tensor of shape {@code [num_boxes]} representing a single
+     * score corresponding to each box (each row of boxes).
+     */
+    public final Operand<TFloat32> scores;
+
+    /**
+     * A scalar integer tensor representing the maximum number of
+     * boxes to be selected by non max suppression.
+     */
+    public final Operand<TInt32> maxOutputSize;
+
+    /**
+     * A 0-D float tensor representing the threshold for deciding whether
+     * boxes overlap too.
+     */
+    public final Operand<TFloat32> overlapThreshold;
+
+    /**
+     * A 0-D float tensor representing the threshold for deciding when to remove
+     * boxes based on score.
+     */
+    public final Operand<TFloat32> scoreThreshold;
+
+    public Inputs(GraphOperation op) {
+      super(new NonMaxSuppressionWithOverlaps(op), op, Arrays.asList());
+      int inputIndex = 0;
+      overlaps = (Operand<TFloat32>) op.input(inputIndex++);
+      scores = (Operand<TFloat32>) op.input(inputIndex++);
+      maxOutputSize = (Operand<TInt32>) op.input(inputIndex++);
+      overlapThreshold = (Operand<TFloat32>) op.input(inputIndex++);
+      scoreThreshold = (Operand<TFloat32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java
index 79c01f8a7dc..ef8936425db 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/QuantizedResizeBilinear.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -65,8 +69,8 @@ private QuantizedResizeBilinear(Operation operation) {
    * @param images 4-D with shape {@code [batch, height, width, channels]}.
    * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
    * new size for the images.
-   * @param min the min value
-   * @param max the max value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizedResizeBilinear} output and operands
    * @return a new instance of QuantizedResizeBilinear
@@ -178,4 +182,55 @@ public Options halfPixelCenters(Boolean halfPixelCenters) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizedResizeBilinear<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> images;
+
+    /**
+     * = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
+     * new size for the images.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The min input
+     */
+    public final Operand<TFloat32> min;
+
+    /**
+     * The max input
+     */
+    public final Operand<TFloat32> max;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and output tensors are
+     * aligned, preserving the values at the corner pixels. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    /**
+     * The halfPixelCenters attribute
+     */
+    public final boolean halfPixelCenters;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedResizeBilinear<>(op), op, Arrays.asList("T", "align_corners", "half_pixel_centers"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      min = (Operand<TFloat32>) op.input(inputIndex++);
+      max = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+      halfPixelCenters = op.attributes().getAttrBool("half_pixel_centers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java
index e791a670099..580d7a893a1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -157,4 +161,43 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RandomCrop<T>> {
+    /**
+     * 3-D of shape {@code [height, width, channels]}.
+     */
+    public final Operand<T> image;
+
+    /**
+     * 1-D of length 2 containing: {@code crop_height}, {@code crop_width}..
+     */
+    public final Operand<TInt64> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomCrop<>(op), op, Arrays.asList("T", "seed", "seed2"));
+      int inputIndex = 0;
+      image = (Operand<T>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java
index b83213e6ddf..fde981548d8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -133,4 +137,37 @@ public Options alignCorners(Boolean alignCorners) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResizeArea> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<? extends TNumber> images;
+
+    /**
+     * = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
+     * new size for the images.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and output tensors are
+     * aligned, preserving the values at the corner pixels. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    public Inputs(GraphOperation op) {
+      super(new ResizeArea(op), op, Arrays.asList("T", "align_corners"));
+      int inputIndex = 0;
+      images = (Operand<? extends TNumber>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java
index 9453984bb64..df9a6dd7977 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -151,4 +155,43 @@ public Options halfPixelCenters(Boolean halfPixelCenters) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResizeBicubic> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<? extends TNumber> images;
+
+    /**
+     * = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
+     * new size for the images.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and output tensors are
+     * aligned, preserving the values at the corner pixels. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    /**
+     * The halfPixelCenters attribute
+     */
+    public final boolean halfPixelCenters;
+
+    public Inputs(GraphOperation op) {
+      super(new ResizeBicubic(op), op, Arrays.asList("T", "align_corners", "half_pixel_centers"));
+      int inputIndex = 0;
+      images = (Operand<? extends TNumber>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+      halfPixelCenters = op.attributes().getAttrBool("half_pixel_centers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java
index 77b7a4ff486..1e9aabf70d3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -149,4 +153,43 @@ public Options halfPixelCenters(Boolean halfPixelCenters) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ResizeBicubicGrad<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<TFloat32> grads;
+
+    /**
+     * 4-D with shape {@code [batch, orig_height, orig_width, channels]},
+     * The image tensor that was resized.
+     */
+    public final Operand<T> originalImage;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and grad tensors are
+     * aligned. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    /**
+     * The halfPixelCenters attribute
+     */
+    public final boolean halfPixelCenters;
+
+    public Inputs(GraphOperation op) {
+      super(new ResizeBicubicGrad<>(op), op, Arrays.asList("T", "align_corners", "half_pixel_centers"));
+      int inputIndex = 0;
+      grads = (Operand<TFloat32>) op.input(inputIndex++);
+      originalImage = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+      halfPixelCenters = op.attributes().getAttrBool("half_pixel_centers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java
index 20cf19314b1..d42617f0aaa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -151,4 +155,43 @@ public Options halfPixelCenters(Boolean halfPixelCenters) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResizeBilinear> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<? extends TNumber> images;
+
+    /**
+     * = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
+     * new size for the images.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and output tensors are
+     * aligned, preserving the values at the corner pixels. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    /**
+     * The halfPixelCenters attribute
+     */
+    public final boolean halfPixelCenters;
+
+    public Inputs(GraphOperation op) {
+      super(new ResizeBilinear(op), op, Arrays.asList("T", "align_corners", "half_pixel_centers"));
+      int inputIndex = 0;
+      images = (Operand<? extends TNumber>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+      halfPixelCenters = op.attributes().getAttrBool("half_pixel_centers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java
index 4e71b41ddcf..25312aaccc1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -149,4 +153,43 @@ public Options halfPixelCenters(Boolean halfPixelCenters) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ResizeBilinearGrad<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<TFloat32> grads;
+
+    /**
+     * 4-D with shape {@code [batch, orig_height, orig_width, channels]},
+     * The image tensor that was resized.
+     */
+    public final Operand<T> originalImage;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and grad tensors are
+     * aligned. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    /**
+     * The halfPixelCenters attribute
+     */
+    public final boolean halfPixelCenters;
+
+    public Inputs(GraphOperation op) {
+      super(new ResizeBilinearGrad<>(op), op, Arrays.asList("T", "align_corners", "half_pixel_centers"));
+      int inputIndex = 0;
+      grads = (Operand<TFloat32>) op.input(inputIndex++);
+      originalImage = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+      halfPixelCenters = op.attributes().getAttrBool("half_pixel_centers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java
index 916023700e4..cc81189c0d6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -152,4 +156,43 @@ public Options halfPixelCenters(Boolean halfPixelCenters) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ResizeNearestNeighbor<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> images;
+
+    /**
+     * = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
+     * new size for the images.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and output tensors are
+     * aligned, preserving the values at the corner pixels. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    /**
+     * The halfPixelCenters attribute
+     */
+    public final boolean halfPixelCenters;
+
+    public Inputs(GraphOperation op) {
+      super(new ResizeNearestNeighbor<>(op), op, Arrays.asList("T", "align_corners", "half_pixel_centers"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+      halfPixelCenters = op.attributes().getAttrBool("half_pixel_centers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java
index 16ed3716716..0aafc8d0f5a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -148,4 +152,43 @@ public Options halfPixelCenters(Boolean halfPixelCenters) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ResizeNearestNeighborGrad<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> grads;
+
+    /**
+     * = A 1-D int32 Tensor of 2 elements: {@code orig_height, orig_width}. The
+     * original input size.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and grad tensors are
+     * aligned. Defaults to false.
+     */
+    public final boolean alignCorners;
+
+    /**
+     * The halfPixelCenters attribute
+     */
+    public final boolean halfPixelCenters;
+
+    public Inputs(GraphOperation op) {
+      super(new ResizeNearestNeighborGrad<>(op), op, Arrays.asList("T", "align_corners", "half_pixel_centers"));
+      int inputIndex = 0;
+      grads = (Operand<T>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      alignCorners = op.attributes().getAttrBool("align_corners");
+      halfPixelCenters = op.attributes().getAttrBool("half_pixel_centers");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java
index b61b476fa53..f06112cddb1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -100,4 +104,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RgbToHsv<T>> {
+    /**
+     * 1-D or higher rank. RGB data to convert. Last dimension must be size 3.
+     */
+    public final Operand<T> images;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RgbToHsv<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      images = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java
index f4cab77b394..bee6684766e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -189,7 +192,7 @@ public static Options aspectRatioRange(List<Float> aspectRatioRange) {
    * width / height within this range.
    * @return this Options instance.
    */
-  public static Options aspectRatioRange(Float[] aspectRatioRange) {
+  public static Options aspectRatioRange(Float... aspectRatioRange) {
     return new Options().aspectRatioRange(aspectRatioRange);
   }
 
@@ -211,7 +214,7 @@ public static Options areaRange(List<Float> areaRange) {
    * supplied image within this range.
    * @return this Options instance.
    */
-  public static Options areaRange(Float[] areaRange) {
+  public static Options areaRange(Float... areaRange) {
     return new Options().areaRange(areaRange);
   }
 
@@ -386,4 +389,83 @@ public Options useImageIfNoBoundingBoxes(Boolean useImageIfNoBoundingBoxes) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SampleDistortedBoundingBox<T>> {
+    /**
+     * 1-D, containing {@code [height, width, channels]}.
+     */
+    public final Operand<T> imageSize;
+
+    /**
+     * 3-D with shape {@code [batch, N, 4]} describing the N bounding boxes
+     * associated with the image.
+     */
+    public final Operand<TFloat32> boundingBoxes;
+
+    /**
+     * The cropped area of the image must contain at least this
+     * fraction of any bounding box supplied. The value of this parameter should be
+     * non-negative. In the case of 0, the cropped area does not need to overlap
+     * any of the bounding boxes supplied.
+     */
+    public final Operand<TFloat32> minObjectCovered;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If either `seed` or `seed2` are set to non-zero, the random number
+     * generator is seeded by the given `seed`.  Otherwise, it is seeded by a random
+     * seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The cropped area of the image must have an aspect ratio =
+     * width / height within this range.
+     */
+    public final float[] aspectRatioRange;
+
+    /**
+     * The cropped area of the image must contain a fraction of the
+     * supplied image within this range.
+     */
+    public final float[] areaRange;
+
+    /**
+     * Number of attempts at generating a cropped region of the image
+     * of the specified constraints. After `max_attempts` failures, return the entire
+     * image.
+     */
+    public final long maxAttempts;
+
+    /**
+     * Controls behavior if no bounding boxes supplied.
+     * If true, assume an implicit bounding box covering the whole input. If false,
+     * raise an error.
+     */
+    public final boolean useImageIfNoBoundingBoxes;
+
+    public Inputs(GraphOperation op) {
+      super(new SampleDistortedBoundingBox<>(op), op, Arrays.asList("T", "seed", "seed2", "aspect_ratio_range", "area_range", "max_attempts", "use_image_if_no_bounding_boxes"));
+      int inputIndex = 0;
+      imageSize = (Operand<T>) op.input(inputIndex++);
+      boundingBoxes = (Operand<TFloat32>) op.input(inputIndex++);
+      minObjectCovered = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      aspectRatioRange = op.attributes().getAttrFloatList("aspect_ratio_range");
+      areaRange = op.attributes().getAttrFloatList("area_range");
+      maxAttempts = op.attributes().getAttrInt("max_attempts");
+      useImageIfNoBoundingBoxes = op.attributes().getAttrBool("use_image_if_no_bounding_boxes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java
index 6c90fce4b0d..5fd3d8f194c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -53,10 +57,10 @@ private ScaleAndTranslate(Operation operation) {
    * Factory method to create a class wrapping a new ScaleAndTranslate operation.
    *
    * @param scope current scope
-   * @param images the images value
-   * @param sizeOutput the sizeOutput value
-   * @param scale the scale value
-   * @param translation the translation value
+   * @param images The images value
+   * @param sizeOutput The sizeOutput value
+   * @param scale The scale value
+   * @param translation The translation value
    * @param options carries optional attribute values
    * @return a new instance of ScaleAndTranslate
    */
@@ -151,4 +155,53 @@ public Options antialias(Boolean antialias) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ScaleAndTranslate> {
+    /**
+     * The images input
+     */
+    public final Operand<? extends TNumber> images;
+
+    /**
+     * The sizeOutput input
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The scale input
+     */
+    public final Operand<TFloat32> scale;
+
+    /**
+     * The translation input
+     */
+    public final Operand<TFloat32> translation;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The kernelType attribute
+     */
+    public final String kernelType;
+
+    /**
+     * The antialias attribute
+     */
+    public final boolean antialias;
+
+    public Inputs(GraphOperation op) {
+      super(new ScaleAndTranslate(op), op, Arrays.asList("T", "kernel_type", "antialias"));
+      int inputIndex = 0;
+      images = (Operand<? extends TNumber>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      scale = (Operand<TFloat32>) op.input(inputIndex++);
+      translation = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      kernelType = op.attributes().getAttrString("kernel_type");
+      antialias = op.attributes().getAttrBool("antialias");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java
index c9dd12e7d31..ad62f12fabe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.image;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -50,10 +54,10 @@ private ScaleAndTranslateGrad(Operation operation) {
    * Factory method to create a class wrapping a new ScaleAndTranslateGrad operation.
    *
    * @param scope current scope
-   * @param grads the grads value
-   * @param originalImage the originalImage value
-   * @param scale the scale value
-   * @param translation the translation value
+   * @param grads The grads value
+   * @param originalImage The originalImage value
+   * @param scale The scale value
+   * @param translation The translation value
    * @param options carries optional attribute values
    * @param <T> data type for {@code ScaleAndTranslateGrad} output and operands
    * @return a new instance of ScaleAndTranslateGrad
@@ -149,4 +153,53 @@ public Options antialias(Boolean antialias) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ScaleAndTranslateGrad<T>> {
+    /**
+     * The grads input
+     */
+    public final Operand<T> grads;
+
+    /**
+     * The originalImage input
+     */
+    public final Operand<T> originalImage;
+
+    /**
+     * The scale input
+     */
+    public final Operand<TFloat32> scale;
+
+    /**
+     * The translation input
+     */
+    public final Operand<TFloat32> translation;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The kernelType attribute
+     */
+    public final String kernelType;
+
+    /**
+     * The antialias attribute
+     */
+    public final boolean antialias;
+
+    public Inputs(GraphOperation op) {
+      super(new ScaleAndTranslateGrad<>(op), op, Arrays.asList("T", "kernel_type", "antialias"));
+      int inputIndex = 0;
+      grads = (Operand<T>) op.input(inputIndex++);
+      originalImage = (Operand<T>) op.input(inputIndex++);
+      scale = (Operand<TFloat32>) op.input(inputIndex++);
+      translation = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      kernelType = op.attributes().getAttrString("kernel_type");
+      antialias = op.attributes().getAttrBool("antialias");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java
index 43ced526792..9bdb6969f7d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -189,7 +192,7 @@ public static Options aspectRatioRange(List<Float> aspectRatioRange) {
    * width / height within this range.
    * @return this Options instance.
    */
-  public static Options aspectRatioRange(Float[] aspectRatioRange) {
+  public static Options aspectRatioRange(Float... aspectRatioRange) {
     return new Options().aspectRatioRange(aspectRatioRange);
   }
 
@@ -211,7 +214,7 @@ public static Options areaRange(List<Float> areaRange) {
    * supplied image within this range.
    * @return this Options instance.
    */
-  public static Options areaRange(Float[] areaRange) {
+  public static Options areaRange(Float... areaRange) {
     return new Options().areaRange(areaRange);
   }
 
@@ -358,4 +361,82 @@ public Options useImageIfNoBoundingBoxes(Boolean useImageIfNoBoundingBoxes) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<StatelessSampleDistortedBoundingBox<T>> {
+    /**
+     * 1-D, containing {@code [height, width, channels]}.
+     */
+    public final Operand<T> imageSize;
+
+    /**
+     * 3-D with shape {@code [batch, N, 4]} describing the N bounding boxes
+     * associated with the image.
+     */
+    public final Operand<TFloat32> boundingBoxes;
+
+    /**
+     * The cropped area of the image must contain at least this
+     * fraction of any bounding box supplied. The value of this parameter should be
+     * non-negative. In the case of 0, the cropped area does not need to overlap
+     * any of the bounding boxes supplied.
+     */
+    public final Operand<TFloat32> minObjectCovered;
+
+    /**
+     * 1-D with shape {@code [2]}. The seed to the random number generator. Must have dtype
+     * {@code int32} or {@code int64}. (When using XLA, only {@code int32} is allowed.)
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    /**
+     * The cropped area of the image must have an aspect ratio =
+     * width / height within this range.
+     */
+    public final float[] aspectRatioRange;
+
+    /**
+     * The cropped area of the image must contain a fraction of the
+     * supplied image within this range.
+     */
+    public final float[] areaRange;
+
+    /**
+     * Number of attempts at generating a cropped region of the image
+     * of the specified constraints. After `max_attempts` failures, return the entire
+     * image.
+     */
+    public final long maxAttempts;
+
+    /**
+     * Controls behavior if no bounding boxes supplied.
+     * If true, assume an implicit bounding box covering the whole input. If false,
+     * raise an error.
+     */
+    public final boolean useImageIfNoBoundingBoxes;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessSampleDistortedBoundingBox<>(op), op, Arrays.asList("T", "Tseed", "aspect_ratio_range", "area_range", "max_attempts", "use_image_if_no_bounding_boxes"));
+      int inputIndex = 0;
+      imageSize = (Operand<T>) op.input(inputIndex++);
+      boundingBoxes = (Operand<TFloat32>) op.input(inputIndex++);
+      minObjectCovered = (Operand<TFloat32>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+      aspectRatioRange = op.attributes().getAttrFloatList("aspect_ratio_range");
+      areaRange = op.attributes().getAttrFloatList("area_range");
+      maxAttempts = op.attributes().getAttrInt("max_attempts");
+      useImageIfNoBoundingBoxes = op.attributes().getAttrBool("use_image_if_no_bounding_boxes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeBase64.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeBase64.java
index 0b2b977050b..4ebc7750b91 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeBase64.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeBase64.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -78,4 +81,17 @@ public Output<TString> output() {
   public Output<TString> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<DecodeBase64> {
+    /**
+     * Base64 strings to decode.
+     */
+    public final Operand<TString> input;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeBase64(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCompressed.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCompressed.java
index 94adf046198..f732ce500eb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCompressed.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCompressed.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -123,4 +126,24 @@ public Options compressionType(String compressionType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeCompressed> {
+    /**
+     * A Tensor of string which is compressed.
+     */
+    public final Operand<TString> bytes;
+
+    /**
+     * A scalar containing either (i) the empty string (no
+     * compression), (ii) "ZLIB", or (iii) "GZIP".
+     */
+    public final String compressionType;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeCompressed(op), op, Arrays.asList("compression_type"));
+      int inputIndex = 0;
+      bytes = (Operand<TString>) op.input(inputIndex++);
+      compressionType = op.attributes().getAttrString("compression_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCsv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCsv.java
index 0076c52f1b5..20073756dc6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCsv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeCsv.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -149,7 +152,7 @@ public static Options selectCols(List<Long> selectCols) {
    * @param selectCols the selectCols option
    * @return this Options instance.
    */
-  public static Options selectCols(Long[] selectCols) {
+  public static Options selectCols(Long... selectCols) {
     return new Options().selectCols(selectCols);
   }
 
@@ -240,4 +243,60 @@ public Options selectCols(Long... selectCols) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeCsv> {
+    /**
+     * Each string is a record/row in the csv and all records should have
+     * the same format.
+     */
+    public final Operand<TString> records;
+
+    /**
+     * One tensor per column of the input record, with either a
+     * scalar default value for that column or an empty vector if the column is
+     * required.
+     */
+    public final Iterable<Operand<?>> recordDefaults;
+
+    /**
+     * The OUTTYPE attribute
+     */
+    public final DataType[] OUTTYPE;
+
+    /**
+     * char delimiter to separate fields in a record.
+     */
+    public final String fieldDelim;
+
+    /**
+     * If false, treats double quotation marks as regular
+     * characters inside of the string fields (ignoring RFC 4180, Section 2,
+     * Bullet 5).
+     */
+    public final boolean useQuoteDelim;
+
+    /**
+     * Additional string to recognize as NA/NaN.
+     */
+    public final String naValue;
+
+    /**
+     * The selectCols attribute
+     */
+    public final long[] selectCols;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeCsv(op), op, Arrays.asList("OUT_TYPE", "field_delim", "use_quote_delim", "na_value", "select_cols"));
+      int inputIndex = 0;
+      records = (Operand<TString>) op.input(inputIndex++);
+      int recordDefaultsLength = op.inputListLength("record_defaults");
+      recordDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, recordDefaultsLength));
+      inputIndex += recordDefaultsLength;
+      OUTTYPE = op.attributes().getAttrTypeList("OUT_TYPE");
+      fieldDelim = op.attributes().getAttrString("field_delim");
+      useQuoteDelim = op.attributes().getAttrBool("use_quote_delim");
+      naValue = op.attributes().getAttrString("na_value");
+      selectCols = op.attributes().getAttrIntList("select_cols");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeJsonExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeJsonExample.java
index 7d56647384c..e27ec07fce8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeJsonExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeJsonExample.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -85,4 +88,18 @@ public Output<TString> binaryExamples() {
   public Output<TString> asOutput() {
     return binaryExamples;
   }
+
+  public static class Inputs extends RawOpInputs<DecodeJsonExample> {
+    /**
+     * Each string is a JSON object serialized according to the JSON
+     * mapping of the Example proto.
+     */
+    public final Operand<TString> jsonExamples;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeJsonExample(op), op, Arrays.asList());
+      int inputIndex = 0;
+      jsonExamples = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java
index 2bee34b952d..693527476d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
@@ -59,7 +63,7 @@ private DecodePaddedRaw(Operation operation) {
    * @param inputBytes Tensor of string to be decoded.
    * @param fixedLength Length in bytes for each element of the decoded output. Must be a multiple
    * of the size of the output type.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DecodePaddedRaw} output and operands
    * @return a new instance of DecodePaddedRaw
@@ -132,4 +136,37 @@ public Options littleEndian(Boolean littleEndian) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodePaddedRaw<?>> {
+    /**
+     * Tensor of string to be decoded.
+     */
+    public final Operand<TString> inputBytes;
+
+    /**
+     * Length in bytes for each element of the decoded output. Must be a multiple
+     * of the size of the output type.
+     */
+    public final Operand<TInt32> fixedLength;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * Whether the input `input_bytes` is in little-endian order. Ignored for
+     * `out_type` values that are stored in a single byte, like `uint8`
+     */
+    public final boolean littleEndian;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodePaddedRaw<>(op), op, Arrays.asList("out_type", "little_endian"));
+      int inputIndex = 0;
+      inputBytes = (Operand<TString>) op.input(inputIndex++);
+      fixedLength = (Operand<TInt32>) op.input(inputIndex++);
+      outType = op.attributes().getAttrType("out_type");
+      littleEndian = op.attributes().getAttrBool("little_endian");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java
index af00d63a45f..393cd50e94b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -56,7 +60,7 @@ private DecodeRaw(Operation operation) {
    *
    * @param scope current scope
    * @param bytes All the elements must have the same length.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DecodeRaw} output and operands
    * @return a new instance of DecodeRaw
@@ -129,4 +133,31 @@ public Options littleEndian(Boolean littleEndian) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<DecodeRaw<?>> {
+    /**
+     * All the elements must have the same length.
+     */
+    public final Operand<TString> bytes;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * Whether the input `bytes` are in little-endian order.
+     * Ignored for `out_type` values that are stored in a single byte like
+     * `uint8`.
+     */
+    public final boolean littleEndian;
+
+    public Inputs(GraphOperation op) {
+      super(new DecodeRaw<>(op), op, Arrays.asList("out_type", "little_endian"));
+      int inputIndex = 0;
+      bytes = (Operand<TString>) op.input(inputIndex++);
+      outType = op.attributes().getAttrType("out_type");
+      littleEndian = op.attributes().getAttrBool("little_endian");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java
index 93380160f31..9c900322d81 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -144,4 +148,24 @@ public Output<T> sparseValues() {
   public Output<TInt64> sparseShape() {
     return sparseShape;
   }
+
+  public static class Inputs extends RawOpInputs<DeserializeManySparse<?>> {
+    /**
+     * 2-D, The {@code N} serialized {@code SparseTensor} objects.
+     * Must have 3 columns.
+     */
+    public final Operand<TString> serializedSparse;
+
+    /**
+     * The `dtype` of the serialized `SparseTensor` objects.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new DeserializeManySparse<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      serializedSparse = (Operand<TString>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/EncodeBase64.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/EncodeBase64.java
index 6b1d2623b00..2f632b33937 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/EncodeBase64.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/EncodeBase64.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -120,4 +123,23 @@ public Options pad(Boolean pad) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EncodeBase64> {
+    /**
+     * Strings to be encoded.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * Bool whether padding is applied at the ends.
+     */
+    public final boolean pad;
+
+    public Inputs(GraphOperation op) {
+      super(new EncodeBase64(op), op, Arrays.asList("pad"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      pad = op.attributes().getAttrBool("pad");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java
index e024c6e94f8..0a2a8f21957 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -112,7 +115,7 @@ public static Options shapes(List<Shape> shapes) {
    * only one element may be dequeued at a time.
    * @return this Options instance.
    */
-  public static Options shapes(Shape[] shapes) {
+  public static Options shapes(Shape... shapes) {
     return new Options().shapes(shapes);
   }
 
@@ -243,4 +246,47 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FifoQueue> {
+    /**
+     * The type of each component in a value.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * The shape of each component in a value. The length of this attr must
+     * be either 0 or the same as the length of component_types. If the length of
+     * this attr is 0, the shapes of queue elements are not constrained, and
+     * only one element may be dequeued at a time.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * The upper bound on the number of elements in this queue.
+     * Negative numbers mean no limit.
+     */
+    public final long capacity;
+
+    /**
+     * If non-empty, this queue is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this queue will be shared under the given name
+     * across multiple sessions.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new FifoQueue(op), op, Arrays.asList("component_types", "shapes", "capacity", "container", "shared_name"));
+      int inputIndex = 0;
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      capacity = op.attributes().getAttrInt("capacity");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FixedLengthRecordReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FixedLengthRecordReader.java
index 719f83c45e3..105ab72ea3d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FixedLengthRecordReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FixedLengthRecordReader.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -255,4 +258,57 @@ public Options encoding(String encoding) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FixedLengthRecordReader> {
+    /**
+     * Number of bytes in the header, defaults to 0.
+     */
+    public final long headerBytes;
+
+    /**
+     * Number of bytes in the record.
+     */
+    public final long recordBytes;
+
+    /**
+     * Number of bytes in the footer, defaults to 0.
+     */
+    public final long footerBytes;
+
+    /**
+     * Number of bytes to hop before each read. Default of 0 means using
+     * record_bytes.
+     */
+    public final long hopBytes;
+
+    /**
+     * If non-empty, this reader is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this reader is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    /**
+     * The type of encoding for the file. Currently ZLIB and GZIP
+     * are supported. Defaults to none.
+     */
+    public final String encoding;
+
+    public Inputs(GraphOperation op) {
+      super(new FixedLengthRecordReader(op), op, Arrays.asList("header_bytes", "record_bytes", "footer_bytes", "hop_bytes", "container", "shared_name", "encoding"));
+      int inputIndex = 0;
+      headerBytes = op.attributes().getAttrInt("header_bytes");
+      recordBytes = op.attributes().getAttrInt("record_bytes");
+      footerBytes = op.attributes().getAttrInt("footer_bytes");
+      hopBytes = op.attributes().getAttrInt("hop_bytes");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      encoding = op.attributes().getAttrString("encoding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/IdentityReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/IdentityReader.java
index bc70cf49882..a58cc80a838 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/IdentityReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/IdentityReader.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -147,4 +150,25 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<IdentityReader> {
+    /**
+     * If non-empty, this reader is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this reader is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new IdentityReader(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/LmdbReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/LmdbReader.java
index e29f59597ef..f90a320cf2b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/LmdbReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/LmdbReader.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -143,4 +146,25 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LmdbReader> {
+    /**
+     * If non-empty, this reader is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this reader is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new LmdbReader(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/MatchingFiles.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/MatchingFiles.java
index 604aacfb348..8c522a5ede2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/MatchingFiles.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/MatchingFiles.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -79,4 +82,17 @@ public Output<TString> filenames() {
   public Output<TString> asOutput() {
     return filenames;
   }
+
+  public static class Inputs extends RawOpInputs<MatchingFiles> {
+    /**
+     * Shell wildcard pattern(s). Scalar or vector of type string.
+     */
+    public final Operand<TString> pattern;
+
+    public Inputs(GraphOperation op) {
+      super(new MatchingFiles(op), op, Arrays.asList());
+      int inputIndex = 0;
+      pattern = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java
index fd89bf18ede..82846004272 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -123,7 +126,7 @@ public static Options shapes(List<Shape> shapes) {
    * different ranks and shapes, but only one element may be dequeued at a time.
    * @return this Options instance.
    */
-  public static Options shapes(Shape[] shapes) {
+  public static Options shapes(Shape... shapes) {
     return new Options().shapes(shapes);
   }
 
@@ -262,4 +265,51 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<PaddingFifoQueue> {
+    /**
+     * The type of each component in a value.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * The shape of each component in a value. The length of this attr must
+     * be either 0 or the same as the length of component_types.
+     * Shapes of fixed rank but variable size are allowed by setting
+     * any shape dimension to -1.  In this case, the inputs' shape may vary along
+     * the given dimension, and DequeueMany will pad the given dimension with
+     * zeros up to the maximum shape of all elements in the given batch.
+     * If the length of this attr is 0, different queue elements may have
+     * different ranks and shapes, but only one element may be dequeued at a time.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * The upper bound on the number of elements in this queue.
+     * Negative numbers mean no limit.
+     */
+    public final long capacity;
+
+    /**
+     * If non-empty, this queue is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this queue will be shared under the given name
+     * across multiple sessions.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new PaddingFifoQueue(op), op, Arrays.asList("component_types", "shapes", "capacity", "container", "shared_name"));
+      int inputIndex = 0;
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      capacity = op.attributes().getAttrInt("capacity");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java
index 2d4958fffb0..e35ba099a79 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
@@ -218,4 +221,118 @@ public List<Output<?>> raggedValues() {
   public List<Output<?>> raggedRowSplits() {
     return raggedRowSplits;
   }
+
+  public static class Inputs extends RawOpInputs<ParseExample> {
+    /**
+     * A scalar or vector containing binary serialized Example protos.
+     */
+    public final Operand<TString> serialized;
+
+    /**
+     * A tensor containing the names of the serialized protos.
+     * Corresponds 1:1 with the {@code serialized} tensor.
+     * May contain, for example, table key (descriptive) names for the
+     * corresponding serialized protos.  These are purely useful for debugging
+     * purposes, and the presence of values here has no effect on the output.
+     * May also be an empty vector if no names are available.
+     * If non-empty, this tensor must have the same shape as &quot;serialized&quot;.
+     */
+    public final Operand<TString> names;
+
+    /**
+     * Vector of strings.
+     * The keys expected in the Examples' features associated with sparse values.
+     */
+    public final Operand<TString> sparseKeys;
+
+    /**
+     * Vector of strings.
+     * The keys expected in the Examples' features associated with dense values.
+     */
+    public final Operand<TString> denseKeys;
+
+    /**
+     * Vector of strings.
+     * The keys expected in the Examples' features associated with ragged values.
+     */
+    public final Operand<TString> raggedKeys;
+
+    /**
+     * A list of Tensors (some may be empty).  Corresponds 1:1 with {@code dense_keys}.
+     * dense_defaults[j] provides default values
+     * when the example's feature_map lacks dense_key[j].  If an empty Tensor is
+     * provided for dense_defaults[j], then the Feature dense_keys[j] is required.
+     * The input type is inferred from dense_defaults[j], even when it's empty.
+     * If dense_defaults[j] is not empty, and dense_shapes[j] is fully defined,
+     * then the shape of dense_defaults[j] must match that of dense_shapes[j].
+     * If dense_shapes[j] has an undefined major dimension (variable strides dense
+     * feature), dense_defaults[j] must contain a single element:
+     * the padding element.
+     */
+    public final Iterable<Operand<?>> denseDefaults;
+
+    /**
+     * The Tdense attribute
+     */
+    public final DataType[] Tdense;
+
+    /**
+     * A list of `num_sparse` types; the data types of data in each Feature
+     * given in sparse_keys.
+     * Currently the ParseExample supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] sparseTypes;
+
+    /**
+     * A list of `num_ragged` types; the data types of data in each Feature
+     * given in ragged_keys (where `num_ragged = sparse_keys.size()`).
+     * Currently the ParseExample supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] raggedValueTypes;
+
+    /**
+     * A list of `num_ragged` types; the data types of row_splits in each Feature
+     * given in ragged_keys (where `num_ragged = sparse_keys.size()`).
+     * May be DT_INT32 or DT_INT64.
+     */
+    public final DataType[] raggedSplitTypes;
+
+    /**
+     * A list of `num_dense` shapes; the shapes of data in each Feature
+     * given in dense_keys (where `num_dense = dense_keys.size()`).
+     * The number of elements in the Feature corresponding to dense_key[j]
+     * must always equal dense_shapes[j].NumEntries().
+     * If dense_shapes[j] == (D0, D1, ..., DN) then the shape of output
+     * Tensor dense_values[j] will be (|serialized|, D0, D1, ..., DN):
+     * The dense outputs are just the inputs row-stacked by batch.
+     * This works for dense_shapes[j] = (-1, D1, ..., DN).  In this case
+     * the shape of the output Tensor dense_values[j] will be
+     * (|serialized|, M, D1, .., DN), where M is the maximum number of blocks
+     * of elements of length D1 * .... * DN, across all minibatch entries
+     * in the input.  Any minibatch entry with less than M blocks of elements of
+     * length D1 * ... * DN will be padded with the corresponding default_value
+     * scalar element along the second dimension.
+     */
+    public final Shape[] denseShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ParseExample(op), op, Arrays.asList("Tdense", "sparse_types", "ragged_value_types", "ragged_split_types", "dense_shapes"));
+      int inputIndex = 0;
+      serialized = (Operand<TString>) op.input(inputIndex++);
+      names = (Operand<TString>) op.input(inputIndex++);
+      sparseKeys = (Operand<TString>) op.input(inputIndex++);
+      denseKeys = (Operand<TString>) op.input(inputIndex++);
+      raggedKeys = (Operand<TString>) op.input(inputIndex++);
+      int denseDefaultsLength = op.inputListLength("dense_defaults");
+      denseDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, denseDefaultsLength));
+      inputIndex += denseDefaultsLength;
+      Tdense = op.attributes().getAttrTypeList("Tdense");
+      sparseTypes = op.attributes().getAttrTypeList("sparse_types");
+      raggedValueTypes = op.attributes().getAttrTypeList("ragged_value_types");
+      raggedSplitTypes = op.attributes().getAttrTypeList("ragged_split_types");
+      denseShapes = op.attributes().getAttrShapeList("dense_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java
index 5482d1ff93a..27bd0d243d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -161,7 +164,7 @@ private ParseSequenceExample(Operation operation) {
    * DT_INT64 (Int64List), and DT_STRING (BytesList).
    * @param contextRaggedValueTypes RaggedTensor.value dtypes for the ragged context features.
    * @param contextRaggedSplitTypes RaggedTensor.row_split dtypes for the ragged context features.
-   * @param featureListDenseTypes the value of the featureListDenseTypes property
+   * @param featureListDenseTypes The value of the featureListDenseTypes attribute
    * @param featureListSparseTypes A list of Nfeature_list_sparse types; the data types
    * of data in each FeatureList given in feature_list_sparse_keys.
    * Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
@@ -268,7 +271,7 @@ public static Options contextDenseShapes(List<Shape> contextDenseShapes) {
    * The shape of context_dense_values[j] will match context_dense_shapes[j].
    * @return this Options instance.
    */
-  public static Options contextDenseShapes(Shape[] contextDenseShapes) {
+  public static Options contextDenseShapes(Shape... contextDenseShapes) {
     return new Options().contextDenseShapes(contextDenseShapes);
   }
 
@@ -316,7 +319,7 @@ public static Options featureListDenseShapes(List<Shape> featureListDenseShapes)
    * feature_list_dense_shapes[j].NumEntries().
    * @return this Options instance.
    */
-  public static Options featureListDenseShapes(Shape[] featureListDenseShapes) {
+  public static Options featureListDenseShapes(Shape... featureListDenseShapes) {
     return new Options().featureListDenseShapes(featureListDenseShapes);
   }
 
@@ -556,4 +559,164 @@ public Options featureListDenseShapes(Shape... featureListDenseShapes) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ParseSequenceExample> {
+    /**
+     * A scalar or vector containing binary serialized SequenceExample protos.
+     */
+    public final Operand<TString> serialized;
+
+    /**
+     * A scalar or vector containing the names of the serialized protos.
+     * May contain, for example, table key (descriptive) name for the
+     * corresponding serialized proto.  This is purely useful for debugging
+     * purposes, and the presence of values here has no effect on the output.
+     * May also be an empty vector if no name is available.
+     */
+    public final Operand<TString> debugName;
+
+    /**
+     * The keys expected in the Examples' features associated with context_sparse
+     * values.
+     */
+    public final Operand<TString> contextSparseKeys;
+
+    /**
+     * The keys expected in the SequenceExamples' context features associated with
+     * dense values.
+     */
+    public final Operand<TString> contextDenseKeys;
+
+    /**
+     * The keys expected in the Examples' features associated with context_ragged
+     * values.
+     */
+    public final Operand<TString> contextRaggedKeys;
+
+    /**
+     * The keys expected in the FeatureLists associated with sparse values.
+     */
+    public final Operand<TString> featureListSparseKeys;
+
+    /**
+     * The keys expected in the SequenceExamples' feature_lists associated
+     * with lists of dense values.
+     */
+    public final Operand<TString> featureListDenseKeys;
+
+    /**
+     * The keys expected in the FeatureLists associated with ragged values.
+     */
+    public final Operand<TString> featureListRaggedKeys;
+
+    /**
+     * A vector corresponding 1:1 with feature_list_dense_keys, indicating which
+     * features may be missing from the SequenceExamples.  If the associated
+     * FeatureList is missing, it is treated as empty.
+     */
+    public final Operand<TBool> featureListDenseMissingAssumedEmpty;
+
+    /**
+     * A list of Ncontext_dense Tensors (some may be empty).
+     * context_dense_defaults[j] provides default values
+     * when the SequenceExample's context map lacks context_dense_key[j].
+     * If an empty Tensor is provided for context_dense_defaults[j],
+     * then the Feature context_dense_keys[j] is required.
+     * The input type is inferred from context_dense_defaults[j], even when it's
+     * empty.  If context_dense_defaults[j] is not empty, its shape must match
+     * context_dense_shapes[j].
+     */
+    public final Iterable<Operand<?>> contextDenseDefaults;
+
+    /**
+     * The TcontextDense attribute
+     */
+    public final DataType[] TcontextDense;
+
+    /**
+     * A list of Ncontext_sparse types; the data types of data in
+     * each context Feature given in context_sparse_keys.
+     * Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] contextSparseTypes;
+
+    /**
+     * RaggedTensor.value dtypes for the ragged context features.
+     */
+    public final DataType[] contextRaggedValueTypes;
+
+    /**
+     * RaggedTensor.row_split dtypes for the ragged context features.
+     */
+    public final DataType[] contextRaggedSplitTypes;
+
+    /**
+     * A list of Ncontext_dense shapes; the shapes of data in
+     * each context Feature given in context_dense_keys.
+     * The number of elements in the Feature corresponding to context_dense_key[j]
+     * must always equal context_dense_shapes[j].NumEntries().
+     * The shape of context_dense_values[j] will match context_dense_shapes[j].
+     */
+    public final Shape[] contextDenseShapes;
+
+    /**
+     * The featureListDenseTypes attribute
+     */
+    public final DataType[] featureListDenseTypes;
+
+    /**
+     * A list of Nfeature_list_sparse types; the data types
+     * of data in each FeatureList given in feature_list_sparse_keys.
+     * Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] featureListSparseTypes;
+
+    /**
+     * RaggedTensor.value dtypes for the ragged FeatureList features.
+     */
+    public final DataType[] featureListRaggedValueTypes;
+
+    /**
+     * RaggedTensor.row_split dtypes for the ragged FeatureList features.
+     */
+    public final DataType[] featureListRaggedSplitTypes;
+
+    /**
+     * A list of Nfeature_list_dense shapes; the shapes of
+     * data in each FeatureList given in feature_list_dense_keys.
+     * The shape of each Feature in the FeatureList corresponding to
+     * feature_list_dense_key[j] must always equal
+     * feature_list_dense_shapes[j].NumEntries().
+     */
+    public final Shape[] featureListDenseShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ParseSequenceExample(op), op, Arrays.asList("Tcontext_dense", "context_sparse_types", "context_ragged_value_types", "context_ragged_split_types", "context_dense_shapes", "feature_list_dense_types", "feature_list_sparse_types", "feature_list_ragged_value_types", "feature_list_ragged_split_types", "feature_list_dense_shapes"));
+      int inputIndex = 0;
+      serialized = (Operand<TString>) op.input(inputIndex++);
+      debugName = (Operand<TString>) op.input(inputIndex++);
+      contextSparseKeys = (Operand<TString>) op.input(inputIndex++);
+      contextDenseKeys = (Operand<TString>) op.input(inputIndex++);
+      contextRaggedKeys = (Operand<TString>) op.input(inputIndex++);
+      featureListSparseKeys = (Operand<TString>) op.input(inputIndex++);
+      featureListDenseKeys = (Operand<TString>) op.input(inputIndex++);
+      featureListRaggedKeys = (Operand<TString>) op.input(inputIndex++);
+      featureListDenseMissingAssumedEmpty = (Operand<TBool>) op.input(inputIndex++);
+      int contextDenseDefaultsLength = op.inputListLength("context_dense_defaults");
+      contextDenseDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, contextDenseDefaultsLength));
+      inputIndex += contextDenseDefaultsLength;
+      TcontextDense = op.attributes().getAttrTypeList("Tcontext_dense");
+      contextSparseTypes = op.attributes().getAttrTypeList("context_sparse_types");
+      contextRaggedValueTypes = op.attributes().getAttrTypeList("context_ragged_value_types");
+      contextRaggedSplitTypes = op.attributes().getAttrTypeList("context_ragged_split_types");
+      contextDenseShapes = op.attributes().getAttrShapeList("context_dense_shapes");
+      featureListDenseTypes = op.attributes().getAttrTypeList("feature_list_dense_types");
+      featureListSparseTypes = op.attributes().getAttrTypeList("feature_list_sparse_types");
+      featureListRaggedValueTypes = op.attributes().getAttrTypeList("feature_list_ragged_value_types");
+      featureListRaggedSplitTypes = op.attributes().getAttrTypeList("feature_list_ragged_split_types");
+      featureListDenseShapes = op.attributes().getAttrShapeList("feature_list_dense_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java
index 8db82e49e41..2c0b92b6acb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -171,4 +174,80 @@ public List<Output<TInt64>> sparseShapes() {
   public List<Output<?>> denseValues() {
     return denseValues;
   }
+
+  public static class Inputs extends RawOpInputs<ParseSingleExample> {
+    /**
+     * A vector containing a batch of binary serialized Example protos.
+     */
+    public final Operand<TString> serialized;
+
+    /**
+     * A list of Tensors (some may be empty), whose length matches
+     * the length of {@code dense_keys}. dense_defaults[j] provides default values
+     * when the example's feature_map lacks dense_key[j].  If an empty Tensor is
+     * provided for dense_defaults[j], then the Feature dense_keys[j] is required.
+     * The input type is inferred from dense_defaults[j], even when it's empty.
+     * If dense_defaults[j] is not empty, and dense_shapes[j] is fully defined,
+     * then the shape of dense_defaults[j] must match that of dense_shapes[j].
+     * If dense_shapes[j] has an undefined major dimension (variable strides dense
+     * feature), dense_defaults[j] must contain a single element:
+     * the padding element.
+     */
+    public final Iterable<Operand<?>> denseDefaults;
+
+    /**
+     * A list of `num_sparse` strings.
+     * The keys expected in the Examples' features associated with sparse values.
+     */
+    public final String[] sparseKeys;
+
+    /**
+     * The keys expected in the Examples' features associated with dense
+     * values.
+     */
+    public final String[] denseKeys;
+
+    /**
+     * A list of `num_sparse` types; the data types of data in each
+     * Feature given in sparse_keys.
+     * Currently the ParseSingleExample op supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] sparseTypes;
+
+    /**
+     * The data types of data in each Feature given in dense_keys.
+     * The length of this list must match the length of `dense_keys`.
+     * Currently the ParseSingleExample op supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] Tdense;
+
+    /**
+     * The shapes of data in each Feature given in dense_keys.
+     * The length of this list must match the length of `dense_keys`.  The
+     * number of elements in the Feature corresponding to dense_key[j] must
+     * always equal dense_shapes[j].NumEntries().  If dense_shapes[j] ==
+     * (D0, D1, ..., DN) then the shape of output Tensor dense_values[j]
+     * will be (D0, D1, ..., DN): In the case dense_shapes[j] = (-1, D1,
+     * ..., DN), the shape of the output Tensor dense_values[j] will be (M,
+     * D1, .., DN), where M is the number of blocks of elements of length
+     * D1 * .... * DN, in the input.
+     */
+    public final Shape[] denseShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ParseSingleExample(op), op, Arrays.asList("sparse_keys", "dense_keys", "sparse_types", "Tdense", "dense_shapes"));
+      int inputIndex = 0;
+      serialized = (Operand<TString>) op.input(inputIndex++);
+      int denseDefaultsLength = op.inputListLength("dense_defaults");
+      denseDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, denseDefaultsLength));
+      inputIndex += denseDefaultsLength;
+      sparseKeys = op.attributes().getAttrStringList("sparse_keys");
+      denseKeys = op.attributes().getAttrStringList("dense_keys");
+      sparseTypes = op.attributes().getAttrTypeList("sparse_types");
+      Tdense = op.attributes().getAttrTypeList("Tdense");
+      denseShapes = op.attributes().getAttrShapeList("dense_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java
index f7517cfe3a1..c5d98799d5a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -129,7 +132,7 @@ private ParseSingleSequenceExample(Operation operation) {
    * each context Feature given in context_sparse_keys.
    * Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
    * DT_INT64 (Int64List), and DT_STRING (BytesList).
-   * @param featureListDenseTypes the value of the featureListDenseTypes property
+   * @param featureListDenseTypes The value of the featureListDenseTypes attribute
    * @param featureListSparseTypes A list of Nfeature_list_sparse types; the data types
    * of data in each FeatureList given in feature_list_sparse_keys.
    * Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
@@ -257,7 +260,7 @@ public static Options contextDenseShapes(List<Shape> contextDenseShapes) {
    * The shape of context_dense_values[j] will match context_dense_shapes[j].
    * @return this Options instance.
    */
-  public static Options contextDenseShapes(Shape[] contextDenseShapes) {
+  public static Options contextDenseShapes(Shape... contextDenseShapes) {
     return new Options().contextDenseShapes(contextDenseShapes);
   }
 
@@ -285,7 +288,7 @@ public static Options featureListDenseShapes(List<Shape> featureListDenseShapes)
    * feature_list_dense_shapes[j].NumEntries().
    * @return this Options instance.
    */
-  public static Options featureListDenseShapes(Shape[] featureListDenseShapes) {
+  public static Options featureListDenseShapes(Shape... featureListDenseShapes) {
     return new Options().featureListDenseShapes(featureListDenseShapes);
   }
 
@@ -484,4 +487,141 @@ public Options featureListDenseShapes(Shape... featureListDenseShapes) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ParseSingleSequenceExample> {
+    /**
+     * A scalar containing a binary serialized SequenceExample proto.
+     */
+    public final Operand<TString> serialized;
+
+    /**
+     * A vector listing the
+     * FeatureList keys which may be missing from the SequenceExample.  If the
+     * associated FeatureList is missing, it is treated as empty.  By default,
+     * any FeatureList not listed in this vector must exist in the SequenceExample.
+     */
+    public final Operand<TString> featureListDenseMissingAssumedEmpty;
+
+    /**
+     * A list of Ncontext_sparse string Tensors (scalars).
+     * The keys expected in the Examples' features associated with context_sparse
+     * values.
+     */
+    public final Iterable<Operand<TString>> contextSparseKeys;
+
+    /**
+     * A list of Ncontext_dense string Tensors (scalars).
+     * The keys expected in the SequenceExamples' context features associated with
+     * dense values.
+     */
+    public final Iterable<Operand<TString>> contextDenseKeys;
+
+    /**
+     * A list of Nfeature_list_sparse string Tensors
+     * (scalars).  The keys expected in the FeatureLists associated with sparse
+     * values.
+     */
+    public final Iterable<Operand<TString>> featureListSparseKeys;
+
+    /**
+     * A list of Nfeature_list_dense string Tensors (scalars).
+     * The keys expected in the SequenceExamples' feature_lists associated
+     * with lists of dense values.
+     */
+    public final Iterable<Operand<TString>> featureListDenseKeys;
+
+    /**
+     * A list of Ncontext_dense Tensors (some may be empty).
+     * context_dense_defaults[j] provides default values
+     * when the SequenceExample's context map lacks context_dense_key[j].
+     * If an empty Tensor is provided for context_dense_defaults[j],
+     * then the Feature context_dense_keys[j] is required.
+     * The input type is inferred from context_dense_defaults[j], even when it's
+     * empty.  If context_dense_defaults[j] is not empty, its shape must match
+     * context_dense_shapes[j].
+     */
+    public final Iterable<Operand<?>> contextDenseDefaults;
+
+    /**
+     * A scalar containing the name of the serialized proto.
+     * May contain, for example, table key (descriptive) name for the
+     * corresponding serialized proto.  This is purely useful for debugging
+     * purposes, and the presence of values here has no effect on the output.
+     * May also be an empty scalar if no name is available.
+     */
+    public final Operand<TString> debugName;
+
+    /**
+     * A list of Ncontext_sparse types; the data types of data in
+     * each context Feature given in context_sparse_keys.
+     * Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] contextSparseTypes;
+
+    /**
+     * The TcontextDense attribute
+     */
+    public final DataType[] TcontextDense;
+
+    /**
+     * The featureListDenseTypes attribute
+     */
+    public final DataType[] featureListDenseTypes;
+
+    /**
+     * A list of Ncontext_dense shapes; the shapes of data in
+     * each context Feature given in context_dense_keys.
+     * The number of elements in the Feature corresponding to context_dense_key[j]
+     * must always equal context_dense_shapes[j].NumEntries().
+     * The shape of context_dense_values[j] will match context_dense_shapes[j].
+     */
+    public final Shape[] contextDenseShapes;
+
+    /**
+     * A list of Nfeature_list_sparse types; the data types
+     * of data in each FeatureList given in feature_list_sparse_keys.
+     * Currently the ParseSingleSequenceExample supports DT_FLOAT (FloatList),
+     * DT_INT64 (Int64List), and DT_STRING (BytesList).
+     */
+    public final DataType[] featureListSparseTypes;
+
+    /**
+     * A list of Nfeature_list_dense shapes; the shapes of
+     * data in each FeatureList given in feature_list_dense_keys.
+     * The shape of each Feature in the FeatureList corresponding to
+     * feature_list_dense_key[j] must always equal
+     * feature_list_dense_shapes[j].NumEntries().
+     */
+    public final Shape[] featureListDenseShapes;
+
+    public Inputs(GraphOperation op) {
+      super(new ParseSingleSequenceExample(op), op, Arrays.asList("context_sparse_types", "Tcontext_dense", "feature_list_dense_types", "context_dense_shapes", "feature_list_sparse_types", "feature_list_dense_shapes"));
+      int inputIndex = 0;
+      serialized = (Operand<TString>) op.input(inputIndex++);
+      featureListDenseMissingAssumedEmpty = (Operand<TString>) op.input(inputIndex++);
+      int contextSparseKeysLength = op.inputListLength("context_sparse_keys");
+      contextSparseKeys = Arrays.asList((Operand<TString>[]) op.inputList(inputIndex, contextSparseKeysLength));
+      inputIndex += contextSparseKeysLength;
+      int contextDenseKeysLength = op.inputListLength("context_dense_keys");
+      contextDenseKeys = Arrays.asList((Operand<TString>[]) op.inputList(inputIndex, contextDenseKeysLength));
+      inputIndex += contextDenseKeysLength;
+      int featureListSparseKeysLength = op.inputListLength("feature_list_sparse_keys");
+      featureListSparseKeys = Arrays.asList((Operand<TString>[]) op.inputList(inputIndex, featureListSparseKeysLength));
+      inputIndex += featureListSparseKeysLength;
+      int featureListDenseKeysLength = op.inputListLength("feature_list_dense_keys");
+      featureListDenseKeys = Arrays.asList((Operand<TString>[]) op.inputList(inputIndex, featureListDenseKeysLength));
+      inputIndex += featureListDenseKeysLength;
+      int contextDenseDefaultsLength = op.inputListLength("context_dense_defaults");
+      contextDenseDefaults = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, contextDenseDefaultsLength));
+      inputIndex += contextDenseDefaultsLength;
+      debugName = (Operand<TString>) op.input(inputIndex++);
+      contextSparseTypes = op.attributes().getAttrTypeList("context_sparse_types");
+      TcontextDense = op.attributes().getAttrTypeList("Tcontext_dense");
+      featureListDenseTypes = op.attributes().getAttrTypeList("feature_list_dense_types");
+      contextDenseShapes = op.attributes().getAttrShapeList("context_dense_shapes");
+      featureListSparseTypes = op.attributes().getAttrTypeList("feature_list_sparse_types");
+      featureListDenseShapes = op.attributes().getAttrShapeList("feature_list_dense_shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java
index 3a49a3ba191..cf71f17624d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -85,4 +89,24 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ParseTensor<?>> {
+    /**
+     * A scalar string containing a serialized TensorProto proto.
+     */
+    public final Operand<TString> serialized;
+
+    /**
+     * The type of the serialized tensor.  The provided type must match the
+     * type of the serialized tensor and no implicit conversion will take place.
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new ParseTensor<>(op), op, Arrays.asList("out_type"));
+      int inputIndex = 0;
+      serialized = (Operand<TString>) op.input(inputIndex++);
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java
index 893f41c9b33..3908003de08 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java
@@ -17,7 +17,9 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -25,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -193,4 +197,47 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<PriorityQueue> {
+    /**
+     * The type of each component in a value.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * The shape of each component in a value. The length of this attr must
+     * be either 0 or the same as the length of component_types. If the length of
+     * this attr is 0, the shapes of queue elements are not constrained, and
+     * only one element may be dequeued at a time.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * The upper bound on the number of elements in this queue.
+     * Negative numbers mean no limit.
+     */
+    public final long capacity;
+
+    /**
+     * If non-empty, this queue is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this queue will be shared under the given name
+     * across multiple sessions.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new PriorityQueue(op), op, Arrays.asList("component_types", "shapes", "capacity", "container", "shared_name"));
+      int inputIndex = 0;
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      capacity = op.attributes().getAttrInt("capacity");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueClose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueClose.java
index a982ee68ff5..bc2bfa3fff4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueClose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueClose.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -104,4 +107,24 @@ public Options cancelPendingEnqueues(Boolean cancelPendingEnqueues) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QueueClose> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * If true, all pending enqueue requests that are
+     * blocked on the given queue will be canceled.
+     */
+    public final boolean cancelPendingEnqueues;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueClose(op), op, Arrays.asList("cancel_pending_enqueues"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      cancelPendingEnqueues = op.attributes().getAttrBool("cancel_pending_enqueues");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java
index 2f6692c5d92..469de83d736 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -135,4 +138,31 @@ public Options timeoutMs(Long timeoutMs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QueueDequeue> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The type of each component in a tuple.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * If the queue is empty, this operation will block for up to
+     * timeout_ms milliseconds.
+     * Note: This option is not supported yet.
+     */
+    public final long timeoutMs;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueDequeue(op), op, Arrays.asList("component_types", "timeout_ms"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      timeoutMs = op.attributes().getAttrInt("timeout_ms");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java
index b7128d86bc0..ed61ce786c2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -143,4 +146,37 @@ public Options timeoutMs(Long timeoutMs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QueueDequeueMany> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The number of tuples to dequeue.
+     */
+    public final Operand<TInt32> n;
+
+    /**
+     * The type of each component in a tuple.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * If the queue has fewer than n elements, this operation
+     * will block for up to timeout_ms milliseconds.
+     * Note: This option is not supported yet.
+     */
+    public final long timeoutMs;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueDequeueMany(op), op, Arrays.asList("component_types", "timeout_ms"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      n = (Operand<TInt32>) op.input(inputIndex++);
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      timeoutMs = op.attributes().getAttrInt("timeout_ms");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java
index 10ab3ed3307..91bec450c7b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -147,4 +150,37 @@ public Options timeoutMs(Long timeoutMs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QueueDequeueUpTo> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The number of tuples to dequeue.
+     */
+    public final Operand<TInt32> n;
+
+    /**
+     * The type of each component in a tuple.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * If the queue has fewer than n elements, this operation
+     * will block for up to timeout_ms milliseconds.
+     * Note: This option is not supported yet.
+     */
+    public final long timeoutMs;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueDequeueUpTo(op), op, Arrays.asList("component_types", "timeout_ms"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      n = (Operand<TInt32>) op.input(inputIndex++);
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      timeoutMs = op.attributes().getAttrInt("timeout_ms");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueue.java
index d4df07bb301..1872c43e0a9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueue.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -108,4 +112,39 @@ public Options timeoutMs(Long timeoutMs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QueueEnqueue> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * One or more tensors from which the enqueued tensors should be taken.
+     */
+    public final Iterable<Operand<?>> components;
+
+    /**
+     * The Tcomponents attribute
+     */
+    public final DataType[] Tcomponents;
+
+    /**
+     * If the queue is full, this operation will block for up to
+     * timeout_ms milliseconds.
+     * Note: This option is not supported yet.
+     */
+    public final long timeoutMs;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueEnqueue(op), op, Arrays.asList("Tcomponents", "timeout_ms"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      int componentsLength = op.inputListLength("components");
+      components = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, componentsLength));
+      inputIndex += componentsLength;
+      Tcomponents = op.attributes().getAttrTypeList("Tcomponents");
+      timeoutMs = op.attributes().getAttrInt("timeout_ms");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueueMany.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueueMany.java
index 04b14587a04..d0c17369fca 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueueMany.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueEnqueueMany.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -112,4 +116,40 @@ public Options timeoutMs(Long timeoutMs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QueueEnqueueMany> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * One or more tensors from which the enqueued tensors should
+     * be taken.
+     */
+    public final Iterable<Operand<?>> components;
+
+    /**
+     * The Tcomponents attribute
+     */
+    public final DataType[] Tcomponents;
+
+    /**
+     * If the queue is too full, this operation will block for up
+     * to timeout_ms milliseconds.
+     * Note: This option is not supported yet.
+     */
+    public final long timeoutMs;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueEnqueueMany(op), op, Arrays.asList("Tcomponents", "timeout_ms"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      int componentsLength = op.inputListLength("components");
+      components = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, componentsLength));
+      inputIndex += componentsLength;
+      Tcomponents = op.attributes().getAttrTypeList("Tcomponents");
+      timeoutMs = op.attributes().getAttrInt("timeout_ms");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueIsClosed.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueIsClosed.java
index edb895517b6..29fdf801889 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueIsClosed.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueIsClosed.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -79,4 +82,17 @@ public Output<TBool> isClosed() {
   public Output<TBool> asOutput() {
     return isClosed;
   }
+
+  public static class Inputs extends RawOpInputs<QueueIsClosed> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueIsClosed(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueSize.java
index d585e6bfc69..2505096d056 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueSize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -77,4 +80,17 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<QueueSize> {
+    /**
+     * The handle to a queue.
+     */
+    public final Operand<? extends TType> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new QueueSize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java
index 9058ef08c5c..c0f90c4cd81 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,9 +27,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -121,7 +124,7 @@ public static Options shapes(List<Shape> shapes) {
    * only one element may be dequeued at a time.
    * @return this Options instance.
    */
-  public static Options shapes(Shape[] shapes) {
+  public static Options shapes(Shape... shapes) {
     return new Options().shapes(shapes);
   }
 
@@ -327,4 +330,68 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RandomShuffleQueue> {
+    /**
+     * The type of each component in a value.
+     */
+    public final DataType[] componentTypes;
+
+    /**
+     * The shape of each component in a value. The length of this attr must
+     * be either 0 or the same as the length of component_types. If the length of
+     * this attr is 0, the shapes of queue elements are not constrained, and
+     * only one element may be dequeued at a time.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * The upper bound on the number of elements in this queue.
+     * Negative numbers mean no limit.
+     */
+    public final long capacity;
+
+    /**
+     * Dequeue will block unless there would be this
+     * many elements after the dequeue or the queue is closed. This
+     * ensures a minimum level of mixing of elements.
+     */
+    public final long minAfterDequeue;
+
+    /**
+     * If either seed or seed2 is set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, a random seed is used.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * If non-empty, this queue is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this queue will be shared under the given name
+     * across multiple sessions.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomShuffleQueue(op), op, Arrays.asList("component_types", "shapes", "capacity", "min_after_dequeue", "seed", "seed2", "container", "shared_name"));
+      int inputIndex = 0;
+      componentTypes = op.attributes().getAttrTypeList("component_types");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      capacity = op.attributes().getAttrInt("capacity");
+      minAfterDequeue = op.attributes().getAttrInt("min_after_dequeue");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReadFile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReadFile.java
index 898d1e577e9..f7d467d0cb7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReadFile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReadFile.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -51,7 +54,7 @@ private ReadFile(Operation operation) {
    * Factory method to create a class wrapping a new ReadFile operation.
    *
    * @param scope current scope
-   * @param filename the filename value
+   * @param filename The filename value
    * @return a new instance of ReadFile
    */
   @Endpoint(
@@ -76,4 +79,17 @@ public Output<TString> contents() {
   public Output<TString> asOutput() {
     return contents;
   }
+
+  public static class Inputs extends RawOpInputs<ReadFile> {
+    /**
+     * The filename input
+     */
+    public final Operand<TString> filename;
+
+    public Inputs(GraphOperation op) {
+      super(new ReadFile(op), op, Arrays.asList());
+      int inputIndex = 0;
+      filename = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumRecordsProduced.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumRecordsProduced.java
index 6d49f6b8947..7f9c067dc03 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumRecordsProduced.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumRecordsProduced.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -80,4 +83,17 @@ public Output<TInt64> recordsProduced() {
   public Output<TInt64> asOutput() {
     return recordsProduced;
   }
+
+  public static class Inputs extends RawOpInputs<ReaderNumRecordsProduced> {
+    /**
+     * Handle to a Reader.
+     */
+    public final Operand<? extends TType> readerHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new ReaderNumRecordsProduced(op), op, Arrays.asList());
+      int inputIndex = 0;
+      readerHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumWorkUnitsCompleted.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumWorkUnitsCompleted.java
index 01b3d0fec55..0271bde551e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumWorkUnitsCompleted.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderNumWorkUnitsCompleted.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -78,4 +81,17 @@ public Output<TInt64> unitsCompleted() {
   public Output<TInt64> asOutput() {
     return unitsCompleted;
   }
+
+  public static class Inputs extends RawOpInputs<ReaderNumWorkUnitsCompleted> {
+    /**
+     * Handle to a Reader.
+     */
+    public final Operand<? extends TType> readerHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new ReaderNumWorkUnitsCompleted(op), op, Arrays.asList());
+      int inputIndex = 0;
+      readerHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRead.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRead.java
index 6e47e762d54..c905794a387 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRead.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRead.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -90,4 +93,23 @@ public Output<TString> key() {
   public Output<TString> value() {
     return value;
   }
+
+  public static class Inputs extends RawOpInputs<ReaderRead> {
+    /**
+     * Handle to a Reader.
+     */
+    public final Operand<? extends TType> readerHandle;
+
+    /**
+     * Handle to a Queue, with string work items.
+     */
+    public final Operand<? extends TType> queueHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new ReaderRead(op), op, Arrays.asList());
+      int inputIndex = 0;
+      readerHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      queueHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReadUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReadUpTo.java
index 87094364f9f..0fa533b15fe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReadUpTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReadUpTo.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -94,4 +97,29 @@ public Output<TString> keys() {
   public Output<TString> values() {
     return values;
   }
+
+  public static class Inputs extends RawOpInputs<ReaderReadUpTo> {
+    /**
+     * Handle to a {@code Reader}.
+     */
+    public final Operand<? extends TType> readerHandle;
+
+    /**
+     * Handle to a {@code Queue}, with string work items.
+     */
+    public final Operand<? extends TType> queueHandle;
+
+    /**
+     * number of records to read from {@code Reader}.
+     */
+    public final Operand<TInt64> numRecords;
+
+    public Inputs(GraphOperation op) {
+      super(new ReaderReadUpTo(op), op, Arrays.asList());
+      int inputIndex = 0;
+      readerHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      queueHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      numRecords = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReset.java
index 697f0bf388b..2523ed24148 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderReset.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -57,4 +60,17 @@ public static ReaderReset create(Scope scope, Operand<? extends TType> readerHan
     opBuilder.addInput(readerHandle.asOutput());
     return new ReaderReset(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ReaderReset> {
+    /**
+     * Handle to a Reader.
+     */
+    public final Operand<? extends TType> readerHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new ReaderReset(op), op, Arrays.asList());
+      int inputIndex = 0;
+      readerHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRestoreState.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRestoreState.java
index 838df56eaf8..0d9a421b5f9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRestoreState.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderRestoreState.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -64,4 +67,24 @@ public static ReaderRestoreState create(Scope scope, Operand<? extends TType> re
     opBuilder.addInput(state.asOutput());
     return new ReaderRestoreState(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ReaderRestoreState> {
+    /**
+     * Handle to a Reader.
+     */
+    public final Operand<? extends TType> readerHandle;
+
+    /**
+     * Result of a ReaderSerializeState of a Reader with type
+     * matching reader_handle.
+     */
+    public final Operand<TString> state;
+
+    public Inputs(GraphOperation op) {
+      super(new ReaderRestoreState(op), op, Arrays.asList());
+      int inputIndex = 0;
+      readerHandle = (Operand<? extends TType>) op.input(inputIndex++);
+      state = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderSerializeState.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderSerializeState.java
index 486eddbb5ef..e4718641bcd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderSerializeState.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ReaderSerializeState.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -79,4 +82,17 @@ public Output<TString> state() {
   public Output<TString> asOutput() {
     return state;
   }
+
+  public static class Inputs extends RawOpInputs<ReaderSerializeState> {
+    /**
+     * Handle to a Reader.
+     */
+    public final Operand<? extends TType> readerHandle;
+
+    public Inputs(GraphOperation op) {
+      super(new ReaderSerializeState(op), op, Arrays.asList());
+      int inputIndex = 0;
+      readerHandle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java
index 94ffbca759e..482eb5554e4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -114,4 +118,42 @@ public Output<U> serializedSparse() {
   public Output<U> asOutput() {
     return serializedSparse;
   }
+
+  public static class Inputs extends RawOpInputs<SerializeManySparse<?>> {
+    /**
+     * 2-D.  The {@code indices} of the minibatch {@code SparseTensor}.
+     */
+    public final Operand<TInt64> sparseIndices;
+
+    /**
+     * 1-D.  The {@code values} of the minibatch {@code SparseTensor}.
+     */
+    public final Operand<? extends TType> sparseValues;
+
+    /**
+     * 1-D.  The {@code shape} of the minibatch {@code SparseTensor}.
+     */
+    public final Operand<TInt64> sparseShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The `dtype` to use for serialization; the supported types are `string`
+     * (default) and `variant`.
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new SerializeManySparse<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      sparseIndices = (Operand<TInt64>) op.input(inputIndex++);
+      sparseValues = (Operand<? extends TType>) op.input(inputIndex++);
+      sparseShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java
index 65f33687722..b2adf565e6e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -108,4 +112,42 @@ public Output<U> serializedSparse() {
   public Output<U> asOutput() {
     return serializedSparse;
   }
+
+  public static class Inputs extends RawOpInputs<SerializeSparse<?>> {
+    /**
+     * 2-D.  The {@code indices} of the {@code SparseTensor}.
+     */
+    public final Operand<TInt64> sparseIndices;
+
+    /**
+     * 1-D.  The {@code values} of the {@code SparseTensor}.
+     */
+    public final Operand<? extends TType> sparseValues;
+
+    /**
+     * 1-D.  The {@code shape} of the {@code SparseTensor}.
+     */
+    public final Operand<TInt64> sparseShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The `dtype` to use for serialization; the supported types are `string`
+     * (default) and `variant`.
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new SerializeSparse<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      sparseIndices = (Operand<TInt64>) op.input(inputIndex++);
+      sparseValues = (Operand<? extends TType>) op.input(inputIndex++);
+      sparseShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeTensor.java
index 78518c5ae50..3321749b0b1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeTensor.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -77,4 +81,23 @@ public Output<TString> serialized() {
   public Output<TString> asOutput() {
     return serialized;
   }
+
+  public static class Inputs extends RawOpInputs<SerializeTensor> {
+    /**
+     * A Tensor of type {@code T}.
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The type of the input tensor.
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SerializeTensor(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilename.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilename.java
index f762ef77640..0693814d39c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilename.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilename.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -53,9 +56,9 @@ private ShardedFilename(Operation operation) {
    * Factory method to create a class wrapping a new ShardedFilename operation.
    *
    * @param scope current scope
-   * @param basename the basename value
-   * @param shard the shard value
-   * @param numShards the numShards value
+   * @param basename The basename value
+   * @param shard The shard value
+   * @param numShards The numShards value
    * @return a new instance of ShardedFilename
    */
   @Endpoint(
@@ -83,4 +86,29 @@ public Output<TString> filename() {
   public Output<TString> asOutput() {
     return filename;
   }
+
+  public static class Inputs extends RawOpInputs<ShardedFilename> {
+    /**
+     * The basename input
+     */
+    public final Operand<TString> basename;
+
+    /**
+     * The shard input
+     */
+    public final Operand<TInt32> shard;
+
+    /**
+     * The numShards input
+     */
+    public final Operand<TInt32> numShards;
+
+    public Inputs(GraphOperation op) {
+      super(new ShardedFilename(op), op, Arrays.asList());
+      int inputIndex = 0;
+      basename = (Operand<TString>) op.input(inputIndex++);
+      shard = (Operand<TInt32>) op.input(inputIndex++);
+      numShards = (Operand<TInt32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilespec.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilespec.java
index 933d0e45f36..f7aec950873 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilespec.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ShardedFilespec.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,8 +55,8 @@ private ShardedFilespec(Operation operation) {
    * Factory method to create a class wrapping a new ShardedFilespec operation.
    *
    * @param scope current scope
-   * @param basename the basename value
-   * @param numShards the numShards value
+   * @param basename The basename value
+   * @param numShards The numShards value
    * @return a new instance of ShardedFilespec
    */
   @Endpoint(
@@ -80,4 +83,23 @@ public Output<TString> filename() {
   public Output<TString> asOutput() {
     return filename;
   }
+
+  public static class Inputs extends RawOpInputs<ShardedFilespec> {
+    /**
+     * The basename input
+     */
+    public final Operand<TString> basename;
+
+    /**
+     * The numShards input
+     */
+    public final Operand<TInt32> numShards;
+
+    public Inputs(GraphOperation op) {
+      super(new ShardedFilespec(op), op, Arrays.asList());
+      int inputIndex = 0;
+      basename = (Operand<TString>) op.input(inputIndex++);
+      numShards = (Operand<TInt32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TextLineReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TextLineReader.java
index 6fa1e3c7065..417b34c310c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TextLineReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TextLineReader.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -171,4 +174,31 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TextLineReader> {
+    /**
+     * Number of lines to skip from the beginning of every file.
+     */
+    public final long skipHeaderLines;
+
+    /**
+     * If non-empty, this reader is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this reader is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new TextLineReader(op), op, Arrays.asList("skip_header_lines", "container", "shared_name"));
+      int inputIndex = 0;
+      skipHeaderLines = op.attributes().getAttrInt("skip_header_lines");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TfRecordReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TfRecordReader.java
index b587c0915da..7eea770b3f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TfRecordReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/TfRecordReader.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -171,4 +174,31 @@ public Options compressionType(String compressionType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TfRecordReader> {
+    /**
+     * If non-empty, this reader is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this reader is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    /**
+     * The compressionType attribute
+     */
+    public final String compressionType;
+
+    public Inputs(GraphOperation op) {
+      super(new TfRecordReader(op), op, Arrays.asList("container", "shared_name", "compression_type"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      compressionType = op.attributes().getAttrString("compression_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WholeFileReader.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WholeFileReader.java
index 862983e5cb1..919b46c7902 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WholeFileReader.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WholeFileReader.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -147,4 +150,25 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<WholeFileReader> {
+    /**
+     * If non-empty, this reader is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this reader is named in the given bucket
+     * with this shared_name. Otherwise, the node name is used instead.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new WholeFileReader(op), op, Arrays.asList("container", "shared_name"));
+      int inputIndex = 0;
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WriteFile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WriteFile.java
index 28fd7ee6335..7143f27744a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WriteFile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/WriteFile.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.io;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -61,4 +64,23 @@ public static WriteFile create(Scope scope, Operand<TString> filename,
     opBuilder.addInput(contents.asOutput());
     return new WriteFile(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<WriteFile> {
+    /**
+     * scalar. The name of the file to which we write the contents.
+     */
+    public final Operand<TString> filename;
+
+    /**
+     * scalar. The content to be written to the output file.
+     */
+    public final Operand<TString> contents;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteFile(op), op, Arrays.asList());
+      int inputIndex = 0;
+      filename = (Operand<TString>) op.input(inputIndex++);
+      contents = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java
index f43a48cb7ef..ac43eb9df3d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -117,4 +121,43 @@ public Output<T> band() {
   public Output<T> asOutput() {
     return band;
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<BandPart<T>> {
+    /**
+     * Rank {@code k} tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 0-D tensor. Number of subdiagonals to keep. If negative, keep entire
+     * lower triangle.
+     */
+    public final Operand<U> numLower;
+
+    /**
+     * 0-D tensor. Number of superdiagonals to keep. If negative, keep
+     * entire upper triangle.
+     */
+    public final Operand<U> numUpper;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindex attribute
+     */
+    public final DataType Tindex;
+
+    public Inputs(GraphOperation op) {
+      super(new BandPart<>(op), op, Arrays.asList("T", "Tindex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      numLower = (Operand<U>) op.input(inputIndex++);
+      numUpper = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindex = op.attributes().getAttrType("Tindex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java
index 77d9642ffed..64f76d4ee42 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -49,8 +53,8 @@ private BandedTriangularSolve(Operation operation) {
    * Factory method to create a class wrapping a new BandedTriangularSolve operation.
    *
    * @param scope current scope
-   * @param matrix the matrix value
-   * @param rhs the rhs value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BandedTriangularSolve} output and operands
    * @return a new instance of BandedTriangularSolve
@@ -143,4 +147,41 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BandedTriangularSolve<T>> {
+    /**
+     * The matrix input
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * The rhs input
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * The lower attribute
+     */
+    public final boolean lower;
+
+    /**
+     * The adjoint attribute
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BandedTriangularSolve<>(op), op, Arrays.asList("lower", "adjoint", "T"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      lower = op.attributes().getAttrBool("lower");
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java
index 11f03e8d543..d7751ef99fb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private BatchCholesky(Operation operation) {
    * Factory method to create a class wrapping a new BatchCholesky operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code BatchCholesky} output and operands
    * @return a new instance of BatchCholesky
    */
@@ -79,4 +83,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BatchCholesky<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchCholesky<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java
index e7554b4a92b..a7671e74726 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,8 +57,8 @@ private BatchCholeskyGrad(Operation operation) {
    * Factory method to create a class wrapping a new BatchCholeskyGrad operation.
    *
    * @param scope current scope
-   * @param l the l value
-   * @param grad the grad value
+   * @param l The l value
+   * @param grad The grad value
    * @param <T> data type for {@code BatchCholeskyGrad} output and operands
    * @return a new instance of BatchCholeskyGrad
    */
@@ -82,4 +86,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BatchCholeskyGrad<T>> {
+    /**
+     * The l input
+     */
+    public final Operand<T> l;
+
+    /**
+     * The grad input
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchCholeskyGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      l = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java
index 17d71e27f7f..f8a440b50b8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -54,9 +58,9 @@ private BatchMatrixBandPart(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixBandPart operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param numLower the numLower value
-   * @param numUpper the numUpper value
+   * @param input The input value
+   * @param numLower The numLower value
+   * @param numUpper The numUpper value
    * @param <T> data type for {@code BatchMatrixBandPart} output and operands
    * @return a new instance of BatchMatrixBandPart
    */
@@ -85,4 +89,35 @@ public Output<T> band() {
   public Output<T> asOutput() {
     return band;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchMatrixBandPart<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The numLower input
+     */
+    public final Operand<TInt64> numLower;
+
+    /**
+     * The numUpper input
+     */
+    public final Operand<TInt64> numUpper;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixBandPart<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      numLower = (Operand<TInt64>) op.input(inputIndex++);
+      numUpper = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java
index d0d15d8d22a..b6824b065de 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,7 +57,7 @@ private BatchMatrixDeterminant(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixDeterminant operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code BatchMatrixDeterminant} output and operands
    * @return a new instance of BatchMatrixDeterminant
    */
@@ -79,4 +83,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchMatrixDeterminant<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixDeterminant<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java
index a8af1f6cfba..62ebc20bf8e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,7 +57,7 @@ private BatchMatrixDiag(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixDiag operation.
    *
    * @param scope current scope
-   * @param diagonal the diagonal value
+   * @param diagonal The diagonal value
    * @param <T> data type for {@code BatchMatrixDiag} output and operands
    * @return a new instance of BatchMatrixDiag
    */
@@ -79,4 +83,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchMatrixDiag<T>> {
+    /**
+     * The diagonal input
+     */
+    public final Operand<T> diagonal;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixDiag<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      diagonal = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java
index c3de49e9c75..c749fed819d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,7 +57,7 @@ private BatchMatrixDiagPart(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixDiagPart operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code BatchMatrixDiagPart} output and operands
    * @return a new instance of BatchMatrixDiagPart
    */
@@ -79,4 +83,23 @@ public Output<T> diagonal() {
   public Output<T> asOutput() {
     return diagonal;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchMatrixDiagPart<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixDiagPart<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java
index ffaf294076d..5f9145ff005 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private BatchMatrixInverse(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixInverse operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixInverse} output and operands
    * @return a new instance of BatchMatrixInverse
@@ -119,4 +123,29 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BatchMatrixInverse<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The adjoint attribute
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixInverse<>(op), op, Arrays.asList("adjoint", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java
index ea3e2277b38..30711550209 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,8 +57,8 @@ private BatchMatrixSetDiag(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixSetDiag operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param diagonal the diagonal value
+   * @param input The input value
+   * @param diagonal The diagonal value
    * @param <T> data type for {@code BatchMatrixSetDiag} output and operands
    * @return a new instance of BatchMatrixSetDiag
    */
@@ -82,4 +86,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchMatrixSetDiag<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The diagonal input
+     */
+    public final Operand<T> diagonal;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixSetDiag<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      diagonal = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java
index 896451d0c58..47af37fb73b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,8 +57,8 @@ private BatchMatrixSolve(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixSolve operation.
    *
    * @param scope current scope
-   * @param matrix the matrix value
-   * @param rhs the rhs value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixSolve} output and operands
    * @return a new instance of BatchMatrixSolve
@@ -121,4 +125,35 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BatchMatrixSolve<T>> {
+    /**
+     * The matrix input
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * The rhs input
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * The adjoint attribute
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixSolve<>(op), op, Arrays.asList("adjoint", "T"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java
index cfe318269e2..537dbc51cda 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat64;
 import org.tensorflow.types.family.TNumber;
 
@@ -54,9 +58,9 @@ private BatchMatrixSolveLs(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixSolveLs operation.
    *
    * @param scope current scope
-   * @param matrix the matrix value
-   * @param rhs the rhs value
-   * @param l2Regularizer the l2Regularizer value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
+   * @param l2Regularizer The l2Regularizer value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixSolveLs} output and operands
    * @return a new instance of BatchMatrixSolveLs
@@ -124,4 +128,41 @@ public Options fast(Boolean fast) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BatchMatrixSolveLs<T>> {
+    /**
+     * The matrix input
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * The rhs input
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * The l2Regularizer input
+     */
+    public final Operand<TFloat64> l2Regularizer;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The fast attribute
+     */
+    public final boolean fast;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixSolveLs<>(op), op, Arrays.asList("T", "fast"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      l2Regularizer = (Operand<TFloat64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      fast = op.attributes().getAttrBool("fast");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java
index a52a7ce9c9e..b1a0fad24a9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,8 +57,8 @@ private BatchMatrixTriangularSolve(Operation operation) {
    * Factory method to create a class wrapping a new BatchMatrixTriangularSolve operation.
    *
    * @param scope current scope
-   * @param matrix the matrix value
-   * @param rhs the rhs value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchMatrixTriangularSolve} output and operands
    * @return a new instance of BatchMatrixTriangularSolve
@@ -147,4 +151,41 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BatchMatrixTriangularSolve<T>> {
+    /**
+     * The matrix input
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * The rhs input
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * The lower attribute
+     */
+    public final boolean lower;
+
+    /**
+     * The adjoint attribute
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatrixTriangularSolve<>(op), op, Arrays.asList("lower", "adjoint", "T"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      lower = op.attributes().getAttrBool("lower");
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java
index 3bc1baa374d..77cc608d34c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -56,7 +60,7 @@ private BatchSelfAdjointEig(Operation operation) {
    * Factory method to create a class wrapping a new BatchSelfAdjointEigV2 operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchSelfAdjointEigV2} output and operands
    * @return a new instance of BatchSelfAdjointEig
@@ -126,4 +130,29 @@ public Options computeV(Boolean computeV) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BatchSelfAdjointEig<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The computeV attribute
+     */
+    public final boolean computeV;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchSelfAdjointEig<>(op), op, Arrays.asList("compute_v", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      computeV = op.attributes().getAttrBool("compute_v");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java
index e52f57dc8b4..0eed0e8668a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,7 +63,7 @@ private BatchSvd(Operation operation) {
    * Factory method to create a class wrapping a new BatchSvd operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code BatchSvd} output and operands
    * @return a new instance of BatchSvd
@@ -164,4 +168,35 @@ public Options fullMatrices(Boolean fullMatrices) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchSvd<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The computeUv attribute
+     */
+    public final boolean computeUv;
+
+    /**
+     * The fullMatrices attribute
+     */
+    public final boolean fullMatrices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchSvd<>(op), op, Arrays.asList("compute_uv", "full_matrices", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      computeUv = op.attributes().getAttrBool("compute_uv");
+      fullMatrices = op.attributes().getAttrBool("full_matrices");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java
index 655831f5ebb..994fe407425 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -89,4 +93,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Cholesky<T>> {
+    /**
+     * Shape is {@code [..., M, M]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Cholesky<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java
index f66f879332f..b52d99e7c91 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -88,4 +92,33 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CholeskyGrad<T>> {
+    /**
+     * Output of batch Cholesky algorithm l = cholesky(A). Shape is {@code [..., M, M]}.
+     * Algorithm depends only on lower triangular part of the innermost matrices of
+     * this tensor.
+     */
+    public final Operand<T> l;
+
+    /**
+     * df/dl where f is some scalar function. Shape is {@code [..., M, M]}.
+     * Algorithm depends only on lower triangular part of the innermost matrices of
+     * this tensor.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new CholeskyGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      l = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java
index 98618b9e7b7..087147d3149 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -57,8 +61,8 @@ private ConjugateTranspose(Operation operation) {
    * Factory method to create a class wrapping a new ConjugateTranspose operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param perm the perm value
+   * @param x The x value
+   * @param perm The perm value
    * @param <T> data type for {@code ConjugateTranspose} output and operands
    * @return a new instance of ConjugateTranspose
    */
@@ -86,4 +90,35 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ConjugateTranspose<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The perm input
+     */
+    public final Operand<? extends TNumber> perm;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tperm attribute
+     */
+    public final DataType Tperm;
+
+    public Inputs(GraphOperation op) {
+      super(new ConjugateTranspose<>(op), op, Arrays.asList("T", "Tperm"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      perm = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tperm = op.attributes().getAttrType("Tperm");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java
index 537c6cdcb48..719266eeede 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -84,4 +88,29 @@ public Output<T> product() {
   public Output<T> asOutput() {
     return product;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Cross<T>> {
+    /**
+     * A tensor containing 3-element vectors.
+     */
+    public final Operand<T> a;
+
+    /**
+     * Another tensor, of same type and shape as {@code a}.
+     */
+    public final Operand<T> b;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Cross<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java
index 0fb44b629a9..32aabbb3182 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -82,4 +86,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Det<T>> {
+    /**
+     * Shape is {@code [..., M, M]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Det<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java
index 0a38377eb0c..ea31072f390 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -68,7 +72,7 @@ private Eig(Operation operation) {
    *
    * @param scope current scope
    * @param input {@code Tensor} input of shape {@code [N, N]}.
-   * @param Tout the value of the Tout property
+   * @param Tout The value of the Tout attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code Eig} output and operands
    * @return a new instance of Eig
@@ -141,4 +145,36 @@ public Options computeV(Boolean computeV) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Eig<?>> {
+    /**
+     * {@code Tensor} input of shape {@code [N, N]}.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * If `True` then eigenvectors will be computed and returned in `v`.
+     * Otherwise, only the eigenvalues will be computed.
+     */
+    public final boolean computeV;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new Eig<>(op), op, Arrays.asList("compute_v", "T", "Tout"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      computeV = op.attributes().getAttrBool("compute_v");
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java
index b95c42f015e..c273cf2f9f0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -146,4 +150,31 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Einsum<T>> {
+    /**
+     * List of 1 or 2 Tensors.
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * String describing the Einstein Summation operation; in the format of np.einsum.
+     */
+    public final String equation;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Einsum<>(op), op, Arrays.asList("equation", "T"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      equation = op.attributes().getAttrString("equation");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java
index 3128f30a34d..a1fdf41273e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -127,4 +131,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<EuclideanNorm<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new EuclideanNorm<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java
index 7c8e91dbe9a..708bf232915 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -128,4 +132,29 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Inv<T>> {
+    /**
+     * Shape is {@code [..., M, M]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The adjoint attribute
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Inv<>(op), op, Arrays.asList("adjoint", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LoadAndRemapMatrix.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LoadAndRemapMatrix.java
index 3f6396dfa99..31232e9c92b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LoadAndRemapMatrix.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LoadAndRemapMatrix.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -173,4 +176,69 @@ public Options maxRowsInMemory(Long maxRowsInMemory) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadAndRemapMatrix> {
+    /**
+     * Path to the TensorFlow checkpoint (version 2, {@code TensorBundle}) from
+     * which the old matrix {@code Tensor} will be loaded.
+     */
+    public final Operand<TString> ckptPath;
+
+    /**
+     * Name of the 2-D {@code Tensor} to load from checkpoint.
+     */
+    public final Operand<TString> oldTensorName;
+
+    /**
+     * An int {@code Tensor} of row remappings (generally created by
+     * {@code generate_vocab_remapping}).  Even if no row remapping is needed, this must
+     * still be an index-valued Tensor (e.g. [0, 1, 2, ...]), or a shifted
+     * index-valued {@code Tensor} (e.g. [8, 9, 10, ...], for partitioned {@code Variables}).
+     */
+    public final Operand<TInt64> rowRemapping;
+
+    /**
+     * An int {@code Tensor} of column remappings (generally created by
+     * {@code generate_vocab_remapping}).  May be a size-0 {@code Tensor} if only row remapping
+     * is to be done (e.g. column ordering is the same).
+     */
+    public final Operand<TInt64> colRemapping;
+
+    /**
+     * A float {@code Tensor} containing  values to fill in for cells
+     * in the output matrix that are not loaded from the checkpoint. Length must be
+     * exactly the same as the number of missing / new cells.
+     */
+    public final Operand<TFloat32> initializingValues;
+
+    /**
+     * Number of rows (length of the 1st dimension) in the output matrix.
+     */
+    public final long numRows;
+
+    /**
+     * Number of columns (length of the 2nd dimension) in the output matrix.
+     */
+    public final long numCols;
+
+    /**
+     * The maximum number of rows to load from the checkpoint at
+     * once. If less than or equal to 0, the entire matrix will be loaded into
+     * memory. Setting this arg trades increased disk reads for lower memory usage.
+     */
+    public final long maxRowsInMemory;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadAndRemapMatrix(op), op, Arrays.asList("num_rows", "num_cols", "max_rows_in_memory"));
+      int inputIndex = 0;
+      ckptPath = (Operand<TString>) op.input(inputIndex++);
+      oldTensorName = (Operand<TString>) op.input(inputIndex++);
+      rowRemapping = (Operand<TInt64>) op.input(inputIndex++);
+      colRemapping = (Operand<TInt64>) op.input(inputIndex++);
+      initializingValues = (Operand<TFloat32>) op.input(inputIndex++);
+      numRows = op.attributes().getAttrInt("num_rows");
+      numCols = op.attributes().getAttrInt("num_cols");
+      maxRowsInMemory = op.attributes().getAttrInt("max_rows_in_memory");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java
index d1b62eae3d3..05456f98e52 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -95,4 +99,23 @@ public Output<T> sign() {
   public Output<T> logAbsDeterminant() {
     return logAbsDeterminant;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<LogMatrixDeterminant<T>> {
+    /**
+     * Shape is {@code [N, M, M]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LogMatrixDeterminant<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java
index 5cd692a71bc..e61e8627340 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -76,7 +80,7 @@ private Lu(Operation operation) {
    * @param scope current scope
    * @param input A tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions form matrices of
    * size {@code [M, M]}.
-   * @param outputIdxType the value of the outputIdxType property
+   * @param outputIdxType The value of the outputIdxType attribute
    * @param <T> data type for {@code Lu} output and operands
    * @param <U> data type for {@code Lu} output and operands
    * @return a new instance of Lu
@@ -134,4 +138,30 @@ public Output<T> lu() {
   public Output<U> p() {
     return p;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Lu<T, ?>> {
+    /**
+     * A tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions form matrices of
+     * size {@code [M, M]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outputIdxType attribute
+     */
+    public final DataType outputIdxType;
+
+    public Inputs(GraphOperation op) {
+      super(new Lu<>(op), op, Arrays.asList("T", "output_idx_type"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outputIdxType = op.attributes().getAttrType("output_idx_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java
index a0269b20948..139cbbb831e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,8 +63,8 @@ private MatMul(Operation operation) {
    * Factory method to create a class wrapping a new MatMul operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param b the b value
+   * @param a The a value
+   * @param b The b value
    * @param options carries optional attribute values
    * @param <T> data type for {@code MatMul} output and operands
    * @return a new instance of MatMul
@@ -153,4 +157,41 @@ public Options transposeB(Boolean transposeB) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatMul<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The b input
+     */
+    public final Operand<T> b;
+
+    /**
+     * If true, "a" is transposed before multiplication.
+     */
+    public final boolean transposeA;
+
+    /**
+     * If true, "b" is transposed before multiplication.
+     */
+    public final boolean transposeB;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MatMul<>(op), op, Arrays.asList("transpose_a", "transpose_b", "T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java
index 74e7289ba2d..9c6f94274bd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -178,4 +182,55 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatrixDiag<T>> {
+    /**
+     * Rank {@code r}, where {@code r >= 1}
+     */
+    public final Operand<T> diagonal;
+
+    /**
+     * Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main
+     * diagonal, and negative value means subdiagonals. {@code k} can be a single integer
+     * (for a single diagonal) or a pair of integers specifying the low and high ends
+     * of a matrix band. {@code k[0]} must not be larger than {@code k[1]}.
+     */
+    public final Operand<TInt32> k;
+
+    /**
+     * The number of rows of the output matrix. If it is not provided, the op assumes
+     * the output matrix is a square matrix and infers the matrix size from k and the
+     * innermost dimension of {@code diagonal}.
+     */
+    public final Operand<TInt32> numRows;
+
+    /**
+     * The number of columns of the output matrix. If it is not provided, the op
+     * assumes the output matrix is a square matrix and infers the matrix size from
+     * k and the innermost dimension of {@code diagonal}.
+     */
+    public final Operand<TInt32> numCols;
+
+    /**
+     * The number to fill the area outside the specified diagonal band with.
+     * Default is 0.
+     */
+    public final Operand<T> paddingValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MatrixDiag<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      diagonal = (Operand<T>) op.input(inputIndex++);
+      k = (Operand<TInt32>) op.input(inputIndex++);
+      numRows = (Operand<TInt32>) op.input(inputIndex++);
+      numCols = (Operand<TInt32>) op.input(inputIndex++);
+      paddingValue = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java
index 6bde824a10a..d98d54862e4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -149,4 +153,39 @@ public Output<T> diagonal() {
   public Output<T> asOutput() {
     return diagonal;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatrixDiagPart<T>> {
+    /**
+     * Rank {@code r} tensor where {@code r >= 2}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main
+     * diagonal, and negative value means subdiagonals. {@code k} can be a single integer
+     * (for a single diagonal) or a pair of integers specifying the low and high ends
+     * of a matrix band. {@code k[0]} must not be larger than {@code k[1]}.
+     */
+    public final Operand<TInt32> k;
+
+    /**
+     * The value to fill the area outside the specified diagonal band with.
+     * Default is 0.
+     */
+    public final Operand<T> paddingValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MatrixDiagPart<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      k = (Operand<TInt32>) op.input(inputIndex++);
+      paddingValue = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java
index 7039e1e4abc..038c744a651 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -230,4 +234,51 @@ public Options align(String align) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatrixDiagPartV3<T>> {
+    /**
+     * Rank {@code r} tensor where {@code r >= 2}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main
+     * diagonal, and negative value means subdiagonals. {@code k} can be a single integer
+     * (for a single diagonal) or a pair of integers specifying the low and high ends
+     * of a matrix band. {@code k[0]} must not be larger than {@code k[1]}.
+     */
+    public final Operand<TInt32> k;
+
+    /**
+     * The value to fill the area outside the specified diagonal band with.
+     * Default is 0.
+     */
+    public final Operand<T> paddingValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Some diagonals are shorter than `max_diag_len` and need to be padded. `align` is
+     * a string specifying how superdiagonals and subdiagonals should be aligned,
+     * respectively. There are four possible alignments: "RIGHT_LEFT" (default),
+     * "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals
+     * to the right (left-pads the row) and subdiagonals to the left (right-pads the
+     * row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is
+     * the opposite alignment.
+     */
+    public final String align;
+
+    public Inputs(GraphOperation op) {
+      super(new MatrixDiagPartV3<>(op), op, Arrays.asList("T", "align"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      k = (Operand<TInt32>) op.input(inputIndex++);
+      paddingValue = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      align = op.attributes().getAttrString("align");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java
index 9a812c4504f..814a25b4058 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagV3.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -257,4 +261,67 @@ public Options align(String align) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatrixDiagV3<T>> {
+    /**
+     * Rank {@code r}, where {@code r >= 1}
+     */
+    public final Operand<T> diagonal;
+
+    /**
+     * Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main
+     * diagonal, and negative value means subdiagonals. {@code k} can be a single integer
+     * (for a single diagonal) or a pair of integers specifying the low and high ends
+     * of a matrix band. {@code k[0]} must not be larger than {@code k[1]}.
+     */
+    public final Operand<TInt32> k;
+
+    /**
+     * The number of rows of the output matrix. If it is not provided, the op assumes
+     * the output matrix is a square matrix and infers the matrix size from k and the
+     * innermost dimension of {@code diagonal}.
+     */
+    public final Operand<TInt32> numRows;
+
+    /**
+     * The number of columns of the output matrix. If it is not provided, the op
+     * assumes the output matrix is a square matrix and infers the matrix size from
+     * k and the innermost dimension of {@code diagonal}.
+     */
+    public final Operand<TInt32> numCols;
+
+    /**
+     * The number to fill the area outside the specified diagonal band with.
+     * Default is 0.
+     */
+    public final Operand<T> paddingValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Some diagonals are shorter than `max_diag_len` and need to be padded. `align` is
+     * a string specifying how superdiagonals and subdiagonals should be aligned,
+     * respectively. There are four possible alignments: "RIGHT_LEFT" (default),
+     * "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals
+     * to the right (left-pads the row) and subdiagonals to the left (right-pads the
+     * row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is
+     * the opposite alignment.
+     */
+    public final String align;
+
+    public Inputs(GraphOperation op) {
+      super(new MatrixDiagV3<>(op), op, Arrays.asList("T", "align"));
+      int inputIndex = 0;
+      diagonal = (Operand<T>) op.input(inputIndex++);
+      k = (Operand<TInt32>) op.input(inputIndex++);
+      numRows = (Operand<TInt32>) op.input(inputIndex++);
+      numCols = (Operand<TInt32>) op.input(inputIndex++);
+      paddingValue = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      align = op.attributes().getAttrString("align");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java
index 822ba52caa7..d0c74cd771b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -89,4 +93,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatrixLogarithm<T>> {
+    /**
+     * Shape is {@code [..., M, M]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MatrixLogarithm<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java
index 7cf8c61e559..89ebedfe50f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -236,4 +240,51 @@ public Options align(String align) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatrixSetDiag<T>> {
+    /**
+     * Rank {@code r+1}, where {@code r >= 1}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * Rank {@code r} when {@code k} is an integer or {@code k[0] == k[1]}. Otherwise, it has rank {@code r+1}.
+     * {@code k >= 1}.
+     */
+    public final Operand<T> diagonal;
+
+    /**
+     * Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main
+     * diagonal, and negative value means subdiagonals. {@code k} can be a single integer
+     * (for a single diagonal) or a pair of integers specifying the low and high ends
+     * of a matrix band. {@code k[0]} must not be larger than {@code k[1]}.
+     */
+    public final Operand<TInt32> k;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Some diagonals are shorter than `max_diag_len` and need to be padded. `align` is
+     * a string specifying how superdiagonals and subdiagonals should be aligned,
+     * respectively. There are four possible alignments: "RIGHT_LEFT" (default),
+     * "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals
+     * to the right (left-pads the row) and subdiagonals to the left (right-pads the
+     * row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is
+     * the opposite alignment.
+     */
+    public final String align;
+
+    public Inputs(GraphOperation op) {
+      super(new MatrixSetDiag<>(op), op, Arrays.asList("T", "align"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      diagonal = (Operand<T>) op.input(inputIndex++);
+      k = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      align = op.attributes().getAttrString("align");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java
index f3cf21c2138..a1a0e24aea4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat64;
 import org.tensorflow.types.family.TType;
 
@@ -157,4 +161,44 @@ public Options fast(Boolean fast) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MatrixSolveLs<T>> {
+    /**
+     * Shape is {@code [..., M, N]}.
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * Shape is {@code [..., M, K]}.
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * Scalar tensor.
+     * <p>{@literal @}compatibility(numpy)<br>
+     * Equivalent to np.linalg.lstsq
+     * <br>{@literal @}end_compatibility
+     */
+    public final Operand<TFloat64> l2Regularizer;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The fast attribute
+     */
+    public final boolean fast;
+
+    public Inputs(GraphOperation op) {
+      super(new MatrixSolveLs<>(op), op, Arrays.asList("T", "fast"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      l2Regularizer = (Operand<TFloat64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      fast = op.attributes().getAttrBool("fast");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java
index 02839271a61..618f33cc405 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -143,4 +147,31 @@ public Options fullMatrices(Boolean fullMatrices) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Qr<T>> {
+    /**
+     * A tensor of shape {@code [..., M, N]} whose inner-most 2 dimensions
+     * form matrices of size {@code [M, N]}. Let {@code P} be the minimum of {@code M} and {@code N}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * If true, compute full-sized `q` and `r`. If false
+     * (the default), compute only the leading `P` columns of `q`.
+     */
+    public final boolean fullMatrices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Qr<>(op), op, Arrays.asList("full_matrices", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      fullMatrices = op.attributes().getAttrBool("full_matrices");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java
index 3f8fae35715..151f366432c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -71,7 +75,7 @@ private QuantizedMatMul(Operation operation) {
    * @param maxA The float value that the highest quantized {@code a} value represents.
    * @param minB The float value that the lowest quantized {@code b} value represents.
    * @param maxB The float value that the highest quantized {@code b} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param Tactivation The type of output produced by activation function
    * following this operation.
    * @param options carries optional attribute values
@@ -188,4 +192,84 @@ public Options transposeB(Boolean transposeB) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedMatMul<?>> {
+    /**
+     * Must be a two-dimensional tensor.
+     */
+    public final Operand<? extends TNumber> a;
+
+    /**
+     * Must be a two-dimensional tensor.
+     */
+    public final Operand<? extends TNumber> b;
+
+    /**
+     * The float value that the lowest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> minA;
+
+    /**
+     * The float value that the highest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> maxA;
+
+    /**
+     * The float value that the lowest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> minB;
+
+    /**
+     * The float value that the highest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> maxB;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    /**
+     * If true, `a` is transposed before multiplication.
+     */
+    public final boolean transposeA;
+
+    /**
+     * If true, `b` is transposed before multiplication.
+     */
+    public final boolean transposeB;
+
+    /**
+     * The type of output produced by activation function
+     * following this operation.
+     */
+    public final DataType Tactivation;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMatMul<>(op), op, Arrays.asList("T1", "T2", "Toutput", "transpose_a", "transpose_b", "Tactivation"));
+      int inputIndex = 0;
+      a = (Operand<? extends TNumber>) op.input(inputIndex++);
+      b = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minA = (Operand<TFloat32>) op.input(inputIndex++);
+      maxA = (Operand<TFloat32>) op.input(inputIndex++);
+      minB = (Operand<TFloat32>) op.input(inputIndex++);
+      maxB = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Toutput = op.attributes().getAttrType("Toutput");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      Tactivation = op.attributes().getAttrType("Tactivation");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java
index c7af6356a65..e55131173ff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -71,7 +75,7 @@ private QuantizedMatMulWithBias(Operation operation) {
    * @param maxA The float value that the highest quantized {@code a} value represents.
    * @param minB The float value that the lowest quantized {@code b} value represents.
    * @param maxB The float value that the highest quantized {@code b} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param options carries optional attribute values
    * @param <W> data type for {@code QuantizedMatMulWithBias} output and operands
    * @return a new instance of QuantizedMatMulWithBias
@@ -211,4 +215,96 @@ public Options inputQuantMode(String inputQuantMode) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedMatMulWithBias<?>> {
+    /**
+     * A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}.
+     */
+    public final Operand<? extends TNumber> a;
+
+    /**
+     * A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}.
+     */
+    public final Operand<? extends TNumber> b;
+
+    /**
+     * A 1D bias tensor with size matching inner dimension of {@code b} (after being
+     * transposed if {@code transposed_b} is non-zero).
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The float value that the lowest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> minA;
+
+    /**
+     * The float value that the highest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> maxA;
+
+    /**
+     * The float value that the lowest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> minB;
+
+    /**
+     * The float value that the highest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> maxB;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    /**
+     * If true, `a` is transposed before multiplication.
+     */
+    public final boolean transposeA;
+
+    /**
+     * If true, `b` is transposed before multiplication.
+     */
+    public final boolean transposeB;
+
+    /**
+     * Input data quantization mode. Either MIN_FIRST(default) or SCALED.
+     */
+    public final String inputQuantMode;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMatMulWithBias<>(op), op, Arrays.asList("T1", "T2", "Tbias", "Toutput", "transpose_a", "transpose_b", "input_quant_mode"));
+      int inputIndex = 0;
+      a = (Operand<? extends TNumber>) op.input(inputIndex++);
+      b = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minA = (Operand<TFloat32>) op.input(inputIndex++);
+      maxA = (Operand<TFloat32>) op.input(inputIndex++);
+      minB = (Operand<TFloat32>) op.input(inputIndex++);
+      maxB = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Tbias = op.attributes().getAttrType("Tbias");
+      Toutput = op.attributes().getAttrType("Toutput");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      inputQuantMode = op.attributes().getAttrString("input_quant_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java
index 7b5d8f0d05f..89adf2b6063 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -72,7 +76,7 @@ private QuantizedMatMulWithBiasAndRelu(Operation operation) {
    * @param maxA The float value that the highest quantized {@code a} value represents.
    * @param minB The float value that the lowest quantized {@code b} value represents.
    * @param maxB The float value that the highest quantized {@code b} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedMatMulWithBiasAndRelu} output and operands
    * @return a new instance of QuantizedMatMulWithBiasAndRelu
@@ -212,4 +216,90 @@ public Options inputQuantMode(String inputQuantMode) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedMatMulWithBiasAndRelu<?>> {
+    /**
+     * A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}.
+     */
+    public final Operand<? extends TNumber> a;
+
+    /**
+     * A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}.
+     */
+    public final Operand<? extends TNumber> b;
+
+    /**
+     * A 1D bias tensor with size matching with inner dimension of {@code b} (after being
+     * transposed if {@code transposed_b} is non-zero).
+     */
+    public final Operand<TFloat32> bias;
+
+    /**
+     * The float value that the lowest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> minA;
+
+    /**
+     * The float value that the highest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> maxA;
+
+    /**
+     * The float value that the lowest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> minB;
+
+    /**
+     * The float value that the highest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> maxB;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    /**
+     * If true, `a` is transposed before multiplication.
+     */
+    public final boolean transposeA;
+
+    /**
+     * If true, `b` is transposed before multiplication.
+     */
+    public final boolean transposeB;
+
+    /**
+     * Input data quantization mode. Either MIN_FIRST(default) or SCALED.
+     */
+    public final String inputQuantMode;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMatMulWithBiasAndRelu<>(op), op, Arrays.asList("T1", "T2", "Toutput", "transpose_a", "transpose_b", "input_quant_mode"));
+      int inputIndex = 0;
+      a = (Operand<? extends TNumber>) op.input(inputIndex++);
+      b = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<TFloat32>) op.input(inputIndex++);
+      minA = (Operand<TFloat32>) op.input(inputIndex++);
+      maxA = (Operand<TFloat32>) op.input(inputIndex++);
+      minB = (Operand<TFloat32>) op.input(inputIndex++);
+      maxB = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Toutput = op.attributes().getAttrType("Toutput");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      inputQuantMode = op.attributes().getAttrString("input_quant_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java
index 22e29864166..adf556ae8d3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -74,8 +78,8 @@ private QuantizedMatMulWithBiasAndReluAndRequantize(Operation operation) {
    * @param minB The float value that the lowest quantized {@code b} value represents.
    * @param maxB The float value that the highest quantized {@code b} value represents.
    * @param minFreezedOutput The float value that the highest quantized output value after requantize.
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param Toutput the value of the Toutput property
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param Toutput The value of the Toutput attribute
    * @param options carries optional attribute values
    * @param <W> data type for {@code QuantizedMatMulWithBiasAndReluAndRequantize} output and operands
    * @return a new instance of QuantizedMatMulWithBiasAndReluAndRequantize
@@ -218,4 +222,108 @@ public Options inputQuantMode(String inputQuantMode) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedMatMulWithBiasAndReluAndRequantize<?>> {
+    /**
+     * A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}.
+     */
+    public final Operand<? extends TNumber> a;
+
+    /**
+     * A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}.
+     */
+    public final Operand<? extends TNumber> b;
+
+    /**
+     * A 1D bias tensor with size matching with inner dimension of {@code b} (after being
+     * transposed if {@code transposed_b} is non-zero).
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The float value that the lowest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> minA;
+
+    /**
+     * The float value that the highest quantized {@code a} value represents.
+     */
+    public final Operand<TFloat32> maxA;
+
+    /**
+     * The float value that the lowest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> minB;
+
+    /**
+     * The float value that the highest quantized {@code b} value represents.
+     */
+    public final Operand<TFloat32> maxB;
+
+    /**
+     * The float value that the highest quantized output value after requantize.
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    /**
+     * If true, `a` is transposed before multiplication.
+     */
+    public final boolean transposeA;
+
+    /**
+     * If true, `b` is transposed before multiplication.
+     */
+    public final boolean transposeB;
+
+    /**
+     * Input data quantization mode. Either MIN_FIRST(default) or SCALED.
+     */
+    public final String inputQuantMode;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMatMulWithBiasAndReluAndRequantize<>(op), op, Arrays.asList("T1", "T2", "Tbias", "Toutput", "transpose_a", "transpose_b", "input_quant_mode"));
+      int inputIndex = 0;
+      a = (Operand<? extends TNumber>) op.input(inputIndex++);
+      b = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minA = (Operand<TFloat32>) op.input(inputIndex++);
+      maxA = (Operand<TFloat32>) op.input(inputIndex++);
+      minB = (Operand<TFloat32>) op.input(inputIndex++);
+      maxB = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Tbias = op.attributes().getAttrType("Tbias");
+      Toutput = op.attributes().getAttrType("Toutput");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      inputQuantMode = op.attributes().getAttrString("input_quant_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java
index d2c93e69887..adde5950814 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/SelfAdjointEig.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -138,4 +142,30 @@ public Options computeV(Boolean computeV) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SelfAdjointEig<T>> {
+    /**
+     * {@code Tensor} input of shape {@code [N, N]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * If `True` then eigenvectors will be computed and returned in `v`.
+     * Otherwise, only the eigenvalues will be computed.
+     */
+    public final boolean computeV;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SelfAdjointEig<>(op), op, Arrays.asList("compute_v", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      computeV = op.attributes().getAttrBool("compute_v");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java
index 42731f6edf4..f07de1dcd02 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -129,4 +133,36 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Solve<T>> {
+    /**
+     * Shape is {@code [..., M, M]}.
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * Shape is {@code [..., M, K]}.
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * Boolean indicating whether to solve with `matrix` or its (block-wise)
+     * adjoint.
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Solve<>(op), op, Arrays.asList("adjoint", "T"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java
index 9dfa820a4da..cb633920385 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -94,4 +98,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sqrtm<T>> {
+    /**
+     * Shape is {@code [..., M, M]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sqrtm<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java
index 2314f25ec56..a3b388794cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -186,4 +190,40 @@ public Options fullMatrices(Boolean fullMatrices) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Svd<T>> {
+    /**
+     * A tensor of shape {@code [..., M, N]} whose inner-most 2 dimensions
+     * form matrices of size {@code [M, N]}. Let {@code P} be the minimum of {@code M} and {@code N}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * If true, left and right singular vectors will be
+     * computed and returned in `u` and `v`, respectively.
+     * If false, `u` and `v` are not set and should never referenced.
+     */
+    public final boolean computeUv;
+
+    /**
+     * If true, compute full-sized `u` and `v`. If false
+     * (the default), compute only the leading `P` singular vectors.
+     * Ignored if `compute_uv` is `False`.
+     */
+    public final boolean fullMatrices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Svd<>(op), op, Arrays.asList("compute_uv", "full_matrices", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      computeUv = op.attributes().getAttrBool("compute_uv");
+      fullMatrices = op.attributes().getAttrBool("full_matrices");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java
index 5a4037cd396..4dac3f09451 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -92,4 +96,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TensorDiag<T>> {
+    /**
+     * Rank k tensor where k is at most 1.
+     */
+    public final Operand<T> diagonal;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorDiag<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      diagonal = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java
index ddcc97d638b..6cc286ea41b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -93,4 +97,23 @@ public Output<T> diagonal() {
   public Output<T> asOutput() {
     return diagonal;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TensorDiagPart<T>> {
+    /**
+     * Rank k tensor where k is even and not zero.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorDiagPart<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java
index 1df128d376d..cb3430f85d4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -56,8 +60,8 @@ private Transpose(Operation operation) {
    * Factory method to create a class wrapping a new Transpose operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param perm the perm value
+   * @param x The x value
+   * @param perm The perm value
    * @param <T> data type for {@code Transpose} output and operands
    * @return a new instance of Transpose
    */
@@ -85,4 +89,35 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Transpose<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The perm input
+     */
+    public final Operand<? extends TNumber> perm;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tperm attribute
+     */
+    public final DataType Tperm;
+
+    public Inputs(GraphOperation op) {
+      super(new Transpose<>(op), op, Arrays.asList("T", "Tperm"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      perm = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tperm = op.attributes().getAttrType("Tperm");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java
index 6b44f83ab59..65f0269ce1d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -199,4 +203,47 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TriangularSolve<T>> {
+    /**
+     * Shape is {@code [..., M, M]}.
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * Shape is {@code [..., M, K]}.
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * Boolean indicating whether the innermost matrices in `matrix` are
+     * lower or upper triangular.
+     */
+    public final boolean lower;
+
+    /**
+     * Boolean indicating whether to solve with `matrix` or its (block-wise)
+     *          adjoint.
+     *
+     * @compatibility(numpy)
+     * Equivalent to scipy.linalg.solve_triangular
+     * @end_compatibility
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TriangularSolve<>(op), op, Arrays.asList("lower", "adjoint", "T"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      lower = op.attributes().getAttrBool("lower");
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java
index a43a50262a2..544a71da27d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -87,4 +91,45 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TridiagonalMatMul<T>> {
+    /**
+     * Tensor of shape {@code [..., 1, M]}, representing superdiagonals of
+     * tri-diagonal matrices to the left of multiplication. Last element is ignored.
+     */
+    public final Operand<T> superdiag;
+
+    /**
+     * Tensor of shape {@code [..., 1, M]}, representing main diagonals of tri-diagonal
+     * matrices to the left of multiplication.
+     */
+    public final Operand<T> maindiag;
+
+    /**
+     * Tensor of shape {@code [..., 1, M]}, representing subdiagonals of tri-diagonal
+     * matrices to the left of multiplication. First element is ignored.
+     */
+    public final Operand<T> subdiag;
+
+    /**
+     * Tensor of shape {@code [..., M, N]}, representing MxN matrices to the right of
+     * multiplication.
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TridiagonalMatMul<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      superdiag = (Operand<T>) op.input(inputIndex++);
+      maindiag = (Operand<T>) op.input(inputIndex++);
+      subdiag = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java
index da22a9d990e..a62030705f6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -156,4 +160,46 @@ public Options perturbSingular(Boolean perturbSingular) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TridiagonalSolve<T>> {
+    /**
+     * Tensor of shape {@code [..., 3, M]} whose innermost 2 dimensions represent the
+     * tridiagonal matrices with three rows being the superdiagonal, diagonals, and
+     * subdiagonals, in order. The last element of the superdiagonal and the first
+     * element of the subdiagonal is ignored.
+     */
+    public final Operand<T> diagonals;
+
+    /**
+     * Tensor of shape {@code [..., M, K]}, representing K right-hand sides per each
+     * left-hand side.
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * Whether to apply partial pivoting. Partial pivoting makes the procedure more
+     * stable, but slower.
+     */
+    public final boolean partialPivoting;
+
+    /**
+     * The perturbSingular attribute
+     */
+    public final boolean perturbSingular;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TridiagonalSolve<>(op), op, Arrays.asList("partial_pivoting", "perturb_singular", "T"));
+      int inputIndex = 0;
+      diagonals = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      partialPivoting = op.attributes().getAttrBool("partial_pivoting");
+      perturbSingular = op.attributes().getAttrBool("perturb_singular");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java
index ed9ea8f002d..441df3a3e05 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -61,7 +65,7 @@ private CSRSparseMatrixComponents(Operation operation) {
    * @param scope current scope
    * @param csrSparseMatrix A batched CSRSparseMatrix.
    * @param index The index in {@code csr_sparse_matrix}'s batch.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param <T> data type for {@code CSRSparseMatrixComponents} output and operands
    * @return a new instance of CSRSparseMatrixComponents
    */
@@ -103,4 +107,29 @@ public Output<TInt32> colInds() {
   public Output<T> values() {
     return values;
   }
+
+  public static class Inputs extends RawOpInputs<CSRSparseMatrixComponents<?>> {
+    /**
+     * A batched CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> csrSparseMatrix;
+
+    /**
+     * The index in {@code csr_sparse_matrix}'s batch.
+     */
+    public final Operand<TInt32> index;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new CSRSparseMatrixComponents<>(op), op, Arrays.asList("type"));
+      int inputIndex = 0;
+      csrSparseMatrix = (Operand<? extends TType>) op.input(inputIndex++);
+      index = (Operand<TInt32>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java
index 1eab3760775..032c356bb97 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,7 +55,7 @@ private CSRSparseMatrixToDense(Operation operation) {
    *
    * @param scope current scope
    * @param sparseInput A batched CSRSparseMatrix.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param <T> data type for {@code CSRSparseMatrixToDense} output and operands
    * @return a new instance of CSRSparseMatrixToDense
    */
@@ -79,4 +83,23 @@ public Output<T> denseOutput() {
   public Output<T> asOutput() {
     return denseOutput;
   }
+
+  public static class Inputs extends RawOpInputs<CSRSparseMatrixToDense<?>> {
+    /**
+     * A batched CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> sparseInput;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new CSRSparseMatrixToDense<>(op), op, Arrays.asList("type"));
+      int inputIndex = 0;
+      sparseInput = (Operand<? extends TType>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java
index ec0efb39f90..e34a47fad2c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -58,7 +62,7 @@ private CSRSparseMatrixToSparseTensor(Operation operation) {
    *
    * @param scope current scope
    * @param sparseMatrix A (possibly batched) CSRSparseMatrix.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param <T> data type for {@code CSRSparseMatrixToSparseTensor} output and operands
    * @return a new instance of CSRSparseMatrixToSparseTensor
    */
@@ -99,4 +103,23 @@ public Output<T> values() {
   public Output<TInt64> denseShape() {
     return denseShape;
   }
+
+  public static class Inputs extends RawOpInputs<CSRSparseMatrixToSparseTensor<?>> {
+    /**
+     * A (possibly batched) CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> sparseMatrix;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new CSRSparseMatrixToSparseTensor<>(op), op, Arrays.asList("type"));
+      int inputIndex = 0;
+      sparseMatrix = (Operand<? extends TType>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/DenseToCSRSparseMatrix.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/DenseToCSRSparseMatrix.java
index e1d3794be5a..b1edd569963 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/DenseToCSRSparseMatrix.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/DenseToCSRSparseMatrix.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -78,4 +82,29 @@ public Output<? extends TType> sparseOutput() {
   public Output<TType> asOutput() {
     return (Output<TType>) sparseOutput;
   }
+
+  public static class Inputs extends RawOpInputs<DenseToCSRSparseMatrix> {
+    /**
+     * A Dense tensor.
+     */
+    public final Operand<? extends TType> denseInput;
+
+    /**
+     * Indices of nonzero elements.
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DenseToCSRSparseMatrix(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      denseInput = (Operand<? extends TType>) op.input(inputIndex++);
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixAdd.java
index 2dbacec3ded..36a84e7f892 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixAdd.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -84,4 +88,41 @@ public Output<? extends TType> c() {
   public Output<TType> asOutput() {
     return (Output<TType>) c;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseMatrixAdd> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> a;
+
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> b;
+
+    /**
+     * A constant scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * A constant scalar.
+     */
+    public final Operand<T> beta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixAdd(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<? extends TType>) op.input(inputIndex++);
+      b = (Operand<? extends TType>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      beta = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java
index c59e026a0a5..11b776289df 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -268,4 +272,65 @@ public Options conjugateOutput(Boolean conjugateOutput) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseMatrixMatMul<T>> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> a;
+
+    /**
+     * A dense tensor.
+     */
+    public final Operand<T> b;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Indicates whether `a` should be transposed.
+     */
+    public final boolean transposeA;
+
+    /**
+     * Indicates whether `b` should be transposed.
+     */
+    public final boolean transposeB;
+
+    /**
+     * Indicates whether `a` should be conjugate-transposed.
+     */
+    public final boolean adjointA;
+
+    /**
+     * Indicates whether `b` should be conjugate-transposed.
+     */
+    public final boolean adjointB;
+
+    /**
+     * Transposes the product of `a` and `b`.
+     */
+    public final boolean transposeOutput;
+
+    /**
+     * Conjugates the product of `a` and `b`.
+     */
+    public final boolean conjugateOutput;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixMatMul<>(op), op, Arrays.asList("T", "transpose_a", "transpose_b", "adjoint_a", "adjoint_b", "transpose_output", "conjugate_output"));
+      int inputIndex = 0;
+      a = (Operand<? extends TType>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      adjointA = op.attributes().getAttrBool("adjoint_a");
+      adjointB = op.attributes().getAttrBool("adjoint_b");
+      transposeOutput = op.attributes().getAttrBool("transpose_output");
+      conjugateOutput = op.attributes().getAttrBool("conjugate_output");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMul.java
index bfe5470377b..ce8d51f00a6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMul.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -83,4 +87,29 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixMul> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> a;
+
+    /**
+     * A dense tensor.
+     */
+    public final Operand<? extends TType> b;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixMul(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<? extends TType>) op.input(inputIndex++);
+      b = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixNNZ.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixNNZ.java
index ec8f88c871c..a6c19832dd2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixNNZ.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixNNZ.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -73,4 +76,17 @@ public Output<TInt32> nnz() {
   public Output<TInt32> asOutput() {
     return nnz;
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixNNZ> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> sparseMatrix;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixNNZ(op), op, Arrays.asList());
+      int inputIndex = 0;
+      sparseMatrix = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixOrderingAMD.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixOrderingAMD.java
index 044f77cd7ea..9b35eac22c9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixOrderingAMD.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixOrderingAMD.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -114,4 +117,17 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixOrderingAMD> {
+    /**
+     * A {@code CSRSparseMatrix}.
+     */
+    public final Operand<? extends TType> input;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixOrderingAMD(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java
index ff71d3a1e0e..5dd3f79012c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -55,7 +59,7 @@ private SparseMatrixSoftmax(Operation operation) {
    *
    * @param scope current scope
    * @param logits A CSRSparseMatrix.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param <T> data type for {@code SparseMatrixSoftmax} output and operands
    * @return a new instance of SparseMatrixSoftmax
    */
@@ -84,4 +88,23 @@ public Output<? extends TType> softmax() {
   public Output<TType> asOutput() {
     return (Output<TType>) softmax;
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixSoftmax> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> logits;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixSoftmax(op), op, Arrays.asList("type"));
+      int inputIndex = 0;
+      logits = (Operand<? extends TType>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java
index f5d48cd58d0..05ae75273bc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -52,7 +56,7 @@ private SparseMatrixSoftmaxGrad(Operation operation) {
    * @param scope current scope
    * @param softmax A CSRSparseMatrix.
    * @param gradSoftmax The gradient of {@code softmax}.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param <T> data type for {@code SparseMatrixSoftmaxGrad} output and operands
    * @return a new instance of SparseMatrixSoftmaxGrad
    */
@@ -82,4 +86,29 @@ public Output<? extends TType> gradient() {
   public Output<TType> asOutput() {
     return (Output<TType>) gradient;
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixSoftmaxGrad> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> softmax;
+
+    /**
+     * The gradient of {@code softmax}.
+     */
+    public final Operand<? extends TType> gradSoftmax;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixSoftmaxGrad(op), op, Arrays.asList("type"));
+      int inputIndex = 0;
+      softmax = (Operand<? extends TType>) op.input(inputIndex++);
+      gradSoftmax = (Operand<? extends TType>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java
index 854d7714176..bd8d2d0fcc4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -116,7 +120,7 @@ private SparseMatrixSparseCholesky(Operation operation) {
    * @param scope current scope
    * @param input A {@code CSRSparseMatrix}.
    * @param permutation A fill-in reducing permutation matrix.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param <T> data type for {@code SparseMatrixSparseCholesky} output and operands
    * @return a new instance of SparseMatrixSparseCholesky
    */
@@ -146,4 +150,29 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixSparseCholesky> {
+    /**
+     * A {@code CSRSparseMatrix}.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * A fill-in reducing permutation matrix.
+     */
+    public final Operand<TInt32> permutation;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixSparseCholesky(op), op, Arrays.asList("type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      permutation = (Operand<TInt32>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java
index 052bcd4aaeb..5c4564e1067 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -117,7 +121,7 @@ private SparseMatrixSparseMatMul(Operation operation) {
    * @param scope current scope
    * @param a A CSRSparseMatrix.
    * @param b A CSRSparseMatrix.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code SparseMatrixSparseMatMul} output and operands
    * @return a new instance of SparseMatrixSparseMatMul
@@ -264,4 +268,53 @@ public Options adjointB(Boolean adjointB) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixSparseMatMul> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> a;
+
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> b;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    /**
+     * Indicates whether `a` should be transposed.
+     */
+    public final boolean transposeA;
+
+    /**
+     * Indicates whether `b` should be transposed.
+     */
+    public final boolean transposeB;
+
+    /**
+     * Indicates whether `a` should be conjugate-transposed.
+     */
+    public final boolean adjointA;
+
+    /**
+     * Indicates whether `b` should be conjugate-transposed.
+     */
+    public final boolean adjointB;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixSparseMatMul(op), op, Arrays.asList("type", "transpose_a", "transpose_b", "adjoint_a", "adjoint_b"));
+      int inputIndex = 0;
+      a = (Operand<? extends TType>) op.input(inputIndex++);
+      b = (Operand<? extends TType>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      adjointA = op.attributes().getAttrBool("adjoint_a");
+      adjointB = op.attributes().getAttrBool("adjoint_b");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java
index 510d784415f..e8a0beceddb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -52,7 +56,7 @@ private SparseMatrixTranspose(Operation operation) {
    *
    * @param scope current scope
    * @param input A CSRSparseMatrix.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code SparseMatrixTranspose} output and operands
    * @return a new instance of SparseMatrixTranspose
@@ -120,4 +124,29 @@ public Options conjugate(Boolean conjugate) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixTranspose> {
+    /**
+     * A CSRSparseMatrix.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * Indicates whether `input` should be conjugated.
+     */
+    public final boolean conjugate;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixTranspose(op), op, Arrays.asList("conjugate", "type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      conjugate = op.attributes().getAttrBool("conjugate");
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java
index 13439e2a49e..6502ad7d100 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -51,7 +55,7 @@ private SparseMatrixZeros(Operation operation) {
    *
    * @param scope current scope
    * @param denseShape The desired matrix shape.
-   * @param type the value of the type property
+   * @param type The value of the type attribute
    * @param <T> data type for {@code SparseMatrixZeros} output and operands
    * @return a new instance of SparseMatrixZeros
    */
@@ -80,4 +84,23 @@ public Output<? extends TType> sparseMatrix() {
   public Output<TType> asOutput() {
     return (Output<TType>) sparseMatrix;
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatrixZeros> {
+    /**
+     * The desired matrix shape.
+     */
+    public final Operand<TInt64> denseShape;
+
+    /**
+     * The type attribute
+     */
+    public final DataType type;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatrixZeros(op), op, Arrays.asList("type"));
+      int inputIndex = 0;
+      denseShape = (Operand<TInt64>) op.input(inputIndex++);
+      type = op.attributes().getAttrType("type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseTensorToCSRSparseMatrix.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseTensorToCSRSparseMatrix.java
index b9d3aebaa6e..36d6fb8013e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseTensorToCSRSparseMatrix.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseTensorToCSRSparseMatrix.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.linalg.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -80,4 +84,35 @@ public Output<? extends TType> sparseMatrix() {
   public Output<TType> asOutput() {
     return (Output<TType>) sparseMatrix;
   }
+
+  public static class Inputs extends RawOpInputs<SparseTensorToCSRSparseMatrix> {
+    /**
+     * SparseTensor indices.
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * SparseTensor values.
+     */
+    public final Operand<? extends TType> values;
+
+    /**
+     * SparseTensor dense shape.
+     */
+    public final Operand<TInt64> denseShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseTensorToCSRSparseMatrix(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<? extends TType>) op.input(inputIndex++);
+      denseShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java
index e18c875dc03..c78b34ed12f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -56,7 +60,7 @@ private Abs(Operation operation) {
    * Factory method to create a class wrapping a new Abs operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Abs} output and operands
    * @return a new instance of Abs
    */
@@ -82,4 +86,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Abs<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Abs<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java
index ecdb5d78af9..7a531d623e8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -90,4 +94,31 @@ public Output<T> sum() {
   public Output<T> asOutput() {
     return sum;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<AccumulateN<T>> {
+    /**
+     * A list of {@code Tensor} objects, each with same shape and type.
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Shape of elements of `inputs`.
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new AccumulateN<>(op), op, Arrays.asList("T", "shape"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java
index bf83134db52..bc2d95bfe5c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,7 +59,7 @@ private Acos(Operation operation) {
    * Factory method to create a class wrapping a new Acos operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Acos} output and operands
    * @return a new instance of Acos
    */
@@ -81,4 +85,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Acos<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Acos<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java
index f8324e7bf17..d273129375d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,7 +63,7 @@ private Acosh(Operation operation) {
    * Factory method to create a class wrapping a new Acosh operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Acosh} output and operands
    * @return a new instance of Acosh
    */
@@ -85,4 +89,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Acosh<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Acosh<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java
index ef34ca94ba9..19bb9502f1d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,8 +61,8 @@ private Add(Operation operation) {
    * Factory method to create a class wrapping a new Add operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Add} output and operands
    * @return a new instance of Add
    */
@@ -85,4 +89,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Add<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Add<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java
index 9968751c73d..04d7c198272 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,7 +63,7 @@ private AddN(Operation operation) {
    * Factory method to create a class wrapping a new AddN operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
+   * @param inputs The inputs value
    * @param <T> data type for {@code AddN} output and operands
    * @return a new instance of AddN
    */
@@ -85,4 +89,25 @@ public Output<T> sum() {
   public Output<T> asOutput() {
     return sum;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<AddN<T>> {
+    /**
+     * The inputs input
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AddN<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java
index 85c68982edf..afb2b79ab48 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -69,8 +73,8 @@ private Angle(Operation operation) {
    * Factory method to create a class wrapping a new Angle operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Angle} output and operands
    * @return a new instance of Angle
    */
@@ -89,7 +93,7 @@ public static <U extends TNumber> Angle<U> create(Scope scope, Operand<? extends
    * Factory method to create a class wrapping a new Angle operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Angle, with default output types
    */
   @Endpoint(
@@ -112,4 +116,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Angle<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new Angle<>(op), op, Arrays.asList("T", "Tout"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ApproximateEqual.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ApproximateEqual.java
index 0ff28f5272f..5a8173def8e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ApproximateEqual.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ApproximateEqual.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -52,8 +56,8 @@ private ApproximateEqual(Operation operation) {
    * Factory method to create a class wrapping a new ApproximateEqual operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param options carries optional attribute values
    * @param <T> data type for {@code ApproximateEqual} output and operands
    * @return a new instance of ApproximateEqual
@@ -120,4 +124,35 @@ public Options tolerance(Float tolerance) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApproximateEqual> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The tolerance attribute
+     */
+    public final float tolerance;
+
+    public Inputs(GraphOperation op) {
+      super(new ApproximateEqual(op), op, Arrays.asList("T", "tolerance"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      tolerance = op.attributes().getAttrFloat("tolerance");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java
index 48709c643ab..91b94a54d2b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -66,11 +70,11 @@ private ArgMax(Operation operation) {
    * Factory method to create a class wrapping a new ArgMax operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    * Describes which dimension of the input Tensor to reduce across. For vectors,
    * use dimension = 0.
-   * @param outputType the value of the outputType property
+   * @param outputType The value of the outputType attribute
    * @param <V> data type for {@code ArgMax} output and operands
    * @return a new instance of ArgMax
    */
@@ -90,7 +94,7 @@ public static <V extends TNumber> ArgMax<V> create(Scope scope, Operand<? extend
    * Factory method to create a class wrapping a new ArgMax operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    * Describes which dimension of the input Tensor to reduce across. For vectors,
    * use dimension = 0.
@@ -117,4 +121,43 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ArgMax<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
+     * Describes which dimension of the input Tensor to reduce across. For vectors,
+     * use dimension = 0.
+     */
+    public final Operand<? extends TNumber> dimension;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The outputType attribute
+     */
+    public final DataType outputType;
+
+    public Inputs(GraphOperation op) {
+      super(new ArgMax<>(op), op, Arrays.asList("T", "Tidx", "output_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      dimension = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      outputType = op.attributes().getAttrType("output_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java
index fc75352c9a7..a5742d5c542 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -66,11 +70,11 @@ private ArgMin(Operation operation) {
    * Factory method to create a class wrapping a new ArgMin operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    * Describes which dimension of the input Tensor to reduce across. For vectors,
    * use dimension = 0.
-   * @param outputType the value of the outputType property
+   * @param outputType The value of the outputType attribute
    * @param <V> data type for {@code ArgMin} output and operands
    * @return a new instance of ArgMin
    */
@@ -90,7 +94,7 @@ public static <V extends TNumber> ArgMin<V> create(Scope scope, Operand<? extend
    * Factory method to create a class wrapping a new ArgMin operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
    * Describes which dimension of the input Tensor to reduce across. For vectors,
    * use dimension = 0.
@@ -117,4 +121,43 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ArgMin<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * int32 or int64, must be in the range {@code [-rank(input), rank(input))}.
+     * Describes which dimension of the input Tensor to reduce across. For vectors,
+     * use dimension = 0.
+     */
+    public final Operand<? extends TNumber> dimension;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The outputType attribute
+     */
+    public final DataType outputType;
+
+    public Inputs(GraphOperation op) {
+      super(new ArgMin<>(op), op, Arrays.asList("T", "Tidx", "output_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      dimension = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      outputType = op.attributes().getAttrType("output_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java
index ee04e8cf388..0ab2256368d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -65,7 +69,7 @@ private Asin(Operation operation) {
    * Factory method to create a class wrapping a new Asin operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Asin} output and operands
    * @return a new instance of Asin
    */
@@ -91,4 +95,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Asin<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Asin<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java
index 0119bd153bc..bd402f3f550 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,7 +64,7 @@ private Asinh(Operation operation) {
    * Factory method to create a class wrapping a new Asinh operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Asinh} output and operands
    * @return a new instance of Asinh
    */
@@ -86,4 +90,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Asinh<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Asinh<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java
index 23d406fc212..06edc00e74a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -65,7 +69,7 @@ private Atan(Operation operation) {
    * Factory method to create a class wrapping a new Atan operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Atan} output and operands
    * @return a new instance of Atan
    */
@@ -91,4 +95,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Atan<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Atan<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java
index ce96908dcde..675120effab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -69,8 +73,8 @@ private Atan2(Operation operation) {
    * Factory method to create a class wrapping a new Atan2 operation.
    *
    * @param scope current scope
-   * @param y the y value
-   * @param x the x value
+   * @param y The y value
+   * @param x The x value
    * @param <T> data type for {@code Atan2} output and operands
    * @return a new instance of Atan2
    */
@@ -97,4 +101,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Atan2<T>> {
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Atan2<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      y = (Operand<T>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java
index 044b5024ce0..c9aff2cf3a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -62,7 +66,7 @@ private Atanh(Operation operation) {
    * Factory method to create a class wrapping a new Atanh operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Atanh} output and operands
    * @return a new instance of Atanh
    */
@@ -88,4 +92,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Atanh<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Atanh<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java
index 35381f86ecc..c7824375420 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselI0(Operation operation) {
    * Factory method to create a class wrapping a new BesselI0 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselI0} output and operands
    * @return a new instance of BesselI0
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselI0<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselI0<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java
index 5aaf7dc071b..a557e9f294e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselI0e(Operation operation) {
    * Factory method to create a class wrapping a new BesselI0e operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselI0e} output and operands
    * @return a new instance of BesselI0e
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselI0e<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselI0e<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java
index 48be4da8852..3b5362106b7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselI1(Operation operation) {
    * Factory method to create a class wrapping a new BesselI1 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselI1} output and operands
    * @return a new instance of BesselI1
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselI1<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselI1<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java
index 86c91135186..00461637760 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselI1e(Operation operation) {
    * Factory method to create a class wrapping a new BesselI1e operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselI1e} output and operands
    * @return a new instance of BesselI1e
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselI1e<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselI1e<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java
index 12a6deebcb8..3e873075268 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -59,9 +63,9 @@ private Betainc(Operation operation) {
    * Factory method to create a class wrapping a new Betainc operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param b the b value
-   * @param x the x value
+   * @param a The a value
+   * @param b The b value
+   * @param x The x value
    * @param <T> data type for {@code Betainc} output and operands
    * @return a new instance of Betainc
    */
@@ -90,4 +94,35 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Betainc<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The b input
+     */
+    public final Operand<T> b;
+
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Betainc<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java
index e5c3df77bb5..ae7d1475d31 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -94,4 +98,37 @@ public Output<T> bins() {
   public Output<T> asOutput() {
     return bins;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Bincount<T>> {
+    /**
+     * int32 {@code Tensor}.
+     */
+    public final Operand<TInt32> arr;
+
+    /**
+     * non-negative int32 scalar {@code Tensor}.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * is an int32, int64, float32, or float64 {@code Tensor} with the same
+     * shape as {@code arr}, or a length-0 {@code Tensor}, in which case it acts as all weights
+     * equal to 1.
+     */
+    public final Operand<T> weights;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Bincount<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      arr = (Operand<TInt32>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      weights = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java
index 9b811445925..f27874e0c69 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Ceil(Operation operation) {
    * Factory method to create a class wrapping a new Ceil operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Ceil} output and operands
    * @return a new instance of Ceil
    */
@@ -79,4 +83,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Ceil<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Ceil<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java
index 6e5df44de86..c03e3d836d1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -70,8 +74,8 @@ private ComplexAbs(Operation operation) {
    * Factory method to create a class wrapping a new ComplexAbs operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param Tout the value of the Tout property
+   * @param x The x value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code ComplexAbs} output and operands
    * @return a new instance of ComplexAbs
    */
@@ -90,7 +94,7 @@ public static <U extends TNumber> ComplexAbs<U> create(Scope scope, Operand<? ex
    * Factory method to create a class wrapping a new ComplexAbs operation, with the default output types.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of ComplexAbs, with default output types
    */
   @Endpoint(
@@ -113,4 +117,29 @@ public Output<U> y() {
   public Output<U> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<ComplexAbs<?>> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TType> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new ComplexAbs<>(op), op, Arrays.asList("T", "Tout"));
+      int inputIndex = 0;
+      x = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java
index cbe6cc9c710..c07c7b6d9dd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -63,7 +67,7 @@ private Conj(Operation operation) {
    * Factory method to create a class wrapping a new Conj operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code Conj} output and operands
    * @return a new instance of Conj
    */
@@ -89,4 +93,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Conj<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Conj<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java
index 23ce30f2b39..ddfe40b21dd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -61,7 +65,7 @@ private Cos(Operation operation) {
    * Factory method to create a class wrapping a new Cos operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Cos} output and operands
    * @return a new instance of Cos
    */
@@ -87,4 +91,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Cos<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Cos<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java
index d47a6e1e490..4cebf838097 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,7 +64,7 @@ private Cosh(Operation operation) {
    * Factory method to create a class wrapping a new Cosh operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Cosh} output and operands
    * @return a new instance of Cosh
    */
@@ -86,4 +90,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Cosh<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Cosh<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java
index b22b0fb1e72..fa818c7aa06 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -171,4 +175,50 @@ public Options reverse(Boolean reverse) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Cumprod<T>> {
+    /**
+     * A {@code Tensor}. Must be one of the following types: {@code float32}, {@code float64},
+     * {@code int64}, {@code int32}, {@code uint8}, {@code uint16}, {@code int16}, {@code int8}, {@code complex64},
+     * {@code complex128}, {@code qint8}, {@code quint8}, {@code qint32}, {@code half}.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A {@code Tensor} of type {@code int32} (default: 0). Must be in the range
+     * {@code [-rank(x), rank(x))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If `True`, perform exclusive cumprod.
+     */
+    public final boolean exclusive;
+
+    /**
+     * A `bool` (default: False).
+     */
+    public final boolean reverse;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Cumprod<>(op), op, Arrays.asList("exclusive", "reverse", "T", "Tidx"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      exclusive = op.attributes().getAttrBool("exclusive");
+      reverse = op.attributes().getAttrBool("reverse");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java
index ecc7e3b0aff..f0b4b9b2e45 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -171,4 +175,50 @@ public Options reverse(Boolean reverse) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Cumsum<T>> {
+    /**
+     * A {@code Tensor}. Must be one of the following types: {@code float32}, {@code float64},
+     * {@code int64}, {@code int32}, {@code uint8}, {@code uint16}, {@code int16}, {@code int8}, {@code complex64},
+     * {@code complex128}, {@code qint8}, {@code quint8}, {@code qint32}, {@code half}.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A {@code Tensor} of type {@code int32} (default: 0). Must be in the range
+     * {@code [-rank(x), rank(x))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If `True`, perform exclusive cumsum.
+     */
+    public final boolean exclusive;
+
+    /**
+     * A `bool` (default: False).
+     */
+    public final boolean reverse;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Cumsum<>(op), op, Arrays.asList("exclusive", "reverse", "T", "Tidx"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      exclusive = op.attributes().getAttrBool("exclusive");
+      reverse = op.attributes().getAttrBool("reverse");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java
index 6e98ab061c4..ca5448a9960 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -160,4 +164,48 @@ public Options reverse(Boolean reverse) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CumulativeLogsumexp<T>> {
+    /**
+     * A {@code Tensor}. Must be one of the following types: {@code float16}, {@code float32}, {@code float64}.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A {@code Tensor} of type {@code int32} (default: 0). Must be in the range
+     * {@code [-rank(x), rank(x))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If `True`, perform exclusive cumulative log-sum-exp.
+     */
+    public final boolean exclusive;
+
+    /**
+     * A `bool` (default: False).
+     */
+    public final boolean reverse;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new CumulativeLogsumexp<>(op), op, Arrays.asList("exclusive", "reverse", "T", "Tidx"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      exclusive = op.attributes().getAttrBool("exclusive");
+      reverse = op.attributes().getAttrBool("reverse");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java
index 6310445901f..556c582b9d6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -133,4 +137,49 @@ public Options binaryOutput(Boolean binaryOutput) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<DenseBincount<U>> {
+    /**
+     * 1D or 2D int {@code Tensor}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * non-negative int scalar {@code Tensor}.
+     */
+    public final Operand<T> sizeOutput;
+
+    /**
+     * is an int32, int64, float32, or float64 {@code Tensor} with the same
+     * shape as {@code arr}, or a length-0 {@code Tensor}, in which case it acts as all weights
+     * equal to 1.
+     */
+    public final Operand<U> weights;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * bool; Whether the kernel should count the appearance or number of occurrences.
+     */
+    public final boolean binaryOutput;
+
+    public Inputs(GraphOperation op) {
+      super(new DenseBincount<>(op), op, Arrays.asList("Tidx", "T", "binary_output"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      sizeOutput = (Operand<T>) op.input(inputIndex++);
+      weights = (Operand<U>) op.input(inputIndex++);
+      Tidx = op.attributes().getAttrType("Tidx");
+      T = op.attributes().getAttrType("T");
+      binaryOutput = op.attributes().getAttrBool("binary_output");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java
index 6e60883e429..7d50c38999a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -54,7 +58,7 @@ private Digamma(Operation operation) {
    * Factory method to create a class wrapping a new Digamma operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Digamma} output and operands
    * @return a new instance of Digamma
    */
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Digamma<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Digamma<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java
index 8988d560e5a..7a8a0ca06de 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private Div(Operation operation) {
    * Factory method to create a class wrapping a new Div operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Div} output and operands
    * @return a new instance of Div
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Div<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Div<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java
index fc3fe91315d..d21762c3127 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private DivNoNan(Operation operation) {
    * Factory method to create a class wrapping a new DivNoNan operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code DivNoNan} output and operands
    * @return a new instance of DivNoNan
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DivNoNan<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DivNoNan<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Equal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Equal.java
index 4c37a703bb8..625624b428c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Equal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Equal.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -63,8 +67,8 @@ private Equal(Operation operation) {
    * Factory method to create a class wrapping a new Equal operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param options carries optional attribute values
    * @param <T> data type for {@code Equal} output and operands
    * @return a new instance of Equal
@@ -131,4 +135,35 @@ public Options incompatibleShapeError(Boolean incompatibleShapeError) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Equal> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The incompatibleShapeError attribute
+     */
+    public final boolean incompatibleShapeError;
+
+    public Inputs(GraphOperation op) {
+      super(new Equal(op), op, Arrays.asList("T", "incompatible_shape_error"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      incompatibleShapeError = op.attributes().getAttrBool("incompatible_shape_error");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java
index 78103474f66..8960e9851f5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Erf(Operation operation) {
    * Factory method to create a class wrapping a new Erf operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Erf} output and operands
    * @return a new instance of Erf
    */
@@ -79,4 +83,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Erf<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Erf<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java
index 68bad7cb746..c24a60a10a4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Erfc(Operation operation) {
    * Factory method to create a class wrapping a new Erfc operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Erfc} output and operands
    * @return a new instance of Erfc
    */
@@ -79,4 +83,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Erfc<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Erfc<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java
index 03d468a2553..edc260dd2ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -74,7 +78,7 @@ private Exp(Operation operation) {
    * Factory method to create a class wrapping a new Exp operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Exp} output and operands
    * @return a new instance of Exp
    */
@@ -100,4 +104,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Exp<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Exp<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java
index 47759eeab1d..29e89e11ae6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -65,7 +69,7 @@ private Expm1(Operation operation) {
    * Factory method to create a class wrapping a new Expm1 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Expm1} output and operands
    * @return a new instance of Expm1
    */
@@ -91,4 +95,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Expm1<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Expm1<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Fact.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Fact.java
index d7fae0d2495..95aa9162307 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Fact.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Fact.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -74,4 +77,11 @@ public Output<TString> fact() {
   public Output<TString> asOutput() {
     return fact;
   }
+
+  public static class Inputs extends RawOpInputs<Fact> {
+    public Inputs(GraphOperation op) {
+      super(new Fact(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java
index 2901b5af2ac..a83480aa9b9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Floor(Operation operation) {
    * Factory method to create a class wrapping a new Floor operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Floor} output and operands
    * @return a new instance of Floor
    */
@@ -79,4 +83,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Floor<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Floor<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java
index 88c184551e3..bb8adeeb63d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private FloorDiv(Operation operation) {
    * Factory method to create a class wrapping a new FloorDiv operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code FloorDiv} output and operands
    * @return a new instance of FloorDiv
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<FloorDiv<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FloorDiv<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java
index d8292045766..61d7d5b5cfa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -57,8 +61,8 @@ private FloorMod(Operation operation) {
    * Factory method to create a class wrapping a new FloorMod operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code FloorMod} output and operands
    * @return a new instance of FloorMod
    */
@@ -85,4 +89,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FloorMod<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FloorMod<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java
index 5986b90cc87..57504b1d508 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -64,8 +68,8 @@ private Greater(Operation operation) {
    * Factory method to create a class wrapping a new Greater operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Greater} output and operands
    * @return a new instance of Greater
    */
@@ -92,4 +96,29 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Greater> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Greater(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java
index 96a0c33cdac..9a38c6b5fa8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -64,8 +68,8 @@ private GreaterEqual(Operation operation) {
    * Factory method to create a class wrapping a new GreaterEqual operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code GreaterEqual} output and operands
    * @return a new instance of GreaterEqual
    */
@@ -92,4 +96,29 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<GreaterEqual> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new GreaterEqual(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java
index d6b96a559bb..5bb9bc21881 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -60,8 +64,8 @@ private Igamma(Operation operation) {
    * Factory method to create a class wrapping a new Igamma operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param x the x value
+   * @param a The a value
+   * @param x The x value
    * @param <T> data type for {@code Igamma} output and operands
    * @return a new instance of Igamma
    */
@@ -88,4 +92,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Igamma<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Igamma<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java
index cca8e5abc1b..f223cb5a1a1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private IgammaGradA(Operation operation) {
    * Factory method to create a class wrapping a new IgammaGradA operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param x the x value
+   * @param a The a value
+   * @param x The x value
    * @param <T> data type for {@code IgammaGradA} output and operands
    * @return a new instance of IgammaGradA
    */
@@ -77,4 +81,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<IgammaGradA<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new IgammaGradA<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java
index 02a42548c8a..356f1129187 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -60,8 +64,8 @@ private Igammac(Operation operation) {
    * Factory method to create a class wrapping a new Igammac operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param x the x value
+   * @param a The a value
+   * @param x The x value
    * @param <T> data type for {@code Igammac} output and operands
    * @return a new instance of Igammac
    */
@@ -88,4 +92,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Igammac<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Igammac<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java
index e650e5ed4fc..10eb163fabe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -65,8 +69,8 @@ private Imag(Operation operation) {
    * Factory method to create a class wrapping a new Imag operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Imag} output and operands
    * @return a new instance of Imag
    */
@@ -85,7 +89,7 @@ public static <U extends TNumber> Imag<U> create(Scope scope, Operand<? extends
    * Factory method to create a class wrapping a new Imag operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Imag, with default output types
    */
   @Endpoint(
@@ -108,4 +112,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Imag<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new Imag<>(op), op, Arrays.asList("T", "Tout"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java
index 25f38778533..570c0408231 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -90,4 +94,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<InvertPermutation<T>> {
+    /**
+     * 1-D.
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new InvertPermutation<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java
index 793ab136dcd..b134a350c34 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -60,7 +64,7 @@ private IsFinite(Operation operation) {
    * Factory method to create a class wrapping a new IsFinite operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of IsFinite
    */
   @Endpoint(
@@ -85,4 +89,23 @@ public Output<TBool> y() {
   public Output<TBool> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<IsFinite> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TNumber> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new IsFinite(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java
index 6a347f259ee..1b111be0a5d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -60,7 +64,7 @@ private IsInf(Operation operation) {
    * Factory method to create a class wrapping a new IsInf operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of IsInf
    */
   @Endpoint(
@@ -85,4 +89,23 @@ public Output<TBool> y() {
   public Output<TBool> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<IsInf> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TNumber> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new IsInf(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java
index 35e52265f72..5d3bbc59140 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -60,7 +64,7 @@ private IsNan(Operation operation) {
    * Factory method to create a class wrapping a new IsNan operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of IsNan
    */
   @Endpoint(
@@ -85,4 +89,23 @@ public Output<TBool> y() {
   public Output<TBool> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<IsNan> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TNumber> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new IsNan(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java
index a45e1462e4e..ab28b8e688d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -64,8 +68,8 @@ private Less(Operation operation) {
    * Factory method to create a class wrapping a new Less operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Less} output and operands
    * @return a new instance of Less
    */
@@ -92,4 +96,29 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Less> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Less(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java
index 2ded1a54f94..de450dd1f93 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -64,8 +68,8 @@ private LessEqual(Operation operation) {
    * Factory method to create a class wrapping a new LessEqual operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code LessEqual} output and operands
    * @return a new instance of LessEqual
    */
@@ -92,4 +96,29 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LessEqual> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LessEqual(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java
index 30a35ea9223..4881d6ca779 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -60,7 +64,7 @@ private Lgamma(Operation operation) {
    * Factory method to create a class wrapping a new Lgamma operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Lgamma} output and operands
    * @return a new instance of Lgamma
    */
@@ -86,4 +90,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Lgamma<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Lgamma<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java
index 69190a0255c..098a1d0ff6a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,7 +63,7 @@ private Log(Operation operation) {
    * Factory method to create a class wrapping a new Log operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Log} output and operands
    * @return a new instance of Log
    */
@@ -85,4 +89,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Log<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Log<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java
index cf86bcf4420..2c4a27b0be2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,7 +63,7 @@ private Log1p(Operation operation) {
    * Factory method to create a class wrapping a new Log1p operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Log1p} output and operands
    * @return a new instance of Log1p
    */
@@ -85,4 +89,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Log1p<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Log1p<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalAnd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalAnd.java
index c5db6740088..b2b1329ef87 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalAnd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalAnd.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -53,8 +56,8 @@ private LogicalAnd(Operation operation) {
    * Factory method to create a class wrapping a new LogicalAnd operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @return a new instance of LogicalAnd
    */
   @Endpoint(
@@ -80,4 +83,23 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs extends RawOpInputs<LogicalAnd> {
+    /**
+     * The x input
+     */
+    public final Operand<TBool> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<TBool> y;
+
+    public Inputs(GraphOperation op) {
+      super(new LogicalAnd(op), op, Arrays.asList());
+      int inputIndex = 0;
+      x = (Operand<TBool>) op.input(inputIndex++);
+      y = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalNot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalNot.java
index d0a2c92741d..65de99bbfcb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalNot.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalNot.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -76,4 +79,17 @@ public Output<TBool> y() {
   public Output<TBool> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<LogicalNot> {
+    /**
+     * A {@code Tensor} of type {@code bool}.
+     */
+    public final Operand<TBool> x;
+
+    public Inputs(GraphOperation op) {
+      super(new LogicalNot(op), op, Arrays.asList());
+      int inputIndex = 0;
+      x = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalOr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalOr.java
index 98cd56008ac..6c7b7c127db 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalOr.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LogicalOr.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -53,8 +56,8 @@ private LogicalOr(Operation operation) {
    * Factory method to create a class wrapping a new LogicalOr operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @return a new instance of LogicalOr
    */
   @Endpoint(
@@ -80,4 +83,23 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs extends RawOpInputs<LogicalOr> {
+    /**
+     * The x input
+     */
+    public final Operand<TBool> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<TBool> y;
+
+    public Inputs(GraphOperation op) {
+      super(new LogicalOr(op), op, Arrays.asList());
+      int inputIndex = 0;
+      x = (Operand<TBool>) op.input(inputIndex++);
+      y = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java
index 93762b5eefb..f467d171afc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -55,8 +59,8 @@ private Maximum(Operation operation) {
    * Factory method to create a class wrapping a new Maximum operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Maximum} output and operands
    * @return a new instance of Maximum
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Maximum<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Maximum<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java
index 2dea3ff81fa..122567fd9ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -127,4 +131,42 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Mean<T>> {
+    /**
+     * The tensor to reduce.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimensions to reduce. Must be in the range
+     * {@code [-rank(input), rank(input))}.
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new Mean<>(op), op, Arrays.asList("keep_dims", "T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java
index aeff1863af4..facf4cb1560 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -55,8 +59,8 @@ private Minimum(Operation operation) {
    * Factory method to create a class wrapping a new Minimum operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Minimum} output and operands
    * @return a new instance of Minimum
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Minimum<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Minimum<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java
index 21b00a05bf7..8838ae84a78 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -57,8 +61,8 @@ private Mod(Operation operation) {
    * Factory method to create a class wrapping a new Mod operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Mod} output and operands
    * @return a new instance of Mod
    */
@@ -85,4 +89,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Mod<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Mod<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java
index d763f538ab7..28cd75c9810 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private Mul(Operation operation) {
    * Factory method to create a class wrapping a new Mul operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Mul} output and operands
    * @return a new instance of Mul
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Mul<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Mul<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java
index 9752010053f..a5a904d2bd4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private MulNoNan(Operation operation) {
    * Factory method to create a class wrapping a new MulNoNan operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code MulNoNan} output and operands
    * @return a new instance of MulNoNan
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<MulNoNan<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MulNoNan<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java
index 8ebe4057cf5..832e0e067ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Ndtri(Operation operation) {
    * Factory method to create a class wrapping a new Ndtri operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Ndtri} output and operands
    * @return a new instance of Ndtri
    */
@@ -79,4 +83,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Ndtri<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Ndtri<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java
index d5778161810..961355ca9af 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,7 +58,7 @@ private Neg(Operation operation) {
    * Factory method to create a class wrapping a new Neg operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Neg} output and operands
    * @return a new instance of Neg
    */
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Neg<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Neg<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java
index 51cc6a5efd4..3f96ce897d7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -58,8 +62,8 @@ private NextAfter(Operation operation) {
    * Factory method to create a class wrapping a new NextAfter operation.
    *
    * @param scope current scope
-   * @param x1 the x1 value
-   * @param x2 the x2 value
+   * @param x1 The x1 value
+   * @param x2 The x2 value
    * @param <T> data type for {@code NextAfter} output and operands
    * @return a new instance of NextAfter
    */
@@ -86,4 +90,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NextAfter<T>> {
+    /**
+     * The x1 input
+     */
+    public final Operand<T> x1;
+
+    /**
+     * The x2 input
+     */
+    public final Operand<T> x2;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new NextAfter<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x1 = (Operand<T>) op.input(inputIndex++);
+      x2 = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NotEqual.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NotEqual.java
index a47f07b2d49..b579d881c1e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NotEqual.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NotEqual.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TType;
 
@@ -54,8 +58,8 @@ private NotEqual(Operation operation) {
    * Factory method to create a class wrapping a new NotEqual operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param options carries optional attribute values
    * @param <T> data type for {@code NotEqual} output and operands
    * @return a new instance of NotEqual
@@ -122,4 +126,35 @@ public Options incompatibleShapeError(Boolean incompatibleShapeError) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<NotEqual> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The incompatibleShapeError attribute
+     */
+    public final boolean incompatibleShapeError;
+
+    public Inputs(GraphOperation op) {
+      super(new NotEqual(op), op, Arrays.asList("T", "incompatible_shape_error"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      incompatibleShapeError = op.attributes().getAttrBool("incompatible_shape_error");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java
index a64e3f6c0c4..2b7aacb5503 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -57,8 +61,8 @@ private Polygamma(Operation operation) {
    * Factory method to create a class wrapping a new Polygamma operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param x the x value
+   * @param a The a value
+   * @param x The x value
    * @param <T> data type for {@code Polygamma} output and operands
    * @return a new instance of Polygamma
    */
@@ -85,4 +89,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Polygamma<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Polygamma<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java
index 4dd412ed439..c49751ed2ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TUint8;
 import org.tensorflow.types.family.TNumber;
 
@@ -57,7 +61,7 @@ private PopulationCount(Operation operation) {
    * Factory method to create a class wrapping a new PopulationCount operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of PopulationCount
    */
   @Endpoint(
@@ -82,4 +86,23 @@ public Output<TUint8> y() {
   public Output<TUint8> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<PopulationCount> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TNumber> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new PopulationCount(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java
index ae2f093d57e..d7a3059dc65 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,8 +64,8 @@ private Pow(Operation operation) {
    * Factory method to create a class wrapping a new Pow operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Pow} output and operands
    * @return a new instance of Pow
    */
@@ -88,4 +92,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Pow<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Pow<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java
index be18d7ab977..49e68db93ce 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -61,13 +65,13 @@ private QuantizedAdd(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedAdd operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param minX The float value that the lowest quantized {@code x} value represents.
    * @param maxX The float value that the highest quantized {@code x} value represents.
    * @param minY The float value that the lowest quantized {@code y} value represents.
    * @param maxY The float value that the highest quantized {@code y} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param <V> data type for {@code QuantizedAdd} output and operands
    * @return a new instance of QuantizedAdd
    */
@@ -116,4 +120,65 @@ public Output<TFloat32> minZ() {
   public Output<TFloat32> maxZ() {
     return maxZ;
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedAdd<?>> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TNumber> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<? extends TNumber> y;
+
+    /**
+     * The float value that the lowest quantized {@code x} value represents.
+     */
+    public final Operand<TFloat32> minX;
+
+    /**
+     * The float value that the highest quantized {@code x} value represents.
+     */
+    public final Operand<TFloat32> maxX;
+
+    /**
+     * The float value that the lowest quantized {@code y} value represents.
+     */
+    public final Operand<TFloat32> minY;
+
+    /**
+     * The float value that the highest quantized {@code y} value represents.
+     */
+    public final Operand<TFloat32> maxY;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedAdd<>(op), op, Arrays.asList("T1", "T2", "Toutput"));
+      int inputIndex = 0;
+      x = (Operand<? extends TNumber>) op.input(inputIndex++);
+      y = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minX = (Operand<TFloat32>) op.input(inputIndex++);
+      maxX = (Operand<TFloat32>) op.input(inputIndex++);
+      minY = (Operand<TFloat32>) op.input(inputIndex++);
+      maxY = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Toutput = op.attributes().getAttrType("Toutput");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java
index 8091f86dd3f..3861db85f3a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -61,13 +65,13 @@ private QuantizedMul(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedMul operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param minX The float value that the lowest quantized {@code x} value represents.
    * @param maxX The float value that the highest quantized {@code x} value represents.
    * @param minY The float value that the lowest quantized {@code y} value represents.
    * @param maxY The float value that the highest quantized {@code y} value represents.
-   * @param Toutput the value of the Toutput property
+   * @param Toutput The value of the Toutput attribute
    * @param <V> data type for {@code QuantizedMul} output and operands
    * @return a new instance of QuantizedMul
    */
@@ -116,4 +120,65 @@ public Output<TFloat32> minZ() {
   public Output<TFloat32> maxZ() {
     return maxZ;
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedMul<?>> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TNumber> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<? extends TNumber> y;
+
+    /**
+     * The float value that the lowest quantized {@code x} value represents.
+     */
+    public final Operand<TFloat32> minX;
+
+    /**
+     * The float value that the highest quantized {@code x} value represents.
+     */
+    public final Operand<TFloat32> maxX;
+
+    /**
+     * The float value that the lowest quantized {@code y} value represents.
+     */
+    public final Operand<TFloat32> minY;
+
+    /**
+     * The float value that the highest quantized {@code y} value represents.
+     */
+    public final Operand<TFloat32> maxY;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMul<>(op), op, Arrays.asList("T1", "T2", "Toutput"));
+      int inputIndex = 0;
+      x = (Operand<? extends TNumber>) op.input(inputIndex++);
+      y = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minX = (Operand<TFloat32>) op.input(inputIndex++);
+      maxX = (Operand<TFloat32>) op.input(inputIndex++);
+      minY = (Operand<TFloat32>) op.input(inputIndex++);
+      maxY = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Toutput = op.attributes().getAttrType("Toutput");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java
index 7534337cb26..b4d443f9083 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -65,8 +69,8 @@ private Real(Operation operation) {
    * Factory method to create a class wrapping a new Real operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code Real} output and operands
    * @return a new instance of Real
    */
@@ -85,7 +89,7 @@ public static <U extends TNumber> Real<U> create(Scope scope, Operand<? extends
    * Factory method to create a class wrapping a new Real operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of Real, with default output types
    */
   @Endpoint(
@@ -108,4 +112,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Real<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new Real<>(op), op, Arrays.asList("T", "Tout"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java
index 7073764f171..3b301133fa1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -56,8 +60,8 @@ private RealDiv(Operation operation) {
    * Factory method to create a class wrapping a new RealDiv operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RealDiv} output and operands
    * @return a new instance of RealDiv
    */
@@ -84,4 +88,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RealDiv<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RealDiv<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java
index 6b199d06c72..637d25d959b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,7 +58,7 @@ private Reciprocal(Operation operation) {
    * Factory method to create a class wrapping a new Reciprocal operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Reciprocal} output and operands
    * @return a new instance of Reciprocal
    */
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Reciprocal<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Reciprocal<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java
index 1865d94ada7..579fc948e26 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,8 +55,8 @@ private ReciprocalGrad(Operation operation) {
    * Factory method to create a class wrapping a new ReciprocalGrad operation.
    *
    * @param scope current scope
-   * @param y the y value
-   * @param dy the dy value
+   * @param y The y value
+   * @param dy The dy value
    * @param <T> data type for {@code ReciprocalGrad} output and operands
    * @return a new instance of ReciprocalGrad
    */
@@ -80,4 +84,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ReciprocalGrad<T>> {
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The dy input
+     */
+    public final Operand<T> dy;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ReciprocalGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      y = (Operand<T>) op.input(inputIndex++);
+      dy = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizationRangePerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizationRangePerChannel.java
index d1b018c5a51..121255c20a4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizationRangePerChannel.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizationRangePerChannel.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -88,4 +92,42 @@ public Output<TFloat32> outputMin() {
   public Output<TFloat32> outputMax() {
     return outputMax;
   }
+
+  public static class Inputs extends RawOpInputs<RequantizationRangePerChannel> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The minimum value of the input tensor
+     */
+    public final Operand<TFloat32> inputMin;
+
+    /**
+     * The maximum value of the input tensor.
+     */
+    public final Operand<TFloat32> inputMax;
+
+    /**
+     * The quantized type of input tensor that needs to be converted.
+     */
+    public final DataType T;
+
+    /**
+     * The maximum value of the output that needs to be clipped.
+     * Example: set this to 6 for Relu6.
+     */
+    public final float clipValueMax;
+
+    public Inputs(GraphOperation op) {
+      super(new RequantizationRangePerChannel(op), op, Arrays.asList("T", "clip_value_max"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      inputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      inputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      clipValueMax = op.attributes().getAttrFloat("clip_value_max");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java
index 833e4472731..f3a513f4164 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -109,4 +113,53 @@ public Output<TFloat32> outputMin() {
   public Output<TFloat32> outputMax() {
     return outputMax;
   }
+
+  public static class Inputs extends RawOpInputs<RequantizePerChannel<?>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The minimum value of the input tensor
+     */
+    public final Operand<TFloat32> inputMin;
+
+    /**
+     * The maximum value of the input tensor.
+     */
+    public final Operand<TFloat32> inputMax;
+
+    /**
+     * The minimum value of the output tensor requested.
+     */
+    public final Operand<TFloat32> requestedOutputMin;
+
+    /**
+     * The maximum value of the output tensor requested.
+     */
+    public final Operand<TFloat32> requestedOutputMax;
+
+    /**
+     * The quantized type of input tensor that needs to be converted.
+     */
+    public final DataType T;
+
+    /**
+     * The quantized type of output tensor that needs to be converted.
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new RequantizePerChannel<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      inputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      inputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      requestedOutputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      requestedOutputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java
index e1eb0d407d9..7014e1f8921 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -61,7 +65,7 @@ private Rint(Operation operation) {
    * Factory method to create a class wrapping a new Rint operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Rint} output and operands
    * @return a new instance of Rint
    */
@@ -87,4 +91,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Rint<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Rint<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java
index 1adeea2a548..1d079601ebd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,7 +59,7 @@ private Round(Operation operation) {
    * Factory method to create a class wrapping a new Round operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Round} output and operands
    * @return a new instance of Round
    */
@@ -81,4 +85,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Round<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Round<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java
index be3fa6fdac3..9bf061a5192 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,7 +58,7 @@ private Rsqrt(Operation operation) {
    * Factory method to create a class wrapping a new Rsqrt operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Rsqrt} output and operands
    * @return a new instance of Rsqrt
    */
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Rsqrt<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Rsqrt<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java
index 6e0c26a41a4..8874d5a8b00 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,8 +55,8 @@ private RsqrtGrad(Operation operation) {
    * Factory method to create a class wrapping a new RsqrtGrad operation.
    *
    * @param scope current scope
-   * @param y the y value
-   * @param dy the dy value
+   * @param y The y value
+   * @param dy The dy value
    * @param <T> data type for {@code RsqrtGrad} output and operands
    * @return a new instance of RsqrtGrad
    */
@@ -79,4 +83,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RsqrtGrad<T>> {
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The dy input
+     */
+    public final Operand<T> dy;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RsqrtGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      y = (Operand<T>) op.input(inputIndex++);
+      dy = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java
index 364dcf15551..57098d1f87e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -70,7 +74,7 @@ private SegmentMax(Operation operation) {
    * Factory method to create a class wrapping a new SegmentMax operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    * first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentMax} output and operands
@@ -101,4 +105,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SegmentMax<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor whose size is equal to the size of {@code data}'s
+     * first dimension.  Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SegmentMax<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java
index b3f41259f52..afd9e32a207 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -72,7 +76,7 @@ private SegmentMean(Operation operation) {
    * Factory method to create a class wrapping a new SegmentMean operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    * first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentMean} output and operands
@@ -103,4 +107,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SegmentMean<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor whose size is equal to the size of {@code data}'s
+     * first dimension.  Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SegmentMean<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java
index 2f2fc4a349b..a32e370e3d3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -70,7 +74,7 @@ private SegmentMin(Operation operation) {
    * Factory method to create a class wrapping a new SegmentMin operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    * first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentMin} output and operands
@@ -101,4 +105,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SegmentMin<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor whose size is equal to the size of {@code data}'s
+     * first dimension.  Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SegmentMin<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java
index 3bd1645daa8..192a5367e3c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -71,7 +75,7 @@ private SegmentProd(Operation operation) {
    * Factory method to create a class wrapping a new SegmentProd operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    * first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentProd} output and operands
@@ -102,4 +106,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SegmentProd<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor whose size is equal to the size of {@code data}'s
+     * first dimension.  Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SegmentProd<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java
index c2cc2fb479a..10f814320f8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -71,7 +75,7 @@ private SegmentSum(Operation operation) {
    * Factory method to create a class wrapping a new SegmentSum operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s
    * first dimension.  Values should be sorted and can be repeated.
    * @param <T> data type for {@code SegmentSum} output and operands
@@ -102,4 +106,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SegmentSum<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor whose size is equal to the size of {@code data}'s
+     * first dimension.  Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SegmentSum<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java
index 485274fa7ee..2716b3cf8b8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,7 +58,7 @@ private Sigmoid(Operation operation) {
    * Factory method to create a class wrapping a new Sigmoid operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sigmoid} output and operands
    * @return a new instance of Sigmoid
    */
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sigmoid<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sigmoid<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java
index a5c4a9ebfbf..55d174c2eba 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,8 +55,8 @@ private SigmoidGrad(Operation operation) {
    * Factory method to create a class wrapping a new SigmoidGrad operation.
    *
    * @param scope current scope
-   * @param y the y value
-   * @param dy the dy value
+   * @param y The y value
+   * @param dy The dy value
    * @param <T> data type for {@code SigmoidGrad} output and operands
    * @return a new instance of SigmoidGrad
    */
@@ -79,4 +83,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SigmoidGrad<T>> {
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The dy input
+     */
+    public final Operand<T> dy;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SigmoidGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      y = (Operand<T>) op.input(inputIndex++);
+      dy = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java
index ccdba9e8bb8..4acd2234734 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -64,7 +68,7 @@ private Sign(Operation operation) {
    * Factory method to create a class wrapping a new Sign operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sign} output and operands
    * @return a new instance of Sign
    */
@@ -90,4 +94,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sign<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sign<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java
index 25913e2d26e..2bf226a61ad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,7 +64,7 @@ private Sin(Operation operation) {
    * Factory method to create a class wrapping a new Sin operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sin} output and operands
    * @return a new instance of Sin
    */
@@ -86,4 +90,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sin<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sin<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java
index 14c8e9a2d9c..4486f6576fb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,7 +64,7 @@ private Sinh(Operation operation) {
    * Factory method to create a class wrapping a new Sinh operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sinh} output and operands
    * @return a new instance of Sinh
    */
@@ -86,4 +90,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sinh<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sinh<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java
index ad9d308baa8..4e31c283009 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -108,4 +112,37 @@ public Output<T> samples() {
   public Output<T> asOutput() {
     return samples;
   }
+
+  public static class Inputs extends RawOpInputs<SobolSample<?>> {
+    /**
+     * Positive scalar {@code Tensor} representing each sample's dimension.
+     */
+    public final Operand<TInt32> dim;
+
+    /**
+     * Positive scalar {@code Tensor} of dtype int32. The number of Sobol points to return
+     * in the output.
+     */
+    public final Operand<TInt32> numResults;
+
+    /**
+     * Positive scalar {@code Tensor} of dtype int32. The number of initial points of the
+     * Sobol sequence to skip.
+     */
+    public final Operand<TInt32> skip;
+
+    /**
+     * The type of the sample. One of: `float32` or `float64`.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new SobolSample<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      dim = (Operand<TInt32>) op.input(inputIndex++);
+      numResults = (Operand<TInt32>) op.input(inputIndex++);
+      skip = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java
index b8e861fda0d..75a59a3389e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Softplus(Operation operation) {
    * Factory method to create a class wrapping a new Softplus operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Softplus} output and operands
    * @return a new instance of Softplus
    */
@@ -79,4 +83,23 @@ public Output<T> activations() {
   public Output<T> asOutput() {
     return activations;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Softplus<T>> {
+    /**
+     * The features input
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Softplus<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java
index 56f08bc78b6..dd9f8637498 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -78,4 +82,29 @@ public Output<T> backprops() {
   public Output<T> asOutput() {
     return backprops;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SoftplusGrad<T>> {
+    /**
+     * The backpropagated gradients to the corresponding softplus operation.
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The features passed as input to the corresponding softplus operation.
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SoftplusGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java
index 81a0fd29f58..ffbc55ab620 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,7 +58,7 @@ private Sqrt(Operation operation) {
    * Factory method to create a class wrapping a new Sqrt operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Sqrt} output and operands
    * @return a new instance of Sqrt
    */
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sqrt<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sqrt<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java
index eae4da43173..8bdef3778d0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,8 +55,8 @@ private SqrtGrad(Operation operation) {
    * Factory method to create a class wrapping a new SqrtGrad operation.
    *
    * @param scope current scope
-   * @param y the y value
-   * @param dy the dy value
+   * @param y The y value
+   * @param dy The dy value
    * @param <T> data type for {@code SqrtGrad} output and operands
    * @return a new instance of SqrtGrad
    */
@@ -79,4 +83,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SqrtGrad<T>> {
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The dy input
+     */
+    public final Operand<T> dy;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SqrtGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      y = (Operand<T>) op.input(inputIndex++);
+      dy = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java
index 19622576247..52f321ef0d5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -54,7 +58,7 @@ private Square(Operation operation) {
    * Factory method to create a class wrapping a new Square operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Square} output and operands
    * @return a new instance of Square
    */
@@ -80,4 +84,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Square<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Square<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java
index cb01df2fd23..a71e97d7c5f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private SquaredDifference(Operation operation) {
    * Factory method to create a class wrapping a new SquaredDifference operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code SquaredDifference} output and operands
    * @return a new instance of SquaredDifference
    */
@@ -84,4 +88,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SquaredDifference<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SquaredDifference<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java
index 006833e67d6..c415449aefc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,8 +59,8 @@ private Sub(Operation operation) {
    * Factory method to create a class wrapping a new Sub operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Sub} output and operands
    * @return a new instance of Sub
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sub<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sub<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java
index 69d3fd517d4..80f4bb51b53 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -61,7 +65,7 @@ private Tan(Operation operation) {
    * Factory method to create a class wrapping a new Tan operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Tan} output and operands
    * @return a new instance of Tan
    */
@@ -87,4 +91,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Tan<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Tan<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java
index 2bbdb6d5078..b4a3cdbe76e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -67,7 +71,7 @@ private Tanh(Operation operation) {
    * Factory method to create a class wrapping a new Tanh operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Tanh} output and operands
    * @return a new instance of Tanh
    */
@@ -93,4 +97,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Tanh<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Tanh<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java
index 3ee48eb3711..287eda24c21 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,8 +55,8 @@ private TanhGrad(Operation operation) {
    * Factory method to create a class wrapping a new TanhGrad operation.
    *
    * @param scope current scope
-   * @param y the y value
-   * @param dy the dy value
+   * @param y The y value
+   * @param dy The dy value
    * @param <T> data type for {@code TanhGrad} output and operands
    * @return a new instance of TanhGrad
    */
@@ -79,4 +83,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TanhGrad<T>> {
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The dy input
+     */
+    public final Operand<T> dy;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TanhGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      y = (Operand<T>) op.input(inputIndex++);
+      dy = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java
index 8bd43a99784..04461701a1e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,8 +63,8 @@ private TruncateDiv(Operation operation) {
    * Factory method to create a class wrapping a new TruncateDiv operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code TruncateDiv} output and operands
    * @return a new instance of TruncateDiv
    */
@@ -87,4 +91,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TruncateDiv<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TruncateDiv<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java
index c1614618783..5e0aeadeaae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -56,8 +60,8 @@ private TruncateMod(Operation operation) {
    * Factory method to create a class wrapping a new TruncateMod operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code TruncateMod} output and operands
    * @return a new instance of TruncateMod
    */
@@ -84,4 +88,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<TruncateMod<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TruncateMod<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java
index dbdeb204a82..fd872df8540 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -76,9 +80,9 @@ private UnsortedSegmentMax(Operation operation) {
    * Factory method to create a class wrapping a new UnsortedSegmentMax operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentMax} output and operands
    * @return a new instance of UnsortedSegmentMax
    */
@@ -109,4 +113,47 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<UnsortedSegmentMax<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A tensor whose shape is a prefix of {@code data.shape}.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The numSegments input
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    public Inputs(GraphOperation op) {
+      super(new UnsortedSegmentMax<>(op), op, Arrays.asList("T", "Tindices", "Tnumsegments"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java
index 7d2a113e53d..5a010ae3b5f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -73,9 +77,9 @@ private UnsortedSegmentMin(Operation operation) {
    * Factory method to create a class wrapping a new UnsortedSegmentMin operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentMin} output and operands
    * @return a new instance of UnsortedSegmentMin
    */
@@ -106,4 +110,47 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<UnsortedSegmentMin<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A tensor whose shape is a prefix of {@code data.shape}.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The numSegments input
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    public Inputs(GraphOperation op) {
+      super(new UnsortedSegmentMin<>(op), op, Arrays.asList("T", "Tindices", "Tnumsegments"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java
index eda5093e66a..e54296d0a47 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -73,9 +77,9 @@ private UnsortedSegmentProd(Operation operation) {
    * Factory method to create a class wrapping a new UnsortedSegmentProd operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentProd} output and operands
    * @return a new instance of UnsortedSegmentProd
    */
@@ -106,4 +110,47 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<UnsortedSegmentProd<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A tensor whose shape is a prefix of {@code data.shape}.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The numSegments input
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    public Inputs(GraphOperation op) {
+      super(new UnsortedSegmentProd<>(op), op, Arrays.asList("T", "Tindices", "Tnumsegments"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java
index d5587f5e862..037711460b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -75,9 +79,9 @@ private UnsortedSegmentSum(Operation operation) {
    * Factory method to create a class wrapping a new UnsortedSegmentSum operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}.
-   * @param numSegments the numSegments value
+   * @param numSegments The numSegments value
    * @param <T> data type for {@code UnsortedSegmentSum} output and operands
    * @return a new instance of UnsortedSegmentSum
    */
@@ -108,4 +112,47 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<UnsortedSegmentSum<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A tensor whose shape is a prefix of {@code data.shape}.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The numSegments input
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    public Inputs(GraphOperation op) {
+      super(new UnsortedSegmentSum<>(op), op, Arrays.asList("T", "Tindices", "Tnumsegments"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java
index cc6624e1cd0..c0cea7d21f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,8 +57,8 @@ private Xdivy(Operation operation) {
    * Factory method to create a class wrapping a new Xdivy operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Xdivy} output and operands
    * @return a new instance of Xdivy
    */
@@ -81,4 +85,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Xdivy<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Xdivy<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java
index 100ff3d2122..75936967d7d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,8 +57,8 @@ private Xlog1py(Operation operation) {
    * Factory method to create a class wrapping a new Xlog1py operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Xlog1py} output and operands
    * @return a new instance of Xlog1py
    */
@@ -81,4 +85,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Xlog1py<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Xlog1py<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java
index edf378b4512..da05a27ba3a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,8 +57,8 @@ private Xlogy(Operation operation) {
    * Factory method to create a class wrapping a new Xlogy operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code Xlogy} output and operands
    * @return a new instance of Xlogy
    */
@@ -81,4 +85,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Xlogy<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Xlogy<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java
index 78aa171bfb2..8a7fb4ebcbc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -55,8 +59,8 @@ private Zeta(Operation operation) {
    * Factory method to create a class wrapping a new Zeta operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param q the q value
+   * @param x The x value
+   * @param q The q value
    * @param <T> data type for {@code Zeta} output and operands
    * @return a new instance of Zeta
    */
@@ -83,4 +87,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Zeta<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The q input
+     */
+    public final Operand<T> q;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Zeta<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      q = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java
index 6953ecc8077..81c9afb6a49 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.math;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private erfinv(Operation operation) {
    * Factory method to create a class wrapping a new Erfinv operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Erfinv} output and operands
    * @return a new instance of erfinv
    */
@@ -79,4 +83,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<erfinv<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new erfinv<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java
index 519967fc69b..a9b0a239f7b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselJ0(Operation operation) {
    * Factory method to create a class wrapping a new BesselJ0 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselJ0} output and operands
    * @return a new instance of BesselJ0
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselJ0<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselJ0<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java
index 2c7665e4453..2f4b8d6b71e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselJ1(Operation operation) {
    * Factory method to create a class wrapping a new BesselJ1 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselJ1} output and operands
    * @return a new instance of BesselJ1
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselJ1<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselJ1<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java
index 89f9f9053e6..13bf915e021 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselK0(Operation operation) {
    * Factory method to create a class wrapping a new BesselK0 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselK0} output and operands
    * @return a new instance of BesselK0
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselK0<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselK0<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java
index 312a80d2c7a..0f611baf8df 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselK0e(Operation operation) {
    * Factory method to create a class wrapping a new BesselK0e operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselK0e} output and operands
    * @return a new instance of BesselK0e
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselK0e<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselK0e<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java
index 509eb4af314..5696e8ca364 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselK1(Operation operation) {
    * Factory method to create a class wrapping a new BesselK1 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselK1} output and operands
    * @return a new instance of BesselK1
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselK1<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselK1<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java
index 0044ef761cc..ce0de01e5fc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselK1e(Operation operation) {
    * Factory method to create a class wrapping a new BesselK1e operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselK1e} output and operands
    * @return a new instance of BesselK1e
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselK1e<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselK1e<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java
index 55c8e7de4d9..79bdc102e59 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselY0(Operation operation) {
    * Factory method to create a class wrapping a new BesselY0 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselY0} output and operands
    * @return a new instance of BesselY0
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselY0<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselY0<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java
index 8dace2d3cbb..25c1343ccf2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private BesselY1(Operation operation) {
    * Factory method to create a class wrapping a new BesselY1 operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code BesselY1} output and operands
    * @return a new instance of BesselY1
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BesselY1<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BesselY1<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java
index 1c7334efbc9..f801b241a46 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private Dawsn(Operation operation) {
    * Factory method to create a class wrapping a new Dawsn operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Dawsn} output and operands
    * @return a new instance of Dawsn
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Dawsn<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Dawsn<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java
index 75e4da57938..ed852574a64 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private Expint(Operation operation) {
    * Factory method to create a class wrapping a new Expint operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Expint} output and operands
    * @return a new instance of Expint
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Expint<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Expint<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java
index 62ad26be841..b7433ee47b5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private FresnelCos(Operation operation) {
    * Factory method to create a class wrapping a new FresnelCos operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code FresnelCos} output and operands
    * @return a new instance of FresnelCos
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FresnelCos<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FresnelCos<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java
index c3f8e75299b..2c3ac5e9469 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private FresnelSin(Operation operation) {
    * Factory method to create a class wrapping a new FresnelSin operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code FresnelSin} output and operands
    * @return a new instance of FresnelSin
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FresnelSin<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FresnelSin<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java
index 96588efcd87..64128da2664 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.math.special;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private Spence(Operation operation) {
    * Factory method to create a class wrapping a new Spence operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code Spence} output and operands
    * @return a new instance of Spence
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Spence<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Spence<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java
index c96b474b4a0..4496333ee52 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -144,4 +148,51 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AvgPool<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> value;
+
+    /**
+     * The size of the sliding window for each dimension of `value`.
+     */
+    public final long[] ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of `value`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AvgPool<>(op), op, Arrays.asList("ksize", "strides", "padding", "data_format", "T"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java
index d1500731844..6a42d550dfa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -146,4 +150,53 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AvgPool3d<T>> {
+    /**
+     * Shape {@code [batch, depth, rows, cols, channels]} tensor to pool over.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 1-D tensor of length 5. The size of the window for each dimension of
+     * the input tensor. Must have `ksize[0] = ksize[4] = 1`.
+     */
+    public final long[] ksize;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AvgPool3d<>(op), op, Arrays.asList("ksize", "strides", "padding", "data_format", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java
index 9be20b9dd64..359c151cf8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -148,4 +152,59 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AvgPool3dGrad<T>> {
+    /**
+     * The original input dimensions.
+     */
+    public final Operand<TInt32> origInputShape;
+
+    /**
+     * Output backprop of shape {@code [batch, depth, rows, cols, channels]}.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * 1-D tensor of length 5. The size of the window for each dimension of
+     * the input tensor. Must have `ksize[0] = ksize[4] = 1`.
+     */
+    public final long[] ksize;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AvgPool3dGrad<>(op), op, Arrays.asList("ksize", "strides", "padding", "data_format", "T"));
+      int inputIndex = 0;
+      origInputShape = (Operand<TInt32>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java
index cc6b577a475..980664e35e1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -143,4 +147,58 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<AvgPoolGrad<T>> {
+    /**
+     * 1-D.  Shape of the original input to {@code avg_pool}.
+     */
+    public final Operand<TInt32> origInputShape;
+
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.  Gradients w.r.t.
+     * the output of {@code avg_pool}.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The size of the sliding window for each dimension of the input.
+     */
+    public final long[] ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the input.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new AvgPoolGrad<>(op), op, Arrays.asList("ksize", "strides", "padding", "data_format", "T"));
+      int inputIndex = 0;
+      origInputShape = (Operand<TInt32>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java
index 3f53920618b..bf1a0975705 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -102,4 +106,67 @@ public Output<T> result() {
   public Output<T> asOutput() {
     return result;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchNormWithGlobalNormalization<T>> {
+    /**
+     * A 4D input Tensor.
+     */
+    public final Operand<T> t;
+
+    /**
+     * A 1D mean Tensor with size matching the last dimension of t.
+     * This is the first output from tf.nn.moments,
+     * or a saved moving average thereof.
+     */
+    public final Operand<T> m;
+
+    /**
+     * A 1D variance Tensor with size matching the last dimension of t.
+     * This is the second output from tf.nn.moments,
+     * or a saved moving average thereof.
+     */
+    public final Operand<T> v;
+
+    /**
+     * A 1D beta Tensor with size matching the last dimension of t.
+     * An offset to be added to the normalized tensor.
+     */
+    public final Operand<T> beta;
+
+    /**
+     * A 1D gamma Tensor with size matching the last dimension of t.
+     * If &quot;scale_after_normalization&quot; is true, this tensor will be multiplied
+     * with the normalized tensor.
+     */
+    public final Operand<T> gamma;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A small float number to avoid dividing by 0.
+     */
+    public final float varianceEpsilon;
+
+    /**
+     * A bool indicating whether the resulted tensor
+     * needs to be multiplied with gamma.
+     */
+    public final boolean scaleAfterNormalization;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchNormWithGlobalNormalization<>(op), op, Arrays.asList("T", "variance_epsilon", "scale_after_normalization"));
+      int inputIndex = 0;
+      t = (Operand<T>) op.input(inputIndex++);
+      m = (Operand<T>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      beta = (Operand<T>) op.input(inputIndex++);
+      gamma = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      varianceEpsilon = op.attributes().getAttrFloat("variance_epsilon");
+      scaleAfterNormalization = op.attributes().getAttrBool("scale_after_normalization");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java
index e248dc193d2..86a0ac56fa1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -144,4 +148,66 @@ public Output<T> db() {
   public Output<T> dg() {
     return dg;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BatchNormWithGlobalNormalizationGrad<T>> {
+    /**
+     * A 4D input Tensor.
+     */
+    public final Operand<T> t;
+
+    /**
+     * A 1D mean Tensor with size matching the last dimension of t.
+     * This is the first output from tf.nn.moments,
+     * or a saved moving average thereof.
+     */
+    public final Operand<T> m;
+
+    /**
+     * A 1D variance Tensor with size matching the last dimension of t.
+     * This is the second output from tf.nn.moments,
+     * or a saved moving average thereof.
+     */
+    public final Operand<T> v;
+
+    /**
+     * A 1D gamma Tensor with size matching the last dimension of t.
+     * If &quot;scale_after_normalization&quot; is true, this Tensor will be multiplied
+     * with the normalized Tensor.
+     */
+    public final Operand<T> gamma;
+
+    /**
+     * 4D backprop Tensor.
+     */
+    public final Operand<T> backprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A small float number to avoid dividing by 0.
+     */
+    public final float varianceEpsilon;
+
+    /**
+     * A bool indicating whether the resulted tensor
+     * needs to be multiplied with gamma.
+     */
+    public final boolean scaleAfterNormalization;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchNormWithGlobalNormalizationGrad<>(op), op, Arrays.asList("T", "variance_epsilon", "scale_after_normalization"));
+      int inputIndex = 0;
+      t = (Operand<T>) op.input(inputIndex++);
+      m = (Operand<T>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      gamma = (Operand<T>) op.input(inputIndex++);
+      backprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      varianceEpsilon = op.attributes().getAttrFloat("variance_epsilon");
+      scaleAfterNormalization = op.attributes().getAttrBool("scale_after_normalization");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java
index ba021575492..0e0917f0422 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -135,4 +139,41 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BiasAdd<T>> {
+    /**
+     * Any number of dimensions.
+     */
+    public final Operand<T> value;
+
+    /**
+     * 1-D with size the last dimension of {@code value}.
+     */
+    public final Operand<T> bias;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the bias tensor will be added to the last dimension
+     * of the value tensor.
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     * The tensor will be added to "in_channels", the third-to-the-last
+     *     dimension.
+     */
+    public final String dataFormat;
+
+    public Inputs(GraphOperation op) {
+      super(new BiasAdd<>(op), op, Arrays.asList("T", "data_format"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      bias = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      dataFormat = op.attributes().getAttrString("data_format");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java
index 661a84087e0..b9eda9a3c68 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -134,4 +138,35 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BiasAddGrad<T>> {
+    /**
+     * Any number of dimensions.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the bias tensor will be added to the last dimension
+     * of the value tensor.
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     * The tensor will be added to "in_channels", the third-to-the-last
+     *     dimension.
+     */
+    public final String dataFormat;
+
+    public Inputs(GraphOperation op) {
+      super(new BiasAddGrad<>(op), op, Arrays.asList("T", "data_format"));
+      int inputIndex = 0;
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      dataFormat = op.attributes().getAttrString("data_format");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java
index fd6708a1772..187ad0505ed 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -247,4 +251,84 @@ public Options usePeephole(Boolean usePeephole) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BlockLSTM<T>> {
+    /**
+     * Maximum time length actually used by this input. Outputs are padded
+     * with zeros beyond this length.
+     */
+    public final Operand<TInt64> seqLenMax;
+
+    /**
+     * The sequence input to the LSTM, shape (timelen, batch_size, num_inputs).
+     */
+    public final Operand<T> x;
+
+    /**
+     * Value of the initial cell state.
+     */
+    public final Operand<T> csPrev;
+
+    /**
+     * Initial output of cell (to be used for peephole).
+     */
+    public final Operand<T> hPrev;
+
+    /**
+     * The weight matrix.
+     */
+    public final Operand<T> w;
+
+    /**
+     * The weight matrix for input gate peephole connection.
+     */
+    public final Operand<T> wci;
+
+    /**
+     * The weight matrix for forget gate peephole connection.
+     */
+    public final Operand<T> wcf;
+
+    /**
+     * The weight matrix for output gate peephole connection.
+     */
+    public final Operand<T> wco;
+
+    /**
+     * The bias vector.
+     */
+    public final Operand<T> b;
+
+    /**
+     * Value to clip the 'cs' value to.
+     */
+    public final float cellClip;
+
+    /**
+     * Whether to use peephole weights.
+     */
+    public final boolean usePeephole;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BlockLSTM<>(op), op, Arrays.asList("cell_clip", "use_peephole", "T"));
+      int inputIndex = 0;
+      seqLenMax = (Operand<TInt64>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      csPrev = (Operand<T>) op.input(inputIndex++);
+      hPrev = (Operand<T>) op.input(inputIndex++);
+      w = (Operand<T>) op.input(inputIndex++);
+      wci = (Operand<T>) op.input(inputIndex++);
+      wcf = (Operand<T>) op.input(inputIndex++);
+      wco = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      cellClip = op.attributes().getAttrFloat("cell_clip");
+      usePeephole = op.attributes().getAttrBool("use_peephole");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java
index 522df1b3b32..f794390c585 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -197,4 +201,132 @@ public Output<T> wcoGrad() {
   public Output<T> bGrad() {
     return bGrad;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<BlockLSTMGrad<T>> {
+    /**
+     * Maximum time length actually used by this input. Outputs are padded
+     * with zeros beyond this length.
+     */
+    public final Operand<TInt64> seqLenMax;
+
+    /**
+     * The sequence input to the LSTM, shape (timelen, batch_size, num_inputs).
+     */
+    public final Operand<T> x;
+
+    /**
+     * Value of the initial cell state.
+     */
+    public final Operand<T> csPrev;
+
+    /**
+     * Initial output of cell (to be used for peephole).
+     */
+    public final Operand<T> hPrev;
+
+    /**
+     * The weight matrix.
+     */
+    public final Operand<T> w;
+
+    /**
+     * The weight matrix for input gate peephole connection.
+     */
+    public final Operand<T> wci;
+
+    /**
+     * The weight matrix for forget gate peephole connection.
+     */
+    public final Operand<T> wcf;
+
+    /**
+     * The weight matrix for output gate peephole connection.
+     */
+    public final Operand<T> wco;
+
+    /**
+     * The bias vector.
+     */
+    public final Operand<T> b;
+
+    /**
+     * The input gate over the whole time sequence.
+     */
+    public final Operand<T> i;
+
+    /**
+     * The cell state before the tanh over the whole time sequence.
+     */
+    public final Operand<T> cs;
+
+    /**
+     * The forget gate over the whole time sequence.
+     */
+    public final Operand<T> f;
+
+    /**
+     * The output gate over the whole time sequence.
+     */
+    public final Operand<T> o;
+
+    /**
+     * The cell input over the whole time sequence.
+     */
+    public final Operand<T> ci;
+
+    /**
+     * The cell after the tanh over the whole time sequence.
+     */
+    public final Operand<T> co;
+
+    /**
+     * The output h vector over the whole time sequence.
+     */
+    public final Operand<T> h;
+
+    /**
+     * The current gradient of cs.
+     */
+    public final Operand<T> csGrad;
+
+    /**
+     * The gradient of h vector.
+     */
+    public final Operand<T> hGrad;
+
+    /**
+     * Whether to use peephole weights.
+     */
+    public final boolean usePeephole;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new BlockLSTMGrad<>(op), op, Arrays.asList("use_peephole", "T"));
+      int inputIndex = 0;
+      seqLenMax = (Operand<TInt64>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      csPrev = (Operand<T>) op.input(inputIndex++);
+      hPrev = (Operand<T>) op.input(inputIndex++);
+      w = (Operand<T>) op.input(inputIndex++);
+      wci = (Operand<T>) op.input(inputIndex++);
+      wcf = (Operand<T>) op.input(inputIndex++);
+      wco = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      i = (Operand<T>) op.input(inputIndex++);
+      cs = (Operand<T>) op.input(inputIndex++);
+      f = (Operand<T>) op.input(inputIndex++);
+      o = (Operand<T>) op.input(inputIndex++);
+      ci = (Operand<T>) op.input(inputIndex++);
+      co = (Operand<T>) op.input(inputIndex++);
+      h = (Operand<T>) op.input(inputIndex++);
+      csGrad = (Operand<T>) op.input(inputIndex++);
+      hGrad = (Operand<T>) op.input(inputIndex++);
+      usePeephole = op.attributes().getAttrBool("use_peephole");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java
index 2c3309dc9fc..cab3b859657 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -196,4 +199,61 @@ public Options ignoreLongerOutputsThanInputs(Boolean ignoreLongerOutputsThanInpu
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<CTCLossV2> {
+    /**
+     * 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits. Default blank
+     * label is 0 rather num_classes - 1.
+     */
+    public final Operand<TFloat32> inputs;
+
+    /**
+     * The indices of a {@code SparseTensor<int32, 2>}.
+     * {@code labels_indices(i, :) == [b, t]} means {@code labels_values(i)} stores the id for
+     * {@code (batch b, time t)}.
+     */
+    public final Operand<TInt64> labelsIndices;
+
+    /**
+     * The values (labels) associated with the given batch and time.
+     */
+    public final Operand<TInt32> labelsValues;
+
+    /**
+     * A vector containing sequence lengths (batch).
+     */
+    public final Operand<TInt32> sequenceLength;
+
+    /**
+     * Scalar, if true then repeated labels are
+     * collapsed prior to the CTC calculation.
+     */
+    public final boolean preprocessCollapseRepeated;
+
+    /**
+     * Scalar.  If set to false, *during* CTC calculation
+     * repeated non-blank labels will not be merged and are interpreted as
+     * individual labels.  This is a simplified version of CTC.
+     */
+    public final boolean ctcMergeRepeated;
+
+    /**
+     * Scalar. If set to true, during CTC
+     * calculation, items that have longer output sequences than input sequences
+     * are skipped: they don't contribute to the loss term and have zero-gradient.
+     */
+    public final boolean ignoreLongerOutputsThanInputs;
+
+    public Inputs(GraphOperation op) {
+      super(new CTCLossV2(op), op, Arrays.asList("preprocess_collapse_repeated", "ctc_merge_repeated", "ignore_longer_outputs_than_inputs"));
+      int inputIndex = 0;
+      inputs = (Operand<TFloat32>) op.input(inputIndex++);
+      labelsIndices = (Operand<TInt64>) op.input(inputIndex++);
+      labelsValues = (Operand<TInt32>) op.input(inputIndex++);
+      sequenceLength = (Operand<TInt32>) op.input(inputIndex++);
+      preprocessCollapseRepeated = op.attributes().getAttrBool("preprocess_collapse_repeated");
+      ctcMergeRepeated = op.attributes().getAttrBool("ctc_merge_repeated");
+      ignoreLongerOutputsThanInputs = op.attributes().getAttrBool("ignore_longer_outputs_than_inputs");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ComputeAccidentalHits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ComputeAccidentalHits.java
index 6de1761c2b1..55e64bbc19f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ComputeAccidentalHits.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ComputeAccidentalHits.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -177,4 +180,43 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ComputeAccidentalHits> {
+    /**
+     * The true_classes output of UnpackSparseLabels.
+     */
+    public final Operand<TInt64> trueClasses;
+
+    /**
+     * The sampled_candidates output of CandidateSampler.
+     */
+    public final Operand<TInt64> sampledCandidates;
+
+    /**
+     * Number of true labels per context.
+     */
+    public final long numTrue;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new ComputeAccidentalHits(op), op, Arrays.asList("num_true", "seed", "seed2"));
+      int inputIndex = 0;
+      trueClasses = (Operand<TInt64>) op.input(inputIndex++);
+      sampledCandidates = (Operand<TInt64>) op.input(inputIndex++);
+      numTrue = op.attributes().getAttrInt("num_true");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java
index abe9e0e66dc..a769c324177 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -160,7 +163,7 @@ public static Options explicitPaddings(List<Long> explicitPaddings) {
    * {@code padding} is not {@code "EXPLICIT"}, {@code explicit_paddings} must be empty.
    * @return this Options instance.
    */
-  public static Options explicitPaddings(Long[] explicitPaddings) {
+  public static Options explicitPaddings(Long... explicitPaddings) {
     return new Options().explicitPaddings(explicitPaddings);
   }
 
@@ -202,7 +205,7 @@ public static Options dilations(List<Long> dilations) {
    * depth dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -320,4 +323,80 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Conv2d<T>> {
+    /**
+     * A 4-D tensor. The dimension order is interpreted according to the value
+     * of {@code data_format}, see below for details.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A 4-D tensor of shape
+     * {@code [filter_height, filter_width, in_channels, out_channels]}
+     */
+    public final Operand<T> filter;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * 1-D tensor of length 4.  The stride of the sliding window for each
+     * dimension of `input`. The dimension order is determined by the value of
+     * `data_format`, see below for details.
+     */
+    public final long[] strides;
+
+    /**
+     * The useCudnnOnGpu attribute
+     */
+    public final boolean useCudnnOnGpu;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * If `padding` is `"EXPLICIT"`, the list of explicit padding amounts. For the ith
+     * dimension, the amount of padding inserted before and after the dimension is
+     * `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If
+     * `padding` is not `"EXPLICIT"`, `explicit_paddings` must be empty.
+     */
+    public final long[] explicitPaddings;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, height, width, channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, channels, height, width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 4.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each
+     * filter element on that dimension. The dimension order is determined by the
+     * value of `data_format`, see above for details. Dilations in the batch and
+     * depth dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new Conv2d<>(op), op, Arrays.asList("T", "strides", "use_cudnn_on_gpu", "padding", "explicit_paddings", "data_format", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      useCudnnOnGpu = op.attributes().getAttrBool("use_cudnn_on_gpu");
+      padding = op.attributes().getAttrString("padding");
+      explicitPaddings = op.attributes().getAttrIntList("explicit_paddings");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java
index e909a1ab6ff..b5718f2ca8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -145,7 +148,7 @@ public static Options explicitPaddings(List<Long> explicitPaddings) {
    * {@code padding} is not {@code "EXPLICIT"}, {@code explicit_paddings} must be empty.
    * @return this Options instance.
    */
-  public static Options explicitPaddings(Long[] explicitPaddings) {
+  public static Options explicitPaddings(Long... explicitPaddings) {
     return new Options().explicitPaddings(explicitPaddings);
   }
 
@@ -187,7 +190,7 @@ public static Options dilations(List<Long> dilations) {
    * dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -306,4 +309,87 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Conv2dBackpropFilter<T>> {
+    /**
+     * 4-D with shape {@code [batch, in_height, in_width, in_channels]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * An integer vector representing the tensor shape of {@code filter},
+     * where {@code filter} is a 4-D
+     * {@code [filter_height, filter_width, in_channels, out_channels]} tensor.
+     */
+    public final Operand<TInt32> filterSizes;
+
+    /**
+     * 4-D with shape {@code [batch, out_height, out_width, out_channels]}.
+     * Gradients w.r.t. the output of the convolution.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * of the convolution. Must be in the same order as the dimension specified with
+     * format.
+     */
+    public final long[] strides;
+
+    /**
+     * The useCudnnOnGpu attribute
+     */
+    public final boolean useCudnnOnGpu;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * If `padding` is `"EXPLICIT"`, the list of explicit padding amounts. For the ith
+     * dimension, the amount of padding inserted before and after the dimension is
+     * `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If
+     * `padding` is not `"EXPLICIT"`, `explicit_paddings` must be empty.
+     */
+    public final long[] explicitPaddings;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 4.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each filter
+     * element on that dimension. The dimension order is determined by the value of
+     * `data_format`, see above for details. Dilations in the batch and depth
+     * dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new Conv2dBackpropFilter<>(op), op, Arrays.asList("T", "strides", "use_cudnn_on_gpu", "padding", "explicit_paddings", "data_format", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filterSizes = (Operand<TInt32>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      useCudnnOnGpu = op.attributes().getAttrBool("use_cudnn_on_gpu");
+      padding = op.attributes().getAttrString("padding");
+      explicitPaddings = op.attributes().getAttrIntList("explicit_paddings");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java
index 7231ac48f8b..f629ba8e03a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -145,7 +148,7 @@ public static Options explicitPaddings(List<Long> explicitPaddings) {
    * {@code padding} is not {@code "EXPLICIT"}, {@code explicit_paddings} must be empty.
    * @return this Options instance.
    */
-  public static Options explicitPaddings(Long[] explicitPaddings) {
+  public static Options explicitPaddings(Long... explicitPaddings) {
     return new Options().explicitPaddings(explicitPaddings);
   }
 
@@ -187,7 +190,7 @@ public static Options dilations(List<Long> dilations) {
    * dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -305,4 +308,87 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Conv2dBackpropInput<T>> {
+    /**
+     * An integer vector representing the shape of {@code input},
+     * where {@code input} is a 4-D {@code [batch, height, width, channels]} tensor.
+     */
+    public final Operand<TInt32> inputSizes;
+
+    /**
+     * 4-D with shape
+     * {@code [filter_height, filter_width, in_channels, out_channels]}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * 4-D with shape {@code [batch, out_height, out_width, out_channels]}.
+     * Gradients w.r.t. the output of the convolution.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * of the convolution. Must be in the same order as the dimension specified with
+     * format.
+     */
+    public final long[] strides;
+
+    /**
+     * The useCudnnOnGpu attribute
+     */
+    public final boolean useCudnnOnGpu;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * If `padding` is `"EXPLICIT"`, the list of explicit padding amounts. For the ith
+     * dimension, the amount of padding inserted before and after the dimension is
+     * `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If
+     * `padding` is not `"EXPLICIT"`, `explicit_paddings` must be empty.
+     */
+    public final long[] explicitPaddings;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 4.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each filter
+     * element on that dimension. The dimension order is determined by the value of
+     * `data_format`, see above for details. Dilations in the batch and depth
+     * dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new Conv2dBackpropInput<>(op), op, Arrays.asList("T", "strides", "use_cudnn_on_gpu", "padding", "explicit_paddings", "data_format", "dilations"));
+      int inputIndex = 0;
+      inputSizes = (Operand<TInt32>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      useCudnnOnGpu = op.attributes().getAttrBool("use_cudnn_on_gpu");
+      padding = op.attributes().getAttrString("padding");
+      explicitPaddings = op.attributes().getAttrIntList("explicit_paddings");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java
index b3059545246..aeefc06db8e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -137,7 +140,7 @@ public static Options dilations(List<Long> dilations) {
    * depth dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -211,4 +214,62 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Conv3d<T>> {
+    /**
+     * Shape {@code [batch, in_depth, in_height, in_width, in_channels]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * Shape {@code [filter_depth, filter_height, filter_width, in_channels, out_channels]}. {@code in_channels} must match between {@code input} and {@code filter}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 5.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each
+     * filter element on that dimension. The dimension order is determined by the
+     * value of `data_format`, see above for details. Dilations in the batch and
+     * depth dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new Conv3d<>(op), op, Arrays.asList("T", "strides", "padding", "data_format", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java
index c9f15f99431..a788a51fb92 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -140,7 +143,7 @@ public static Options dilations(List<Long> dilations) {
    * depth dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -214,4 +217,71 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Conv3dBackpropFilter<T>> {
+    /**
+     * Shape {@code [batch, depth, rows, cols, in_channels]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * An integer vector representing the tensor shape of {@code filter},
+     * where {@code filter} is a 5-D
+     * {@code [filter_depth, filter_height, filter_width, in_channels, out_channels]}
+     * tensor.
+     */
+    public final Operand<TInt32> filterSizes;
+
+    /**
+     * Backprop signal of shape {@code [batch, out_depth, out_rows, out_cols, out_channels]}.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 5.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each
+     * filter element on that dimension. The dimension order is determined by the
+     * value of `data_format`, see above for details. Dilations in the batch and
+     * depth dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new Conv3dBackpropFilter<>(op), op, Arrays.asList("T", "strides", "padding", "data_format", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filterSizes = (Operand<TInt32>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java
index 4cfce74a0ce..0cda7f2020c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -139,7 +142,7 @@ public static Options dilations(List<Long> dilations) {
    * depth dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -213,4 +216,77 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<Conv3dBackpropInput<U>> {
+    /**
+     * An integer vector representing the tensor shape of {@code input},
+     * where {@code input} is a 5-D
+     * {@code [batch, depth, rows, cols, in_channels]} tensor.
+     */
+    public final Operand<? extends TNumber> inputSizes;
+
+    /**
+     * Shape {@code [depth, rows, cols, in_channels, out_channels]}.
+     * {@code in_channels} must match between {@code input} and {@code filter}.
+     */
+    public final Operand<U> filter;
+
+    /**
+     * Backprop signal of shape {@code [batch, out_depth, out_rows, out_cols, out_channels]}.
+     */
+    public final Operand<U> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 5.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each
+     * filter element on that dimension. The dimension order is determined by the
+     * value of `data_format`, see above for details. Dilations in the batch and
+     * depth dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new Conv3dBackpropInput<>(op), op, Arrays.asList("T", "strides", "padding", "data_format", "dilations", "Tshape"));
+      int inputIndex = 0;
+      inputSizes = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<U>) op.input(inputIndex++);
+      outBackprop = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java
index ff6a6420b0c..b9cab99e0a5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
@@ -179,4 +182,41 @@ public Options mergeRepeated(Boolean mergeRepeated) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CtcBeamSearchDecoder<T>> {
+    /**
+     * 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits.
+     */
+    public final Operand<T> inputs;
+
+    /**
+     * A vector containing sequence lengths, size {@code (batch)}.
+     */
+    public final Operand<TInt32> sequenceLength;
+
+    /**
+     * A scalar >= 0 (beam search beam width).
+     */
+    public final long beamWidth;
+
+    /**
+     * If true, merge repeated classes in output.
+     */
+    public final boolean mergeRepeated;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new CtcBeamSearchDecoder<>(op), op, Arrays.asList("beam_width", "merge_repeated", "T"));
+      int inputIndex = 0;
+      inputs = (Operand<T>) op.input(inputIndex++);
+      sequenceLength = (Operand<TInt32>) op.input(inputIndex++);
+      beamWidth = op.attributes().getAttrInt("beam_width");
+      mergeRepeated = op.attributes().getAttrBool("merge_repeated");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java
index 525cc165763..3975061991c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
@@ -192,4 +196,41 @@ public Options blankIndex(Long blankIndex) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CtcGreedyDecoder<T>> {
+    /**
+     * 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits.
+     */
+    public final Operand<T> inputs;
+
+    /**
+     * A vector containing sequence lengths, size {@code (batch_size)}.
+     */
+    public final Operand<TInt32> sequenceLength;
+
+    /**
+     * If True, merge repeated classes in output.
+     */
+    public final boolean mergeRepeated;
+
+    /**
+     * The blankIndex attribute
+     */
+    public final long blankIndex;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new CtcGreedyDecoder<>(op), op, Arrays.asList("merge_repeated", "blank_index", "T"));
+      int inputIndex = 0;
+      inputs = (Operand<T>) op.input(inputIndex++);
+      sequenceLength = (Operand<TInt32>) op.input(inputIndex++);
+      mergeRepeated = op.attributes().getAttrBool("merge_repeated");
+      blankIndex = op.attributes().getAttrInt("blank_index");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java
index 92460960518..f70a3763d9e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
@@ -202,4 +206,66 @@ public Options ignoreLongerOutputsThanInputs(Boolean ignoreLongerOutputsThanInpu
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CtcLoss<T>> {
+    /**
+     * 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits.
+     */
+    public final Operand<T> inputs;
+
+    /**
+     * The indices of a {@code SparseTensor<int32, 2>}.
+     * {@code labels_indices(i, :) == [b, t]} means {@code labels_values(i)} stores the id for
+     * {@code (batch b, time t)}.
+     */
+    public final Operand<TInt64> labelsIndices;
+
+    /**
+     * The values (labels) associated with the given batch and time.
+     */
+    public final Operand<TInt32> labelsValues;
+
+    /**
+     * A vector containing sequence lengths (batch).
+     */
+    public final Operand<TInt32> sequenceLength;
+
+    /**
+     * Scalar, if true then repeated labels are
+     * collapsed prior to the CTC calculation.
+     */
+    public final boolean preprocessCollapseRepeated;
+
+    /**
+     * Scalar.  If set to false, *during* CTC calculation
+     * repeated non-blank labels will not be merged and are interpreted as
+     * individual labels.  This is a simplified version of CTC.
+     */
+    public final boolean ctcMergeRepeated;
+
+    /**
+     * Scalar. If set to true, during CTC
+     * calculation, items that have longer output sequences than input sequences
+     * are skipped: they don't contribute to the loss term and have zero-gradient.
+     */
+    public final boolean ignoreLongerOutputsThanInputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new CtcLoss<>(op), op, Arrays.asList("preprocess_collapse_repeated", "ctc_merge_repeated", "ignore_longer_outputs_than_inputs", "T"));
+      int inputIndex = 0;
+      inputs = (Operand<T>) op.input(inputIndex++);
+      labelsIndices = (Operand<TInt64>) op.input(inputIndex++);
+      labelsValues = (Operand<TInt32>) op.input(inputIndex++);
+      sequenceLength = (Operand<TInt32>) op.input(inputIndex++);
+      preprocessCollapseRepeated = op.attributes().getAttrBool("preprocess_collapse_repeated");
+      ctcMergeRepeated = op.attributes().getAttrBool("ctc_merge_repeated");
+      ignoreLongerOutputsThanInputs = op.attributes().getAttrBool("ignore_longer_outputs_than_inputs");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java
index 5d32b0db85d..68e42dfd916 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -100,11 +104,11 @@ private CudnnRNN(Operation operation) {
    * Factory method to create a class wrapping a new CudnnRNNV3 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param inputH the inputH value
-   * @param inputC the inputC value
-   * @param params the params value
-   * @param sequenceLengths the sequenceLengths value
+   * @param input The input value
+   * @param inputH The inputH value
+   * @param inputC The inputC value
+   * @param params The params value
+   * @param sequenceLengths The sequenceLengths value
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNV3} output and operands
    * @return a new instance of CudnnRNN
@@ -414,4 +418,101 @@ public Options timeMajor(Boolean timeMajor) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CudnnRNN<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The inputH input
+     */
+    public final Operand<T> inputH;
+
+    /**
+     * The inputC input
+     */
+    public final Operand<T> inputC;
+
+    /**
+     * The params input
+     */
+    public final Operand<T> params;
+
+    /**
+     * The sequenceLengths input
+     */
+    public final Operand<TInt32> sequenceLengths;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The rnnMode attribute
+     */
+    public final String rnnMode;
+
+    /**
+     * The inputMode attribute
+     */
+    public final String inputMode;
+
+    /**
+     * The direction attribute
+     */
+    public final String direction;
+
+    /**
+     * The dropout attribute
+     */
+    public final float dropout;
+
+    /**
+     * The seed attribute
+     */
+    public final long seed;
+
+    /**
+     * The seed2 attribute
+     */
+    public final long seed2;
+
+    /**
+     * The numProj attribute
+     */
+    public final long numProj;
+
+    /**
+     * The isTraining attribute
+     */
+    public final boolean isTraining;
+
+    /**
+     * The timeMajor attribute
+     */
+    public final boolean timeMajor;
+
+    public Inputs(GraphOperation op) {
+      super(new CudnnRNN<>(op), op, Arrays.asList("T", "rnn_mode", "input_mode", "direction", "dropout", "seed", "seed2", "num_proj", "is_training", "time_major"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      inputH = (Operand<T>) op.input(inputIndex++);
+      inputC = (Operand<T>) op.input(inputIndex++);
+      params = (Operand<T>) op.input(inputIndex++);
+      sequenceLengths = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      rnnMode = op.attributes().getAttrString("rnn_mode");
+      inputMode = op.attributes().getAttrString("input_mode");
+      direction = op.attributes().getAttrString("direction");
+      dropout = op.attributes().getAttrFloat("dropout");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      numProj = op.attributes().getAttrInt("num_proj");
+      isTraining = op.attributes().getAttrBool("is_training");
+      timeMajor = op.attributes().getAttrBool("time_major");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java
index 4c9166bc46d..13372cc1bbc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -106,19 +110,19 @@ private CudnnRNNBackprop(Operation operation) {
    * Factory method to create a class wrapping a new CudnnRNNBackpropV3 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param inputH the inputH value
-   * @param inputC the inputC value
-   * @param params the params value
-   * @param sequenceLengths the sequenceLengths value
-   * @param output the output value
-   * @param outputH the outputH value
-   * @param outputC the outputC value
-   * @param outputBackprop the outputBackprop value
-   * @param outputHBackprop the outputHBackprop value
-   * @param outputCBackprop the outputCBackprop value
-   * @param reserveSpace the reserveSpace value
-   * @param hostReserved the hostReserved value
+   * @param input The input value
+   * @param inputH The inputH value
+   * @param inputC The inputC value
+   * @param params The params value
+   * @param sequenceLengths The sequenceLengths value
+   * @param output The output value
+   * @param outputH The outputH value
+   * @param outputC The outputC value
+   * @param outputBackprop The outputBackprop value
+   * @param outputHBackprop The outputHBackprop value
+   * @param outputCBackprop The outputCBackprop value
+   * @param reserveSpace The reserveSpace value
+   * @param hostReserved The hostReserved value
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNBackpropV3} output and operands
    * @return a new instance of CudnnRNNBackprop
@@ -403,4 +407,143 @@ public Options timeMajor(Boolean timeMajor) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CudnnRNNBackprop<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The inputH input
+     */
+    public final Operand<T> inputH;
+
+    /**
+     * The inputC input
+     */
+    public final Operand<T> inputC;
+
+    /**
+     * The params input
+     */
+    public final Operand<T> params;
+
+    /**
+     * The sequenceLengths input
+     */
+    public final Operand<TInt32> sequenceLengths;
+
+    /**
+     * The output input
+     */
+    public final Operand<T> output;
+
+    /**
+     * The outputH input
+     */
+    public final Operand<T> outputH;
+
+    /**
+     * The outputC input
+     */
+    public final Operand<T> outputC;
+
+    /**
+     * The outputBackprop input
+     */
+    public final Operand<T> outputBackprop;
+
+    /**
+     * The outputHBackprop input
+     */
+    public final Operand<T> outputHBackprop;
+
+    /**
+     * The outputCBackprop input
+     */
+    public final Operand<T> outputCBackprop;
+
+    /**
+     * The reserveSpace input
+     */
+    public final Operand<T> reserveSpace;
+
+    /**
+     * The hostReserved input
+     */
+    public final Operand<? extends TType> hostReserved;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The rnnMode attribute
+     */
+    public final String rnnMode;
+
+    /**
+     * The inputMode attribute
+     */
+    public final String inputMode;
+
+    /**
+     * The direction attribute
+     */
+    public final String direction;
+
+    /**
+     * The dropout attribute
+     */
+    public final float dropout;
+
+    /**
+     * The seed attribute
+     */
+    public final long seed;
+
+    /**
+     * The seed2 attribute
+     */
+    public final long seed2;
+
+    /**
+     * The numProj attribute
+     */
+    public final long numProj;
+
+    /**
+     * The timeMajor attribute
+     */
+    public final boolean timeMajor;
+
+    public Inputs(GraphOperation op) {
+      super(new CudnnRNNBackprop<>(op), op, Arrays.asList("T", "rnn_mode", "input_mode", "direction", "dropout", "seed", "seed2", "num_proj", "time_major"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      inputH = (Operand<T>) op.input(inputIndex++);
+      inputC = (Operand<T>) op.input(inputIndex++);
+      params = (Operand<T>) op.input(inputIndex++);
+      sequenceLengths = (Operand<TInt32>) op.input(inputIndex++);
+      output = (Operand<T>) op.input(inputIndex++);
+      outputH = (Operand<T>) op.input(inputIndex++);
+      outputC = (Operand<T>) op.input(inputIndex++);
+      outputBackprop = (Operand<T>) op.input(inputIndex++);
+      outputHBackprop = (Operand<T>) op.input(inputIndex++);
+      outputCBackprop = (Operand<T>) op.input(inputIndex++);
+      reserveSpace = (Operand<T>) op.input(inputIndex++);
+      hostReserved = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      rnnMode = op.attributes().getAttrString("rnn_mode");
+      inputMode = op.attributes().getAttrString("input_mode");
+      direction = op.attributes().getAttrString("direction");
+      dropout = op.attributes().getAttrFloat("dropout");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      numProj = op.attributes().getAttrInt("num_proj");
+      timeMajor = op.attributes().getAttrBool("time_major");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java
index ca5b35320f8..eeda8931a7b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -83,11 +87,11 @@ private CudnnRNNCanonicalToParams(Operation operation) {
    * Factory method to create a class wrapping a new CudnnRNNCanonicalToParamsV2 operation.
    *
    * @param scope current scope
-   * @param numLayers the numLayers value
-   * @param numUnits the numUnits value
-   * @param inputSize the inputSize value
-   * @param weights the weights value
-   * @param biases the biases value
+   * @param numLayers The numLayers value
+   * @param numUnits The numUnits value
+   * @param inputSize The inputSize value
+   * @param weights The weights value
+   * @param biases The biases value
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNCanonicalToParamsV2} output and operands
    * @return a new instance of CudnnRNNCanonicalToParams
@@ -314,4 +318,93 @@ public Options numProj(Long numProj) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CudnnRNNCanonicalToParams<T>> {
+    /**
+     * The numLayers input
+     */
+    public final Operand<TInt32> numLayers;
+
+    /**
+     * The numUnits input
+     */
+    public final Operand<TInt32> numUnits;
+
+    /**
+     * The inputSize input
+     */
+    public final Operand<TInt32> inputSize;
+
+    /**
+     * The weights input
+     */
+    public final Iterable<Operand<T>> weights;
+
+    /**
+     * The biases input
+     */
+    public final Iterable<Operand<T>> biases;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The rnnMode attribute
+     */
+    public final String rnnMode;
+
+    /**
+     * The inputMode attribute
+     */
+    public final String inputMode;
+
+    /**
+     * The direction attribute
+     */
+    public final String direction;
+
+    /**
+     * The dropout attribute
+     */
+    public final float dropout;
+
+    /**
+     * The seed attribute
+     */
+    public final long seed;
+
+    /**
+     * The seed2 attribute
+     */
+    public final long seed2;
+
+    /**
+     * The numProj attribute
+     */
+    public final long numProj;
+
+    public Inputs(GraphOperation op) {
+      super(new CudnnRNNCanonicalToParams<>(op), op, Arrays.asList("T", "rnn_mode", "input_mode", "direction", "dropout", "seed", "seed2", "num_proj"));
+      int inputIndex = 0;
+      numLayers = (Operand<TInt32>) op.input(inputIndex++);
+      numUnits = (Operand<TInt32>) op.input(inputIndex++);
+      inputSize = (Operand<TInt32>) op.input(inputIndex++);
+      int weightsLength = op.inputListLength("weights");
+      weights = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, weightsLength));
+      inputIndex += weightsLength;
+      int biasesLength = op.inputListLength("biases");
+      biases = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, biasesLength));
+      inputIndex += biasesLength;
+      T = op.attributes().getAttrType("T");
+      rnnMode = op.attributes().getAttrString("rnn_mode");
+      inputMode = op.attributes().getAttrString("input_mode");
+      direction = op.attributes().getAttrString("direction");
+      dropout = op.attributes().getAttrFloat("dropout");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      numProj = op.attributes().getAttrInt("num_proj");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java
index 4f161d810f5..4cfdf128902 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -92,12 +95,12 @@ private CudnnRNNParamsToCanonical(Operation operation) {
    * Factory method to create a class wrapping a new CudnnRNNParamsToCanonicalV2 operation.
    *
    * @param scope current scope
-   * @param numLayers the numLayers value
-   * @param numUnits the numUnits value
-   * @param inputSize the inputSize value
-   * @param params the params value
-   * @param numParamsWeights the value of the numParamsWeights property
-   * @param numParamsBiases the value of the numParamsBiases property
+   * @param numLayers The numLayers value
+   * @param numUnits The numUnits value
+   * @param inputSize The inputSize value
+   * @param params The params value
+   * @param numParamsWeights The value of the numParamsWeights attribute
+   * @param numParamsBiases The value of the numParamsBiases attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNParamsToCanonicalV2} output and operands
    * @return a new instance of CudnnRNNParamsToCanonical
@@ -329,4 +332,83 @@ public Options numProj(Long numProj) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CudnnRNNParamsToCanonical<T>> {
+    /**
+     * The numLayers input
+     */
+    public final Operand<TInt32> numLayers;
+
+    /**
+     * The numUnits input
+     */
+    public final Operand<TInt32> numUnits;
+
+    /**
+     * The inputSize input
+     */
+    public final Operand<TInt32> inputSize;
+
+    /**
+     * The params input
+     */
+    public final Operand<T> params;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The rnnMode attribute
+     */
+    public final String rnnMode;
+
+    /**
+     * The inputMode attribute
+     */
+    public final String inputMode;
+
+    /**
+     * The direction attribute
+     */
+    public final String direction;
+
+    /**
+     * The dropout attribute
+     */
+    public final float dropout;
+
+    /**
+     * The seed attribute
+     */
+    public final long seed;
+
+    /**
+     * The seed2 attribute
+     */
+    public final long seed2;
+
+    /**
+     * The numProj attribute
+     */
+    public final long numProj;
+
+    public Inputs(GraphOperation op) {
+      super(new CudnnRNNParamsToCanonical<>(op), op, Arrays.asList("T", "rnn_mode", "input_mode", "direction", "dropout", "seed", "seed2", "num_proj"));
+      int inputIndex = 0;
+      numLayers = (Operand<TInt32>) op.input(inputIndex++);
+      numUnits = (Operand<TInt32>) op.input(inputIndex++);
+      inputSize = (Operand<TInt32>) op.input(inputIndex++);
+      params = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      rnnMode = op.attributes().getAttrString("rnn_mode");
+      inputMode = op.attributes().getAttrString("input_mode");
+      direction = op.attributes().getAttrString("direction");
+      dropout = op.attributes().getAttrFloat("dropout");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      numProj = op.attributes().getAttrInt("num_proj");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java
index 676460b8765..2dd40e8cfad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -75,11 +79,11 @@ private CudnnRnnParamsSize(Operation operation) {
    * Factory method to create a class wrapping a new CudnnRNNParamsSize operation.
    *
    * @param scope current scope
-   * @param numLayers the numLayers value
-   * @param numUnits the numUnits value
-   * @param inputSize the inputSize value
-   * @param T the value of the T property
-   * @param S the value of the S property
+   * @param numLayers The numLayers value
+   * @param numUnits The numUnits value
+   * @param inputSize The inputSize value
+   * @param T The value of the T attribute
+   * @param S The value of the S attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code CudnnRNNParamsSize} output and operands
    * @param <U> data type for {@code CudnnRNNParamsSize} output and operands
@@ -307,4 +311,83 @@ public Options numProj(Long numProj) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<CudnnRnnParamsSize<?>> {
+    /**
+     * The numLayers input
+     */
+    public final Operand<TInt32> numLayers;
+
+    /**
+     * The numUnits input
+     */
+    public final Operand<TInt32> numUnits;
+
+    /**
+     * The inputSize input
+     */
+    public final Operand<TInt32> inputSize;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The S attribute
+     */
+    public final DataType S;
+
+    /**
+     * The rnnMode attribute
+     */
+    public final String rnnMode;
+
+    /**
+     * The inputMode attribute
+     */
+    public final String inputMode;
+
+    /**
+     * The direction attribute
+     */
+    public final String direction;
+
+    /**
+     * The dropout attribute
+     */
+    public final float dropout;
+
+    /**
+     * The seed attribute
+     */
+    public final long seed;
+
+    /**
+     * The seed2 attribute
+     */
+    public final long seed2;
+
+    /**
+     * The numProj attribute
+     */
+    public final long numProj;
+
+    public Inputs(GraphOperation op) {
+      super(new CudnnRnnParamsSize<>(op), op, Arrays.asList("T", "S", "rnn_mode", "input_mode", "direction", "dropout", "seed", "seed2", "num_proj"));
+      int inputIndex = 0;
+      numLayers = (Operand<TInt32>) op.input(inputIndex++);
+      numUnits = (Operand<TInt32>) op.input(inputIndex++);
+      inputSize = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      S = op.attributes().getAttrType("S");
+      rnnMode = op.attributes().getAttrString("rnn_mode");
+      inputMode = op.attributes().getAttrString("input_mode");
+      direction = op.attributes().getAttrString("direction");
+      dropout = op.attributes().getAttrFloat("dropout");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      numProj = op.attributes().getAttrInt("num_proj");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java
index 1ce3cba2ce5..95cf7c41dd0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -147,4 +151,36 @@ public Options dstFormat(String dstFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<DataFormatDimMap<T>> {
+    /**
+     * A Tensor with each element as a dimension index in source data format.
+     * Must be in the range [-4, 4).
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * source data format.
+     */
+    public final String srcFormat;
+
+    /**
+     * destination data format.
+     */
+    public final String dstFormat;
+
+    public Inputs(GraphOperation op) {
+      super(new DataFormatDimMap<>(op), op, Arrays.asList("T", "src_format", "dst_format"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      srcFormat = op.attributes().getAttrString("src_format");
+      dstFormat = op.attributes().getAttrString("dst_format");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java
index 73e7653b3a7..df1a3825d4b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -164,4 +168,35 @@ public Options dstFormat(String dstFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<DataFormatVecPermute<T>> {
+    /**
+     * Vector of size 4 or Tensor of shape (4, 2) in source data format.
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * source data format.
+     */
+    public final String srcFormat;
+
+    /**
+     * destination data format.
+     */
+    public final String dstFormat;
+
+    public Inputs(GraphOperation op) {
+      super(new DataFormatVecPermute<>(op), op, Arrays.asList("T", "src_format", "dst_format"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      srcFormat = op.attributes().getAttrString("src_format");
+      dstFormat = op.attributes().getAttrString("dst_format");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java
index 2e22c5f1658..2d2d46b500b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -127,7 +131,7 @@ private DepthToSpace(Operation operation) {
    * Factory method to create a class wrapping a new DepthToSpace operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param blockSize The size of the spatial block, same as in Space2Depth.
    * @param options carries optional attribute values
    * @param <T> data type for {@code DepthToSpace} output and operands
@@ -195,4 +199,35 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DepthToSpace<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The size of the spatial block, same as in Space2Depth.
+     */
+    public final long blockSize;
+
+    /**
+     * The dataFormat attribute
+     */
+    public final String dataFormat;
+
+    public Inputs(GraphOperation op) {
+      super(new DepthToSpace<>(op), op, Arrays.asList("T", "block_size", "data_format"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      blockSize = op.attributes().getAttrInt("block_size");
+      dataFormat = op.attributes().getAttrString("data_format");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java
index 262ae8aaeab..929cd0737ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -71,8 +74,8 @@ private DepthwiseConv2dNative(Operation operation) {
    * Factory method to create a class wrapping a new DepthwiseConv2dNative operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
+   * @param input The input value
+   * @param filter The filter value
    * @param strides 1-D of length 4.  The stride of the sliding window for each dimension
    * of {@code input}.
    * @param padding The type of padding algorithm to use.
@@ -134,7 +137,7 @@ public static Options explicitPaddings(List<Long> explicitPaddings) {
    * @param explicitPaddings the explicitPaddings option
    * @return this Options instance.
    */
-  public static Options explicitPaddings(Long[] explicitPaddings) {
+  public static Options explicitPaddings(Long... explicitPaddings) {
     return new Options().explicitPaddings(explicitPaddings);
   }
 
@@ -176,7 +179,7 @@ public static Options dilations(List<Long> dilations) {
    * dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -274,4 +277,68 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<DepthwiseConv2dNative<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<T> filter;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * 1-D of length 4.  The stride of the sliding window for each dimension
+     * of `input`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The explicitPaddings attribute
+     */
+    public final long[] explicitPaddings;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, height, width, channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, channels, height, width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 4.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each filter
+     * element on that dimension. The dimension order is determined by the value of
+     * `data_format`, see above for details. Dilations in the batch and depth
+     * dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new DepthwiseConv2dNative<>(op), op, Arrays.asList("T", "strides", "padding", "explicit_paddings", "data_format", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      explicitPaddings = op.attributes().getAttrIntList("explicit_paddings");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java
index 07e30fc3001..9e80ec91386 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -128,7 +131,7 @@ public static Options explicitPaddings(List<Long> explicitPaddings) {
    * @param explicitPaddings the explicitPaddings option
    * @return this Options instance.
    */
-  public static Options explicitPaddings(Long[] explicitPaddings) {
+  public static Options explicitPaddings(Long... explicitPaddings) {
     return new Options().explicitPaddings(explicitPaddings);
   }
 
@@ -170,7 +173,7 @@ public static Options dilations(List<Long> dilations) {
    * dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -270,4 +273,80 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<DepthwiseConv2dNativeBackpropFilter<T>> {
+    /**
+     * 4-D with shape based on {@code data_format}.  For example, if
+     * {@code data_format} is 'NHWC' then {@code input} is a 4-D {@code [batch, in_height, in_width, in_channels]} tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * An integer vector representing the tensor shape of {@code filter},
+     * where {@code filter} is a 4-D
+     * {@code [filter_height, filter_width, in_channels, depthwise_multiplier]} tensor.
+     */
+    public final Operand<TInt32> filterSizes;
+
+    /**
+     * 4-D with shape  based on {@code data_format}.
+     * For example, if {@code data_format} is 'NHWC' then
+     * out_backprop shape is {@code [batch, out_height, out_width, out_channels]}.
+     * Gradients w.r.t. the output of the convolution.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * of the convolution.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The explicitPaddings attribute
+     */
+    public final long[] explicitPaddings;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, height, width, channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, channels, height, width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 4.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each filter
+     * element on that dimension. The dimension order is determined by the value of
+     * `data_format`, see above for details. Dilations in the batch and depth
+     * dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new DepthwiseConv2dNativeBackpropFilter<>(op), op, Arrays.asList("T", "strides", "padding", "explicit_paddings", "data_format", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filterSizes = (Operand<TInt32>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      explicitPaddings = op.attributes().getAttrIntList("explicit_paddings");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java
index 392345ee075..57baa455eaf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -128,7 +131,7 @@ public static Options explicitPaddings(List<Long> explicitPaddings) {
    * @param explicitPaddings the explicitPaddings option
    * @return this Options instance.
    */
-  public static Options explicitPaddings(Long[] explicitPaddings) {
+  public static Options explicitPaddings(Long... explicitPaddings) {
     return new Options().explicitPaddings(explicitPaddings);
   }
 
@@ -170,7 +173,7 @@ public static Options dilations(List<Long> dilations) {
    * dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -270,4 +273,80 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<DepthwiseConv2dNativeBackpropInput<T>> {
+    /**
+     * An integer vector representing the shape of {@code input}, based
+     * on {@code data_format}.  For example, if {@code data_format} is 'NHWC' then
+     * {@code input} is a 4-D {@code [batch, height, width, channels]} tensor.
+     */
+    public final Operand<TInt32> inputSizes;
+
+    /**
+     * 4-D with shape
+     * {@code [filter_height, filter_width, in_channels, depthwise_multiplier]}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * 4-D with shape  based on {@code data_format}.
+     * For example, if {@code data_format} is 'NHWC' then
+     * out_backprop shape is {@code [batch, out_height, out_width, out_channels]}.
+     * Gradients w.r.t. the output of the convolution.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * of the convolution.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The explicitPaddings attribute
+     */
+    public final long[] explicitPaddings;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, height, width, channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, channels, height, width].
+     */
+    public final String dataFormat;
+
+    /**
+     * 1-D tensor of length 4.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each filter
+     * element on that dimension. The dimension order is determined by the value of
+     * `data_format`, see above for details. Dilations in the batch and depth
+     * dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new DepthwiseConv2dNativeBackpropInput<>(op), op, Arrays.asList("T", "strides", "padding", "explicit_paddings", "data_format", "dilations"));
+      int inputIndex = 0;
+      inputSizes = (Operand<TInt32>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      explicitPaddings = op.attributes().getAttrIntList("explicit_paddings");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java
index a070c09c659..2eced92585f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -120,4 +124,49 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Dilation2d<T>> {
+    /**
+     * 4-D with shape {@code [batch, in_height, in_width, depth]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 3-D with shape {@code [filter_height, filter_width, depth]}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * tensor. Must be: `[1, stride_height, stride_width, 1]`.
+     */
+    public final long[] strides;
+
+    /**
+     * The input stride for atrous morphological dilation. Must be:
+     * `[1, rate_height, rate_width, 1]`.
+     */
+    public final long[] rates;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new Dilation2d<>(op), op, Arrays.asList("T", "strides", "rates", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      rates = op.attributes().getAttrIntList("rates");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java
index e4b191ab199..baa0e803e8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -102,4 +106,55 @@ public Output<T> filterBackprop() {
   public Output<T> asOutput() {
     return filterBackprop;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Dilation2dBackpropFilter<T>> {
+    /**
+     * 4-D with shape {@code [batch, in_height, in_width, depth]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 3-D with shape {@code [filter_height, filter_width, depth]}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * 4-D with shape {@code [batch, out_height, out_width, depth]}.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * 1-D of length 4. The stride of the sliding window for each dimension of
+     * the input tensor. Must be: `[1, stride_height, stride_width, 1]`.
+     */
+    public final long[] strides;
+
+    /**
+     * 1-D of length 4. The input stride for atrous morphological dilation.
+     * Must be: `[1, rate_height, rate_width, 1]`.
+     */
+    public final long[] rates;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new Dilation2dBackpropFilter<>(op), op, Arrays.asList("T", "strides", "rates", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      rates = op.attributes().getAttrIntList("rates");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java
index 12e8a9b2094..2a11f34c905 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -102,4 +106,55 @@ public Output<T> inBackprop() {
   public Output<T> asOutput() {
     return inBackprop;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Dilation2dBackpropInput<T>> {
+    /**
+     * 4-D with shape {@code [batch, in_height, in_width, depth]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 3-D with shape {@code [filter_height, filter_width, depth]}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * 4-D with shape {@code [batch, out_height, out_width, depth]}.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * 1-D of length 4. The stride of the sliding window for each dimension of
+     * the input tensor. Must be: `[1, stride_height, stride_width, 1]`.
+     */
+    public final long[] strides;
+
+    /**
+     * 1-D of length 4. The input stride for atrous morphological dilation.
+     * Must be: `[1, rate_height, rate_width, 1]`.
+     */
+    public final long[] rates;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new Dilation2dBackpropInput<>(op), op, Arrays.asList("T", "strides", "rates", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      rates = op.attributes().getAttrIntList("rates");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java
index 801e842cd57..0060e99d5f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -73,7 +77,7 @@ private Elu(Operation operation) {
    * Factory method to create a class wrapping a new Elu operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Elu} output and operands
    * @return a new instance of Elu
    */
@@ -99,4 +103,23 @@ public Output<T> activations() {
   public Output<T> asOutput() {
     return activations;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Elu<T>> {
+    /**
+     * The features input
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Elu<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java
index 01b0f59507a..7d3af9d8535 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -79,4 +83,29 @@ public Output<T> backprops() {
   public Output<T> asOutput() {
     return backprops;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<EluGrad<T>> {
+    /**
+     * The backpropagated gradients to the corresponding Elu operation.
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The outputs of the corresponding Elu operation.
+     */
+    public final Operand<T> outputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new EluGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      outputs = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FixedUnigramCandidateSampler.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FixedUnigramCandidateSampler.java
index cd5a577fad0..d488683a39b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FixedUnigramCandidateSampler.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FixedUnigramCandidateSampler.java
@@ -19,11 +19,13 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -212,7 +214,7 @@ public static Options unigrams(List<Float> unigrams) {
    * order. Exactly one of vocab_file and unigrams should be passed to this op.
    * @return this Options instance.
    */
-  public static Options unigrams(Float[] unigrams) {
+  public static Options unigrams(Float... unigrams) {
     return new Options().unigrams(unigrams);
   }
 
@@ -413,4 +415,111 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FixedUnigramCandidateSampler> {
+    /**
+     * A batch_size * num_true matrix, in which each row contains the
+     * IDs of the num_true target_classes in the corresponding original label.
+     */
+    public final Operand<TInt64> trueClasses;
+
+    /**
+     * Number of true labels per context.
+     */
+    public final long numTrue;
+
+    /**
+     * Number of candidates to randomly sample.
+     */
+    public final long numSampled;
+
+    /**
+     * If unique is true, we sample with rejection, so that all sampled
+     * candidates in a batch are unique. This requires some approximation to
+     * estimate the post-rejection sampling probabilities.
+     */
+    public final boolean unique;
+
+    /**
+     * The sampler will sample integers from the interval [0, range_max).
+     */
+    public final long rangeMax;
+
+    /**
+     * Each valid line in this file (which should have a CSV-like format)
+     * corresponds to a valid word ID. IDs are in sequential order, starting from
+     * num_reserved_ids. The last entry in each line is expected to be a value
+     * corresponding to the count or relative probability. Exactly one of vocab_file
+     * and unigrams needs to be passed to this op.
+     */
+    public final String vocabFile;
+
+    /**
+     * The distortion is used to skew the unigram probability distribution.
+     * Each weight is first raised to the distortion's power before adding to the
+     * internal unigram distribution. As a result, distortion = 1.0 gives regular
+     * unigram sampling (as defined by the vocab file), and distortion = 0.0 gives
+     * a uniform distribution.
+     */
+    public final float distortion;
+
+    /**
+     * Optionally some reserved IDs can be added in the range [0,
+     * ..., num_reserved_ids) by the users. One use case is that a special unknown
+     * word token is used as ID 0. These IDs will have a sampling probability of 0.
+     */
+    public final long numReservedIds;
+
+    /**
+     * A sampler can be used to sample from a subset of the original range
+     * in order to speed up the whole computation through parallelism. This parameter
+     * (together with 'shard') indicates the number of partitions that are being
+     * used in the overall computation.
+     */
+    public final long numShards;
+
+    /**
+     * A sampler can be used to sample from a subset of the original range
+     * in order to speed up the whole computation through parallelism. This parameter
+     * (together with 'num_shards') indicates the particular partition number of a
+     * sampler op, when partitioning is being used.
+     */
+    public final long shard;
+
+    /**
+     * A list of unigram counts or probabilities, one per ID in sequential
+     * order. Exactly one of vocab_file and unigrams should be passed to this op.
+     */
+    public final float[] unigrams;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new FixedUnigramCandidateSampler(op), op, Arrays.asList("num_true", "num_sampled", "unique", "range_max", "vocab_file", "distortion", "num_reserved_ids", "num_shards", "shard", "unigrams", "seed", "seed2"));
+      int inputIndex = 0;
+      trueClasses = (Operand<TInt64>) op.input(inputIndex++);
+      numTrue = op.attributes().getAttrInt("num_true");
+      numSampled = op.attributes().getAttrInt("num_sampled");
+      unique = op.attributes().getAttrBool("unique");
+      rangeMax = op.attributes().getAttrInt("range_max");
+      vocabFile = op.attributes().getAttrString("vocab_file");
+      distortion = op.attributes().getAttrFloat("distortion");
+      numReservedIds = op.attributes().getAttrInt("num_reserved_ids");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shard = op.attributes().getAttrInt("shard");
+      unigrams = op.attributes().getAttrFloatList("unigrams");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java
index ae6c9ebb5e9..ce678467253 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -283,4 +287,79 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FractionalAvgPool<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> value;
+
+    /**
+     * Pooling ratio for each dimension of `value`, currently only
+     * supports row and col dimension and should be >= 1.0. For example, a valid
+     * pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements
+     * must be 1.0 because we don't allow pooling on batch and channels
+     * dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions
+     * respectively.
+     */
+    public final float[] poolingRatio;
+
+    /**
+     * When set to True, generates the pooling sequence in a
+     * pseudorandom fashion, otherwise, in a random fashion. Check paper [Benjamin
+     * Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071) for
+     * difference between pseudorandom and random.
+     */
+    public final boolean pseudoRandom;
+
+    /**
+     * When set to True, it means when pooling, the values at the boundary
+     * of adjacent pooling cells are used by both cells. For example:
+     *
+     * `index  0  1  2  3  4`
+     *
+     * `value  20 5  16 3  7`
+     *
+     * If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
+     * The result would be [41/3, 26/3] for fractional avg pooling.
+     */
+    public final boolean overlapping;
+
+    /**
+     * When set to True, a fixed pooling region will be used when
+     * iterating over a FractionalAvgPool node in the computation graph. Mainly used
+     * in unit test to make FractionalAvgPool deterministic.
+     */
+    public final boolean deterministic;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FractionalAvgPool<>(op), op, Arrays.asList("pooling_ratio", "pseudo_random", "overlapping", "deterministic", "seed", "seed2", "T"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      poolingRatio = op.attributes().getAttrFloatList("pooling_ratio");
+      pseudoRandom = op.attributes().getAttrBool("pseudo_random");
+      overlapping = op.attributes().getAttrBool("overlapping");
+      deterministic = op.attributes().getAttrBool("deterministic");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java
index c703f47835a..0cfd7f8e7d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -141,4 +145,58 @@ public Options overlapping(Boolean overlapping) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FractionalAvgPoolGrad<T>> {
+    /**
+     * Original input tensor shape for {@code fractional_avg_pool}
+     */
+    public final Operand<TInt64> origInputTensorShape;
+
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.  Gradients
+     * w.r.t. the output of {@code fractional_avg_pool}.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * row pooling sequence, form pooling region with
+     * col_pooling_sequence.
+     */
+    public final Operand<TInt64> rowPoolingSequence;
+
+    /**
+     * column pooling sequence, form pooling region with
+     * row_pooling sequence.
+     */
+    public final Operand<TInt64> colPoolingSequence;
+
+    /**
+     * When set to True, it means when pooling, the values at the boundary
+     * of adjacent pooling cells are used by both cells. For example:
+     *
+     * `index  0  1  2  3  4`
+     *
+     * `value  20 5  16 3  7`
+     *
+     * If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
+     * The result would be [41/3, 26/3] for fractional avg pooling.
+     */
+    public final boolean overlapping;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FractionalAvgPoolGrad<>(op), op, Arrays.asList("overlapping", "T"));
+      int inputIndex = 0;
+      origInputTensorShape = (Operand<TInt64>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      rowPoolingSequence = (Operand<TInt64>) op.input(inputIndex++);
+      colPoolingSequence = (Operand<TInt64>) op.input(inputIndex++);
+      overlapping = op.attributes().getAttrBool("overlapping");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java
index 44e4cd682c6..f1733ed28cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -305,4 +309,79 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FractionalMaxPool<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> value;
+
+    /**
+     * Pooling ratio for each dimension of `value`, currently only
+     * supports row and col dimension and should be >= 1.0. For example, a valid
+     * pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements
+     * must be 1.0 because we don't allow pooling on batch and channels
+     * dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions
+     * respectively.
+     */
+    public final float[] poolingRatio;
+
+    /**
+     * When set to True, generates the pooling sequence in a
+     * pseudorandom fashion, otherwise, in a random fashion. Check paper [Benjamin
+     * Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071) for
+     * difference between pseudorandom and random.
+     */
+    public final boolean pseudoRandom;
+
+    /**
+     * When set to True, it means when pooling, the values at the boundary
+     * of adjacent pooling cells are used by both cells. For example:
+     *
+     * `index  0  1  2  3  4`
+     *
+     * `value  20 5  16 3  7`
+     *
+     * If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
+     * The result would be [20, 16] for fractional max pooling.
+     */
+    public final boolean overlapping;
+
+    /**
+     * When set to True, a fixed pooling region will be used when
+     * iterating over a FractionalMaxPool node in the computation graph. Mainly used
+     * in unit test to make FractionalMaxPool deterministic.
+     */
+    public final boolean deterministic;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FractionalMaxPool<>(op), op, Arrays.asList("pooling_ratio", "pseudo_random", "overlapping", "deterministic", "seed", "seed2", "T"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      poolingRatio = op.attributes().getAttrFloatList("pooling_ratio");
+      pseudoRandom = op.attributes().getAttrBool("pseudo_random");
+      overlapping = op.attributes().getAttrBool("overlapping");
+      deterministic = op.attributes().getAttrBool("deterministic");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java
index b9f75ea53bb..5233a6b19f1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -138,4 +142,64 @@ public Options overlapping(Boolean overlapping) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FractionalMaxPoolGrad<T>> {
+    /**
+     * Original input for {@code fractional_max_pool}
+     */
+    public final Operand<T> origInput;
+
+    /**
+     * Original output for {@code fractional_max_pool}
+     */
+    public final Operand<T> origOutput;
+
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.  Gradients
+     * w.r.t. the output of {@code fractional_max_pool}.
+     */
+    public final Operand<T> outBackprop;
+
+    /**
+     * row pooling sequence, form pooling region with
+     * col_pooling_sequence.
+     */
+    public final Operand<TInt64> rowPoolingSequence;
+
+    /**
+     * column pooling sequence, form pooling region with
+     * row_pooling sequence.
+     */
+    public final Operand<TInt64> colPoolingSequence;
+
+    /**
+     * When set to True, it means when pooling, the values at the boundary
+     * of adjacent pooling cells are used by both cells. For example:
+     *
+     * `index  0  1  2  3  4`
+     *
+     * `value  20 5  16 3  7`
+     *
+     * If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
+     * The result would be [20, 16] for fractional max pooling.
+     */
+    public final boolean overlapping;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new FractionalMaxPoolGrad<>(op), op, Arrays.asList("overlapping", "T"));
+      int inputIndex = 0;
+      origInput = (Operand<T>) op.input(inputIndex++);
+      origOutput = (Operand<T>) op.input(inputIndex++);
+      outBackprop = (Operand<T>) op.input(inputIndex++);
+      rowPoolingSequence = (Operand<TInt64>) op.input(inputIndex++);
+      colPoolingSequence = (Operand<TInt64>) op.input(inputIndex++);
+      overlapping = op.attributes().getAttrBool("overlapping");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java
index b832e66d0f9..a216c600ff7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -275,4 +279,80 @@ public Options isTraining(Boolean isTraining) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<FusedBatchNorm<T, U>> {
+    /**
+     * A 4D Tensor for input data.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A 1D Tensor for scaling factor, to scale the normalized x.
+     */
+    public final Operand<U> scale;
+
+    /**
+     * A 1D Tensor for offset, to shift to the normalized x.
+     */
+    public final Operand<U> offset;
+
+    /**
+     * A 1D Tensor for population mean. Used for inference only;
+     * must be empty for training.
+     */
+    public final Operand<U> mean;
+
+    /**
+     * A 1D Tensor for population variance. Used for inference only;
+     * must be empty for training.
+     */
+    public final Operand<U> variance;
+
+    /**
+     * The data type for the elements of input and output Tensors.
+     */
+    public final DataType T;
+
+    /**
+     * The data type for the scale, offset, mean, and variance.
+     */
+    public final DataType U;
+
+    /**
+     * A small float number added to the variance of x.
+     */
+    public final float epsilon;
+
+    /**
+     * The exponentialAvgFactor attribute
+     */
+    public final float exponentialAvgFactor;
+
+    /**
+     * The data format for x and y. Either "NHWC" (default) or "NCHW".
+     */
+    public final String dataFormat;
+
+    /**
+     * A bool value to indicate the operation is for training (default)
+     * or inference.
+     */
+    public final boolean isTraining;
+
+    public Inputs(GraphOperation op) {
+      super(new FusedBatchNorm<>(op), op, Arrays.asList("T", "U", "epsilon", "exponential_avg_factor", "data_format", "is_training"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      scale = (Operand<U>) op.input(inputIndex++);
+      offset = (Operand<U>) op.input(inputIndex++);
+      mean = (Operand<U>) op.input(inputIndex++);
+      variance = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      U = op.attributes().getAttrType("U");
+      epsilon = op.attributes().getAttrFloat("epsilon");
+      exponentialAvgFactor = op.attributes().getAttrFloat("exponential_avg_factor");
+      dataFormat = op.attributes().getAttrString("data_format");
+      isTraining = op.attributes().getAttrBool("is_training");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java
index d72aa33d4ee..a423903c502 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -245,4 +249,88 @@ public Options isTraining(Boolean isTraining) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<FusedBatchNormGrad<T, U>> {
+    /**
+     * A 4D Tensor for the gradient with respect to y.
+     */
+    public final Operand<T> yBackprop;
+
+    /**
+     * A 4D Tensor for input data.
+     */
+    public final Operand<T> x;
+
+    /**
+     * A 1D Tensor for scaling factor, to scale the normalized x.
+     */
+    public final Operand<TFloat32> scale;
+
+    /**
+     * When is_training is True, a 1D Tensor for the computed batch
+     * mean to be reused in gradient computation. When is_training is
+     * False, a 1D Tensor for the population mean to be reused in both
+     * 1st and 2nd order gradient computation.
+     */
+    public final Operand<U> reserveSpace1;
+
+    /**
+     * When is_training is True, a 1D Tensor for the computed batch
+     * variance (inverted variance in the cuDNN case) to be reused in
+     * gradient computation. When is_training is False, a 1D Tensor
+     * for the population variance to be reused in both 1st and 2nd
+     * order gradient computation.
+     */
+    public final Operand<U> reserveSpace2;
+
+    /**
+     * When is_training is True, a 1D Tensor for some intermediate results to be reused
+     * in gradient computation. When is_training is False, a dummy empty Tensor will be
+     * created.
+     */
+    public final Operand<U> reserveSpace3;
+
+    /**
+     * The data type for the elements of input and output Tensors.
+     */
+    public final DataType T;
+
+    /**
+     * The data type for the scale, offset, mean, and variance.
+     */
+    public final DataType U;
+
+    /**
+     * A small float number added to the variance of x.
+     */
+    public final float epsilon;
+
+    /**
+     * The data format for y_backprop, x, x_backprop.
+     * Either "NHWC" (default) or "NCHW".
+     */
+    public final String dataFormat;
+
+    /**
+     * A bool value to indicate the operation is for training (default)
+     * or inference.
+     */
+    public final boolean isTraining;
+
+    public Inputs(GraphOperation op) {
+      super(new FusedBatchNormGrad<>(op), op, Arrays.asList("T", "U", "epsilon", "data_format", "is_training"));
+      int inputIndex = 0;
+      yBackprop = (Operand<T>) op.input(inputIndex++);
+      x = (Operand<T>) op.input(inputIndex++);
+      scale = (Operand<TFloat32>) op.input(inputIndex++);
+      reserveSpace1 = (Operand<U>) op.input(inputIndex++);
+      reserveSpace2 = (Operand<U>) op.input(inputIndex++);
+      reserveSpace3 = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      U = op.attributes().getAttrType("U");
+      epsilon = op.attributes().getAttrFloat("epsilon");
+      dataFormat = op.attributes().getAttrString("data_format");
+      isTraining = op.attributes().getAttrBool("is_training");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java
index 2ca95bdf8ed..3d938544bd8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -71,7 +75,7 @@ private FusedPadConv2d(Operation operation) {
    * rows must be the same as the rank of {@code input}.
    * @param filter 4-D with shape
    * {@code [filter_height, filter_width, in_channels, out_channels]}.
-   * @param mode the value of the mode property
+   * @param mode The value of the mode attribute
    * @param strides 1-D of length 4.  The stride of the sliding window for each dimension
    * of {@code input}. Must be in the same order as the dimension specified with format.
    * @param padding The type of padding algorithm to use.
@@ -111,4 +115,56 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FusedPadConv2d<T>> {
+    /**
+     * 4-D with shape {@code [batch, in_height, in_width, in_channels]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A two-column matrix specifying the padding sizes. The number of
+     * rows must be the same as the rank of {@code input}.
+     */
+    public final Operand<TInt32> paddings;
+
+    /**
+     * 4-D with shape
+     * {@code [filter_height, filter_width, in_channels, out_channels]}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The mode attribute
+     */
+    public final String mode;
+
+    /**
+     * 1-D of length 4.  The stride of the sliding window for each dimension
+     * of `input`. Must be in the same order as the dimension specified with format.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new FusedPadConv2d<>(op), op, Arrays.asList("T", "mode", "strides", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      paddings = (Operand<TInt32>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      mode = op.attributes().getAttrString("mode");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java
index 85ede719c12..1d072dbf388 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -72,7 +76,7 @@ private FusedResizeAndPadConv2d(Operation operation) {
    * rows must be the same as the rank of {@code input}.
    * @param filter 4-D with shape
    * {@code [filter_height, filter_width, in_channels, out_channels]}.
-   * @param mode the value of the mode property
+   * @param mode The value of the mode attribute
    * @param strides 1-D of length 4.  The stride of the sliding window for each dimension
    * of {@code input}. Must be in the same order as the dimension specified with format.
    * @param padding The type of padding algorithm to use.
@@ -154,4 +158,70 @@ public Options resizeAlignCorners(Boolean resizeAlignCorners) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<FusedResizeAndPadConv2d<T>> {
+    /**
+     * 4-D with shape {@code [batch, in_height, in_width, in_channels]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}.  The
+     * new size for the images.
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * A two-column matrix specifying the padding sizes. The number of
+     * rows must be the same as the rank of {@code input}.
+     */
+    public final Operand<TInt32> paddings;
+
+    /**
+     * 4-D with shape
+     * {@code [filter_height, filter_width, in_channels, out_channels]}.
+     */
+    public final Operand<T> filter;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If true, the centers of the 4 corner pixels of the input and output tensors are
+     * aligned, preserving the values at the corner pixels. Defaults to false.
+     */
+    public final boolean resizeAlignCorners;
+
+    /**
+     * The mode attribute
+     */
+    public final String mode;
+
+    /**
+     * 1-D of length 4.  The stride of the sliding window for each dimension
+     * of `input`. Must be in the same order as the dimension specified with format.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new FusedResizeAndPadConv2d<>(op), op, Arrays.asList("T", "resize_align_corners", "mode", "strides", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      paddings = (Operand<TInt32>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      resizeAlignCorners = op.attributes().getAttrBool("resize_align_corners");
+      mode = op.attributes().getAttrString("mode");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java
index f097c11d9ba..a78808f3977 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -96,12 +100,12 @@ private GRUBlockCell(Operation operation) {
    * Factory method to create a class wrapping a new GRUBlockCell operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param hPrev the hPrev value
-   * @param wRu the wRu value
-   * @param wC the wC value
-   * @param bRu the bRu value
-   * @param bC the bC value
+   * @param x The x value
+   * @param hPrev The hPrev value
+   * @param wRu The wRu value
+   * @param wC The wC value
+   * @param bRu The bRu value
+   * @param bC The bC value
    * @param <T> data type for {@code GRUBlockCell} output and operands
    * @return a new instance of GRUBlockCell
    */
@@ -155,4 +159,53 @@ public Output<T> c() {
   public Output<T> h() {
     return h;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<GRUBlockCell<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The hPrev input
+     */
+    public final Operand<T> hPrev;
+
+    /**
+     * The wRu input
+     */
+    public final Operand<T> wRu;
+
+    /**
+     * The wC input
+     */
+    public final Operand<T> wC;
+
+    /**
+     * The bRu input
+     */
+    public final Operand<T> bRu;
+
+    /**
+     * The bC input
+     */
+    public final Operand<T> bC;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new GRUBlockCell<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      hPrev = (Operand<T>) op.input(inputIndex++);
+      wRu = (Operand<T>) op.input(inputIndex++);
+      wC = (Operand<T>) op.input(inputIndex++);
+      bRu = (Operand<T>) op.input(inputIndex++);
+      bC = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java
index 7491f7e22d4..b2a324662d1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -131,16 +135,16 @@ private GRUBlockCellGrad(Operation operation) {
    * Factory method to create a class wrapping a new GRUBlockCellGrad operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param hPrev the hPrev value
-   * @param wRu the wRu value
-   * @param wC the wC value
-   * @param bRu the bRu value
-   * @param bC the bC value
-   * @param r the r value
-   * @param u the u value
-   * @param c the c value
-   * @param dH the dH value
+   * @param x The x value
+   * @param hPrev The hPrev value
+   * @param wRu The wRu value
+   * @param wC The wC value
+   * @param bRu The bRu value
+   * @param bC The bC value
+   * @param r The r value
+   * @param u The u value
+   * @param c The c value
+   * @param dH The dH value
    * @param <T> data type for {@code GRUBlockCellGrad} output and operands
    * @return a new instance of GRUBlockCellGrad
    */
@@ -199,4 +203,77 @@ public Output<T> dCBar() {
   public Output<T> dRBarUBar() {
     return dRBarUBar;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<GRUBlockCellGrad<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The hPrev input
+     */
+    public final Operand<T> hPrev;
+
+    /**
+     * The wRu input
+     */
+    public final Operand<T> wRu;
+
+    /**
+     * The wC input
+     */
+    public final Operand<T> wC;
+
+    /**
+     * The bRu input
+     */
+    public final Operand<T> bRu;
+
+    /**
+     * The bC input
+     */
+    public final Operand<T> bC;
+
+    /**
+     * The r input
+     */
+    public final Operand<T> r;
+
+    /**
+     * The u input
+     */
+    public final Operand<T> u;
+
+    /**
+     * The c input
+     */
+    public final Operand<T> c;
+
+    /**
+     * The dH input
+     */
+    public final Operand<T> dH;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new GRUBlockCellGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      hPrev = (Operand<T>) op.input(inputIndex++);
+      wRu = (Operand<T>) op.input(inputIndex++);
+      wC = (Operand<T>) op.input(inputIndex++);
+      bRu = (Operand<T>) op.input(inputIndex++);
+      bC = (Operand<T>) op.input(inputIndex++);
+      r = (Operand<T>) op.input(inputIndex++);
+      u = (Operand<T>) op.input(inputIndex++);
+      c = (Operand<T>) op.input(inputIndex++);
+      dH = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java
index f6ba25f9885..43b2d73ac08 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
@@ -95,4 +99,35 @@ public Output<TBool> precision() {
   public Output<TBool> asOutput() {
     return precision;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<InTopK> {
+    /**
+     * A {@code batch_size} x {@code classes} tensor.
+     */
+    public final Operand<TFloat32> predictions;
+
+    /**
+     * A {@code batch_size} vector of class ids.
+     */
+    public final Operand<T> targets;
+
+    /**
+     * Number of top elements to look at for computing precision.
+     */
+    public final Operand<T> k;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new InTopK(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      predictions = (Operand<TFloat32>) op.input(inputIndex++);
+      targets = (Operand<T>) op.input(inputIndex++);
+      k = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java
index 0e8c241594d..bb095a412bb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,8 +55,8 @@ private InvGrad(Operation operation) {
    * Factory method to create a class wrapping a new InvGrad operation.
    *
    * @param scope current scope
-   * @param y the y value
-   * @param dy the dy value
+   * @param y The y value
+   * @param dy The dy value
    * @param <T> data type for {@code InvGrad} output and operands
    * @return a new instance of InvGrad
    */
@@ -79,4 +83,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<InvGrad<T>> {
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The dy input
+     */
+    public final Operand<T> dy;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new InvGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      y = (Operand<T>) op.input(inputIndex++);
+      dy = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java
index 20b1c7f5145..2da787ebe0b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -102,4 +106,29 @@ public Output<U> output() {
   public Output<TInt32> segments() {
     return segments;
   }
+
+  public static class Inputs extends RawOpInputs<IsotonicRegression<?>> {
+    /**
+     * A (batch_size, dim)-tensor holding a batch of inputs.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Dtype of output.
+     */
+    public final DataType outputDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new IsotonicRegression<>(op), op, Arrays.asList("T", "output_dtype"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outputDtype = op.attributes().getAttrType("output_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java
index 7f747028c27..e4b2fcf5d47 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -83,4 +87,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<L2Loss<T>> {
+    /**
+     * Typically 2-D, but may have any dimensions.
+     */
+    public final Operand<T> t;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new L2Loss<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      t = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java
index b64f2d1ad90..4f3067b63e7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -271,4 +275,83 @@ public Options usePeephole(Boolean usePeephole) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LSTMBlockCell<T>> {
+    /**
+     * The input to the LSTM cell, shape (batch_size, num_inputs).
+     */
+    public final Operand<T> x;
+
+    /**
+     * Value of the cell state at previous time step.
+     */
+    public final Operand<T> csPrev;
+
+    /**
+     * Output of the previous cell at previous time step.
+     */
+    public final Operand<T> hPrev;
+
+    /**
+     * The weight matrix.
+     */
+    public final Operand<T> w;
+
+    /**
+     * The weight matrix for input gate peephole connection.
+     */
+    public final Operand<T> wci;
+
+    /**
+     * The weight matrix for forget gate peephole connection.
+     */
+    public final Operand<T> wcf;
+
+    /**
+     * The weight matrix for output gate peephole connection.
+     */
+    public final Operand<T> wco;
+
+    /**
+     * The bias vector.
+     */
+    public final Operand<T> b;
+
+    /**
+     * The forget gate bias.
+     */
+    public final float forgetBias;
+
+    /**
+     * Value to clip the 'cs' value to.
+     */
+    public final float cellClip;
+
+    /**
+     * Whether to use peephole weights.
+     */
+    public final boolean usePeephole;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LSTMBlockCell<>(op), op, Arrays.asList("forget_bias", "cell_clip", "use_peephole", "T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      csPrev = (Operand<T>) op.input(inputIndex++);
+      hPrev = (Operand<T>) op.input(inputIndex++);
+      w = (Operand<T>) op.input(inputIndex++);
+      wci = (Operand<T>) op.input(inputIndex++);
+      wcf = (Operand<T>) op.input(inputIndex++);
+      wco = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      forgetBias = op.attributes().getAttrFloat("forget_bias");
+      cellClip = op.attributes().getAttrFloat("cell_clip");
+      usePeephole = op.attributes().getAttrBool("use_peephole");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java
index d2049d0183b..b20e2482520 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -154,4 +158,119 @@ public Output<T> wcfGrad() {
   public Output<T> wcoGrad() {
     return wcoGrad;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LSTMBlockCellGrad<T>> {
+    /**
+     * The input to the LSTM cell, shape (batch_size, num_inputs).
+     */
+    public final Operand<T> x;
+
+    /**
+     * The previous cell state.
+     */
+    public final Operand<T> csPrev;
+
+    /**
+     * The previous h state.
+     */
+    public final Operand<T> hPrev;
+
+    /**
+     * The weight matrix.
+     */
+    public final Operand<T> w;
+
+    /**
+     * The weight matrix for input gate peephole connection.
+     */
+    public final Operand<T> wci;
+
+    /**
+     * The weight matrix for forget gate peephole connection.
+     */
+    public final Operand<T> wcf;
+
+    /**
+     * The weight matrix for output gate peephole connection.
+     */
+    public final Operand<T> wco;
+
+    /**
+     * The bias vector.
+     */
+    public final Operand<T> b;
+
+    /**
+     * The input gate.
+     */
+    public final Operand<T> i;
+
+    /**
+     * The cell state before the tanh.
+     */
+    public final Operand<T> cs;
+
+    /**
+     * The forget gate.
+     */
+    public final Operand<T> f;
+
+    /**
+     * The output gate.
+     */
+    public final Operand<T> o;
+
+    /**
+     * The cell input.
+     */
+    public final Operand<T> ci;
+
+    /**
+     * The cell after the tanh.
+     */
+    public final Operand<T> co;
+
+    /**
+     * The current gradient of cs.
+     */
+    public final Operand<T> csGrad;
+
+    /**
+     * The gradient of h vector.
+     */
+    public final Operand<T> hGrad;
+
+    /**
+     * Whether the cell uses peephole connections.
+     */
+    public final boolean usePeephole;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LSTMBlockCellGrad<>(op), op, Arrays.asList("use_peephole", "T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      csPrev = (Operand<T>) op.input(inputIndex++);
+      hPrev = (Operand<T>) op.input(inputIndex++);
+      w = (Operand<T>) op.input(inputIndex++);
+      wci = (Operand<T>) op.input(inputIndex++);
+      wcf = (Operand<T>) op.input(inputIndex++);
+      wco = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      i = (Operand<T>) op.input(inputIndex++);
+      cs = (Operand<T>) op.input(inputIndex++);
+      f = (Operand<T>) op.input(inputIndex++);
+      o = (Operand<T>) op.input(inputIndex++);
+      ci = (Operand<T>) op.input(inputIndex++);
+      co = (Operand<T>) op.input(inputIndex++);
+      csGrad = (Operand<T>) op.input(inputIndex++);
+      hGrad = (Operand<T>) op.input(inputIndex++);
+      usePeephole = op.attributes().getAttrBool("use_peephole");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java
index 1d13c658e78..b02c71ea25a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private LeakyRelu(Operation operation) {
    * Factory method to create a class wrapping a new LeakyRelu operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param options carries optional attribute values
    * @param <T> data type for {@code LeakyRelu} output and operands
    * @return a new instance of LeakyRelu
@@ -119,4 +123,29 @@ public Options alpha(Float alpha) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LeakyRelu<T>> {
+    /**
+     * The features input
+     */
+    public final Operand<T> features;
+
+    /**
+     * The alpha attribute
+     */
+    public final float alpha;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LeakyRelu<>(op), op, Arrays.asList("alpha", "T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      alpha = op.attributes().getAttrFloat("alpha");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LearnedUnigramCandidateSampler.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LearnedUnigramCandidateSampler.java
index f9dede20ce7..0e0c5633f34 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LearnedUnigramCandidateSampler.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LearnedUnigramCandidateSampler.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -190,4 +193,58 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LearnedUnigramCandidateSampler> {
+    /**
+     * A batch_size * num_true matrix, in which each row contains the
+     * IDs of the num_true target_classes in the corresponding original label.
+     */
+    public final Operand<TInt64> trueClasses;
+
+    /**
+     * Number of true labels per context.
+     */
+    public final long numTrue;
+
+    /**
+     * Number of candidates to randomly sample.
+     */
+    public final long numSampled;
+
+    /**
+     * If unique is true, we sample with rejection, so that all sampled
+     * candidates in a batch are unique. This requires some approximation to
+     * estimate the post-rejection sampling probabilities.
+     */
+    public final boolean unique;
+
+    /**
+     * The sampler will sample integers from the interval [0, range_max).
+     */
+    public final long rangeMax;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new LearnedUnigramCandidateSampler(op), op, Arrays.asList("num_true", "num_sampled", "unique", "range_max", "seed", "seed2"));
+      int inputIndex = 0;
+      trueClasses = (Operand<TInt64>) op.input(inputIndex++);
+      numTrue = op.attributes().getAttrInt("num_true");
+      numSampled = op.attributes().getAttrInt("num_sampled");
+      unique = op.attributes().getAttrBool("unique");
+      rangeMax = op.attributes().getAttrInt("range_max");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java
index 1fd9649c309..826c443cf64 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -208,4 +212,47 @@ public Options beta(Float beta) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LocalResponseNormalization<T>> {
+    /**
+     * 4-D.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 0-D.  Half-width of the 1-D normalization window.
+     */
+    public final long depthRadius;
+
+    /**
+     * An offset (usually positive to avoid dividing by 0).
+     */
+    public final float bias;
+
+    /**
+     * A scale factor, usually positive.
+     */
+    public final float alpha;
+
+    /**
+     * An exponent.
+     */
+    public final float beta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LocalResponseNormalization<>(op), op, Arrays.asList("depth_radius", "bias", "alpha", "beta", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      depthRadius = op.attributes().getAttrInt("depth_radius");
+      bias = op.attributes().getAttrFloat("bias");
+      alpha = op.attributes().getAttrFloat("alpha");
+      beta = op.attributes().getAttrFloat("beta");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java
index 57d51c9daf1..d3ef3925776 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -197,4 +201,59 @@ public Options beta(Float beta) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LocalResponseNormalizationGrad<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> inputGrads;
+
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> inputImage;
+
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> outputImage;
+
+    /**
+     * A depth radius.
+     */
+    public final long depthRadius;
+
+    /**
+     * An offset (usually > 0 to avoid dividing by 0).
+     */
+    public final float bias;
+
+    /**
+     * A scale factor, usually positive.
+     */
+    public final float alpha;
+
+    /**
+     * An exponent.
+     */
+    public final float beta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LocalResponseNormalizationGrad<>(op), op, Arrays.asList("depth_radius", "bias", "alpha", "beta", "T"));
+      int inputIndex = 0;
+      inputGrads = (Operand<T>) op.input(inputIndex++);
+      inputImage = (Operand<T>) op.input(inputIndex++);
+      outputImage = (Operand<T>) op.input(inputIndex++);
+      depthRadius = op.attributes().getAttrInt("depth_radius");
+      bias = op.attributes().getAttrFloat("bias");
+      alpha = op.attributes().getAttrFloat("alpha");
+      beta = op.attributes().getAttrFloat("beta");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java
index a70ad1ba80d..82f178f0e1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -83,4 +87,23 @@ public Output<T> logsoftmax() {
   public Output<T> asOutput() {
     return logsoftmax;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<LogSoftmax<T>> {
+    /**
+     * 2-D with shape {@code [batch_size, num_classes]}.
+     */
+    public final Operand<T> logits;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new LogSoftmax<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      logits = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java
index 630374f0888..52286432580 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -135,4 +139,52 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPool<T>> {
+    /**
+     * 4-D input to pool over.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     */
+    public final Operand<TInt32> ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the
+     * input tensor.
+     */
+    public final Operand<TInt32> strides;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPool<>(op), op, Arrays.asList("T", "padding", "data_format"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      ksize = (Operand<TInt32>) op.input(inputIndex++);
+      strides = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java
index 321a5dcb029..5d9bfdffa7d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -144,4 +148,53 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPool3d<T>> {
+    /**
+     * Shape {@code [batch, depth, rows, cols, channels]} tensor to pool over.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 1-D tensor of length 5. The size of the window for each dimension of
+     * the input tensor. Must have `ksize[0] = ksize[4] = 1`.
+     */
+    public final long[] ksize;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPool3d<>(op), op, Arrays.asList("ksize", "strides", "padding", "data_format", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java
index f3f0ec2b5cf..2bfe76491b4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -150,4 +154,71 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<MaxPool3dGrad<U>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<T> origInput;
+
+    /**
+     * The original output tensor.
+     */
+    public final Operand<T> origOutput;
+
+    /**
+     * Output backprop of shape {@code [batch, depth, rows, cols, channels]}.
+     */
+    public final Operand<U> grad;
+
+    /**
+     * 1-D tensor of length 5. The size of the window for each dimension of
+     * the input tensor. Must have `ksize[0] = ksize[4] = 1`.
+     */
+    public final long[] ksize;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The TInput attribute
+     */
+    public final DataType TInput;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPool3dGrad<>(op), op, Arrays.asList("ksize", "strides", "padding", "data_format", "T", "TInput"));
+      int inputIndex = 0;
+      origInput = (Operand<T>) op.input(inputIndex++);
+      origOutput = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<U>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+      TInput = op.attributes().getAttrType("TInput");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java
index 79673ef2121..0db33576167 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -149,4 +153,65 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPool3dGradGrad<T>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<T> origInput;
+
+    /**
+     * The original output tensor.
+     */
+    public final Operand<T> origOutput;
+
+    /**
+     * Output backprop of shape {@code [batch, depth, rows, cols, channels]}.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * 1-D tensor of length 5. The size of the window for each dimension of
+     * the input tensor. Must have `ksize[0] = ksize[4] = 1`.
+     */
+    public final long[] ksize;
+
+    /**
+     * 1-D tensor of length 5. The stride of the sliding window for each
+     * dimension of `input`. Must have `strides[0] = strides[4] = 1`.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * The data format of the input and output data. With the
+     * default format "NDHWC", the data is stored in the order of:
+     *     [batch, in_depth, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCDHW", the data storage order is:
+     *     [batch, in_channels, in_depth, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPool3dGradGrad<>(op), op, Arrays.asList("ksize", "strides", "padding", "data_format", "T"));
+      int inputIndex = 0;
+      origInput = (Operand<T>) op.input(inputIndex++);
+      origOutput = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java
index 60129b28217..a2e15973e80 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -140,4 +144,64 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPoolGrad<T>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<T> origInput;
+
+    /**
+     * The original output tensor.
+     */
+    public final Operand<T> origOutput;
+
+    /**
+     * 4-D.  Gradients w.r.t. the output of {@code max_pool}.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     */
+    public final Operand<TInt32> ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the
+     * input tensor.
+     */
+    public final Operand<TInt32> strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPoolGrad<>(op), op, Arrays.asList("padding", "data_format", "T"));
+      int inputIndex = 0;
+      origInput = (Operand<T>) op.input(inputIndex++);
+      origOutput = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      ksize = (Operand<TInt32>) op.input(inputIndex++);
+      strides = (Operand<TInt32>) op.input(inputIndex++);
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java
index 7be3b57875e..baeb0c83a39 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -140,4 +144,64 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPoolGradGrad<T>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<T> origInput;
+
+    /**
+     * The original output tensor.
+     */
+    public final Operand<T> origOutput;
+
+    /**
+     * 4-D.  Gradients of gradients w.r.t. the input of {@code max_pool}.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     */
+    public final Operand<TInt32> ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the
+     * input tensor.
+     */
+    public final Operand<TInt32> strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Specify the data format of the input and output data. With the
+     * default format "NHWC", the data is stored in the order of:
+     *     [batch, in_height, in_width, in_channels].
+     * Alternatively, the format could be "NCHW", the data storage order of:
+     *     [batch, in_channels, in_height, in_width].
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPoolGradGrad<>(op), op, Arrays.asList("padding", "data_format", "T"));
+      int inputIndex = 0;
+      origInput = (Operand<T>) op.input(inputIndex++);
+      origOutput = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      ksize = (Operand<TInt32>) op.input(inputIndex++);
+      strides = (Operand<TInt32>) op.input(inputIndex++);
+      padding = op.attributes().getAttrString("padding");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java
index 2e617fa36c4..e9acc1d5cc9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -141,4 +145,67 @@ public Options includeBatchInIndex(Boolean includeBatchInIndex) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPoolGradGradWithArgmax<T>> {
+    /**
+     * The original input.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.  Gradients w.r.t. the
+     * input of {@code max_pool}.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The indices of the maximum values chosen for each output of {@code max_pool}.
+     */
+    public final Operand<? extends TNumber> argmax;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     */
+    public final long[] ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the
+     * input tensor.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Whether to include batch dimension in flattened index of `argmax`.
+     */
+    public final boolean includeBatchInIndex;
+
+    /**
+     * The Targmax attribute
+     */
+    public final DataType Targmax;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPoolGradGradWithArgmax<>(op), op, Arrays.asList("ksize", "strides", "padding", "include_batch_in_index", "Targmax", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      argmax = (Operand<? extends TNumber>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      includeBatchInIndex = op.attributes().getAttrBool("include_batch_in_index");
+      Targmax = op.attributes().getAttrType("Targmax");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java
index 79d6a05146e..b2fd0acb7e3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -137,4 +141,67 @@ public Options includeBatchInIndex(Boolean includeBatchInIndex) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPoolGradWithArgmax<T>> {
+    /**
+     * The original input.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.  Gradients w.r.t. the
+     * output of {@code max_pool}.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The indices of the maximum values chosen for each output of {@code max_pool}.
+     */
+    public final Operand<? extends TNumber> argmax;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     */
+    public final long[] ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the
+     * input tensor.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Whether to include batch dimension in flattened index of `argmax`.
+     */
+    public final boolean includeBatchInIndex;
+
+    /**
+     * The Targmax attribute
+     */
+    public final DataType Targmax;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPoolGradWithArgmax<>(op), op, Arrays.asList("ksize", "strides", "padding", "include_batch_in_index", "Targmax", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      argmax = (Operand<? extends TNumber>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      includeBatchInIndex = op.attributes().getAttrBool("include_batch_in_index");
+      Targmax = op.attributes().getAttrType("Targmax");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java
index f3685f3aa0e..42e6dfbefb5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -73,7 +77,7 @@ private MaxPoolWithArgmax(Operation operation) {
    * @param ksize The size of the window for each dimension of the input tensor.
    * @param strides The stride of the sliding window for each dimension of the
    * input tensor.
-   * @param Targmax the value of the Targmax property
+   * @param Targmax The value of the Targmax attribute
    * @param padding The type of padding algorithm to use.
    * @param options carries optional attribute values
    * @param <T> data type for {@code MaxPoolWithArgmax} output and operands
@@ -179,4 +183,54 @@ public Options includeBatchInIndex(Boolean includeBatchInIndex) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<MaxPoolWithArgmax<T, ?>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.  Input to pool over.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     */
+    public final long[] ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the
+     * input tensor.
+     */
+    public final long[] strides;
+
+    /**
+     * The Targmax attribute
+     */
+    public final DataType Targmax;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * Whether to include batch dimension in flattened index of `argmax`.
+     */
+    public final boolean includeBatchInIndex;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new MaxPoolWithArgmax<>(op), op, Arrays.asList("ksize", "strides", "Targmax", "padding", "include_batch_in_index", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      Targmax = op.attributes().getAttrType("Targmax");
+      padding = op.attributes().getAttrString("padding");
+      includeBatchInIndex = op.attributes().getAttrBool("include_batch_in_index");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java
index 47f38a213fb..14df47bbcc2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -132,4 +136,37 @@ public Options reverse(Boolean reverse) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<NthElement<T>> {
+    /**
+     * 1-D or higher with last dimension at least {@code n+1}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 0-D. Position of sorted vector to select along the last dimension (along
+     * each row for matrices). Valid range of n is {@code [0, input.shape[:-1])}
+     */
+    public final Operand<TInt32> n;
+
+    /**
+     * When set to True, find the nth-largest value in the vector and vice
+     * versa.
+     */
+    public final boolean reverse;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new NthElement<>(op), op, Arrays.asList("reverse", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      n = (Operand<TInt32>) op.input(inputIndex++);
+      reverse = op.attributes().getAttrBool("reverse");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java
index d9ae295a485..bceac12fb5d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -122,4 +126,55 @@ public Output<TFloat32> minOutput() {
   public Output<TFloat32> maxOutput() {
     return maxOutput;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizedAvgPool<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, channels]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The float value that the lowest quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the highest quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     * The length must be 4 to match the number of dimensions of the input.
+     */
+    public final long[] ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * tensor.  The length must be 4 to match the number of dimensions of the input.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedAvgPool<>(op), op, Arrays.asList("T", "ksize", "strides", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java
index f7d54b8efa4..7ff416e12ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -85,7 +89,7 @@ private QuantizedBatchNormWithGlobalNormalization(Operation operation) {
    * with the normalized tensor.
    * @param gammaMin The value represented by the lowest quantized gamma.
    * @param gammaMax The value represented by the highest quantized gamma.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param varianceEpsilon A small float number to avoid dividing by 0.
    * @param scaleAfterNormalization A bool indicating whether the resulted tensor
    * needs to be multiplied with gamma.
@@ -150,4 +154,133 @@ public Output<TFloat32> resultMin() {
   public Output<TFloat32> resultMax() {
     return resultMax;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizedBatchNormWithGlobalNormalization<?>> {
+    /**
+     * A 4D input Tensor.
+     */
+    public final Operand<T> t;
+
+    /**
+     * The value represented by the lowest quantized input.
+     */
+    public final Operand<TFloat32> tMin;
+
+    /**
+     * The value represented by the highest quantized input.
+     */
+    public final Operand<TFloat32> tMax;
+
+    /**
+     * A 1D mean Tensor with size matching the last dimension of t.
+     * This is the first output from tf.nn.moments,
+     * or a saved moving average thereof.
+     */
+    public final Operand<T> m;
+
+    /**
+     * The value represented by the lowest quantized mean.
+     */
+    public final Operand<TFloat32> mMin;
+
+    /**
+     * The value represented by the highest quantized mean.
+     */
+    public final Operand<TFloat32> mMax;
+
+    /**
+     * A 1D variance Tensor with size matching the last dimension of t.
+     * This is the second output from tf.nn.moments,
+     * or a saved moving average thereof.
+     */
+    public final Operand<T> v;
+
+    /**
+     * The value represented by the lowest quantized variance.
+     */
+    public final Operand<TFloat32> vMin;
+
+    /**
+     * The value represented by the highest quantized variance.
+     */
+    public final Operand<TFloat32> vMax;
+
+    /**
+     * A 1D beta Tensor with size matching the last dimension of t.
+     * An offset to be added to the normalized tensor.
+     */
+    public final Operand<T> beta;
+
+    /**
+     * The value represented by the lowest quantized offset.
+     */
+    public final Operand<TFloat32> betaMin;
+
+    /**
+     * The value represented by the highest quantized offset.
+     */
+    public final Operand<TFloat32> betaMax;
+
+    /**
+     * A 1D gamma Tensor with size matching the last dimension of t.
+     * If &quot;scale_after_normalization&quot; is true, this tensor will be multiplied
+     * with the normalized tensor.
+     */
+    public final Operand<T> gamma;
+
+    /**
+     * The value represented by the lowest quantized gamma.
+     */
+    public final Operand<TFloat32> gammaMin;
+
+    /**
+     * The value represented by the highest quantized gamma.
+     */
+    public final Operand<TFloat32> gammaMax;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * A small float number to avoid dividing by 0.
+     */
+    public final float varianceEpsilon;
+
+    /**
+     * A bool indicating whether the resulted tensor
+     * needs to be multiplied with gamma.
+     */
+    public final boolean scaleAfterNormalization;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedBatchNormWithGlobalNormalization<>(op), op, Arrays.asList("Tinput", "out_type", "variance_epsilon", "scale_after_normalization"));
+      int inputIndex = 0;
+      t = (Operand<T>) op.input(inputIndex++);
+      tMin = (Operand<TFloat32>) op.input(inputIndex++);
+      tMax = (Operand<TFloat32>) op.input(inputIndex++);
+      m = (Operand<T>) op.input(inputIndex++);
+      mMin = (Operand<TFloat32>) op.input(inputIndex++);
+      mMax = (Operand<TFloat32>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      vMin = (Operand<TFloat32>) op.input(inputIndex++);
+      vMax = (Operand<TFloat32>) op.input(inputIndex++);
+      beta = (Operand<T>) op.input(inputIndex++);
+      betaMin = (Operand<TFloat32>) op.input(inputIndex++);
+      betaMax = (Operand<TFloat32>) op.input(inputIndex++);
+      gamma = (Operand<T>) op.input(inputIndex++);
+      gammaMin = (Operand<TFloat32>) op.input(inputIndex++);
+      gammaMax = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      outType = op.attributes().getAttrType("out_type");
+      varianceEpsilon = op.attributes().getAttrFloat("variance_epsilon");
+      scaleAfterNormalization = op.attributes().getAttrBool("scale_after_normalization");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java
index ac9a8fc2861..a646479464f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -62,13 +66,13 @@ private QuantizedBiasAdd(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedBiasAdd operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param bias A 1D bias Tensor with size matching the last dimension of 'input'.
    * @param minInput The float value that the lowest quantized input value represents.
    * @param maxInput The float value that the highest quantized input value represents.
    * @param minBias The float value that the lowest quantized bias value represents.
    * @param maxBias The float value that the highest quantized bias value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <V> data type for {@code QuantizedBiasAdd} output and operands
    * @return a new instance of QuantizedBiasAdd
    */
@@ -116,4 +120,65 @@ public Output<TFloat32> minOut() {
   public Output<TFloat32> maxOut() {
     return maxOut;
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedBiasAdd<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * A 1D bias Tensor with size matching the last dimension of 'input'.
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The float value that the lowest quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the highest quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The float value that the lowest quantized bias value represents.
+     */
+    public final Operand<TFloat32> minBias;
+
+    /**
+     * The float value that the highest quantized bias value represents.
+     */
+    public final Operand<TFloat32> maxBias;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedBiasAdd<>(op), op, Arrays.asList("T1", "T2", "out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minBias = (Operand<TFloat32>) op.input(inputIndex++);
+      maxBias = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java
index c7980b56a44..ec7cfb17939 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,15 +62,15 @@ private QuantizedConv2DAndRelu(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DAndRelu operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedConv2DAndRelu} output and operands
    * @return a new instance of QuantizedConv2DAndRelu
@@ -131,7 +134,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -151,7 +154,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -237,4 +240,89 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DAndRelu<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DAndRelu<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java
index e4adb5cf7f9..c50cda07ac7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,17 +62,17 @@ private QuantizedConv2DAndReluAndRequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DAndReluAndRequantize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedConv2DAndReluAndRequantize} output and operands
    * @return a new instance of QuantizedConv2DAndReluAndRequantize
@@ -136,7 +139,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -156,7 +159,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -242,4 +245,101 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DAndReluAndRequantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DAndReluAndRequantize<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java
index c4f415ebf8a..8fcd6d5e6e6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,17 +62,17 @@ private QuantizedConv2DAndRequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DAndRequantize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedConv2DAndRequantize} output and operands
    * @return a new instance of QuantizedConv2DAndRequantize
@@ -136,7 +139,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -156,7 +159,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -242,4 +245,101 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DAndRequantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DAndRequantize<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java
index eb8860fde35..cd45b84d21f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -67,7 +70,7 @@ private QuantizedConv2DPerChannel(Operation operation) {
    * @param maxFilter The maximum value of the filter tensor.
    * @param outType The quantized type of output tensor that needs to be converted.
    * @param strides list of stride values.
-   * @param padding the value of the padding property
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedConv2DPerChannel} output and operands
    * @return a new instance of QuantizedConv2DPerChannel
@@ -124,7 +127,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations list of dilation values.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -186,4 +189,83 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DPerChannel<?>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The original filter tensor.
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The minimum value of the input tensor
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maximum value of the input tensor.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minimum value of the filter tensor.
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maximum value of the filter tensor.
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The quantized type of input tensor that needs to be converted.
+     */
+    public final DataType Tinput;
+
+    /**
+     * The quantized type of filter tensor that needs to be converted.
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The quantized type of output tensor that needs to be converted.
+     */
+    public final DataType outType;
+
+    /**
+     * list of stride values.
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * list of dilation values.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DPerChannel<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java
index ccdd59f9d22..aae3f6b2ce1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,16 +62,16 @@ private QuantizedConv2DWithBias(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DWithBias operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param bias the bias value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param bias The bias value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedConv2DWithBias} output and operands
    * @return a new instance of QuantizedConv2DWithBias
@@ -133,7 +136,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -153,7 +156,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -239,4 +242,95 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DWithBias<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The bias input
+     */
+    public final Operand<TFloat32> bias;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DWithBias<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<TFloat32>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java
index 591734ef5f1..060fb88ec1f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,16 +62,16 @@ private QuantizedConv2DWithBiasAndRelu(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DWithBiasAndRelu operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param bias the bias value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param bias The bias value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedConv2DWithBiasAndRelu} output and operands
    * @return a new instance of QuantizedConv2DWithBiasAndRelu
@@ -133,7 +136,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -153,7 +156,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -239,4 +242,95 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DWithBiasAndRelu<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The bias input
+     */
+    public final Operand<TFloat32> bias;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DWithBiasAndRelu<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<TFloat32>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java
index 238d0e6a440..9709b6afc6d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,18 +62,18 @@ private QuantizedConv2DWithBiasAndReluAndRequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DWithBiasAndReluAndRequantize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param bias the bias value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param bias The bias value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <W> data type for {@code QuantizedConv2DWithBiasAndReluAndRequantize} output and operands
    * @return a new instance of QuantizedConv2DWithBiasAndReluAndRequantize
@@ -138,7 +141,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -158,7 +161,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -244,4 +247,113 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DWithBiasAndReluAndRequantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The bias input
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DWithBiasAndReluAndRequantize<>(op), op, Arrays.asList("Tinput", "Tfilter", "Tbias", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      Tbias = op.attributes().getAttrType("Tbias");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java
index cceca8676b0..478048a5504 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,18 +62,18 @@ private QuantizedConv2DWithBiasAndRequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DWithBiasAndRequantize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param bias the bias value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param bias The bias value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <W> data type for {@code QuantizedConv2DWithBiasAndRequantize} output and operands
    * @return a new instance of QuantizedConv2DWithBiasAndRequantize
@@ -138,7 +141,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -158,7 +161,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -244,4 +247,113 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DWithBiasAndRequantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The bias input
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DWithBiasAndRequantize<>(op), op, Arrays.asList("Tinput", "Tfilter", "Tbias", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      Tbias = op.attributes().getAttrType("Tbias");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java
index 07979421f05..e9e88ec8b2e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,21 +62,21 @@ private QuantizedConv2DWithBiasSignedSumAndReluAndRequantize(Operation operation
    * Factory method to create a class wrapping a new QuantizedConv2DWithBiasSignedSumAndReluAndRequantize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param bias the bias value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param summand the summand value
-   * @param minSummand the minSummand value
-   * @param maxSummand the maxSummand value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param bias The bias value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param summand The summand value
+   * @param minSummand The minSummand value
+   * @param maxSummand The maxSummand value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <X> data type for {@code QuantizedConv2DWithBiasSignedSumAndReluAndRequantize} output and operands
    * @return a new instance of QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
@@ -145,7 +148,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -165,7 +168,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -251,4 +254,137 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DWithBiasSignedSumAndReluAndRequantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The bias input
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The summand input
+     */
+    public final Operand<? extends TNumber> summand;
+
+    /**
+     * The minSummand input
+     */
+    public final Operand<TFloat32> minSummand;
+
+    /**
+     * The maxSummand input
+     */
+    public final Operand<TFloat32> maxSummand;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The Tsummand attribute
+     */
+    public final DataType Tsummand;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DWithBiasSignedSumAndReluAndRequantize<>(op), op, Arrays.asList("Tinput", "Tfilter", "Tbias", "Tsummand", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      summand = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minSummand = (Operand<TFloat32>) op.input(inputIndex++);
+      maxSummand = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      Tbias = op.attributes().getAttrType("Tbias");
+      Tsummand = op.attributes().getAttrType("Tsummand");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java
index 3ae339e9774..b3178a7b7c9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,17 +62,17 @@ private QuantizedConv2DWithBiasSumAndRelu(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DWithBiasSumAndRelu operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param bias the bias value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param summand the summand value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param bias The bias value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param summand The summand value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedConv2DWithBiasSumAndRelu} output and operands
    * @return a new instance of QuantizedConv2DWithBiasSumAndRelu
@@ -135,7 +138,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -155,7 +158,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -241,4 +244,101 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DWithBiasSumAndRelu<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The bias input
+     */
+    public final Operand<TFloat32> bias;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The summand input
+     */
+    public final Operand<TFloat32> summand;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DWithBiasSumAndRelu<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<TFloat32>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      summand = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java
index 53be5e9f6b0..0a173c9732d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,21 +62,21 @@ private QuantizedConv2DWithBiasSumAndReluAndRequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2DWithBiasSumAndReluAndRequantize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param bias the bias value
-   * @param minInput the minInput value
-   * @param maxInput the maxInput value
-   * @param minFilter the minFilter value
-   * @param maxFilter the maxFilter value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param summand the summand value
-   * @param minSummand the minSummand value
-   * @param maxSummand the maxSummand value
-   * @param outType the value of the outType property
-   * @param strides the value of the strides property
-   * @param padding the value of the padding property
+   * @param input The input value
+   * @param filter The filter value
+   * @param bias The bias value
+   * @param minInput The minInput value
+   * @param maxInput The maxInput value
+   * @param minFilter The minFilter value
+   * @param maxFilter The maxFilter value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param summand The summand value
+   * @param minSummand The minSummand value
+   * @param maxSummand The maxSummand value
+   * @param outType The value of the outType attribute
+   * @param strides The value of the strides attribute
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <X> data type for {@code QuantizedConv2DWithBiasSumAndReluAndRequantize} output and operands
    * @return a new instance of QuantizedConv2DWithBiasSumAndReluAndRequantize
@@ -145,7 +148,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -165,7 +168,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -251,4 +254,137 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2DWithBiasSumAndReluAndRequantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The bias input
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The minInput input
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The maxInput input
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The minFilter input
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The maxFilter input
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The summand input
+     */
+    public final Operand<? extends TNumber> summand;
+
+    /**
+     * The minSummand input
+     */
+    public final Operand<TFloat32> minSummand;
+
+    /**
+     * The maxSummand input
+     */
+    public final Operand<TFloat32> maxSummand;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The Tsummand attribute
+     */
+    public final DataType Tsummand;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2DWithBiasSumAndReluAndRequantize<>(op), op, Arrays.asList("Tinput", "Tfilter", "Tbias", "Tsummand", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      summand = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minSummand = (Operand<TFloat32>) op.input(inputIndex++);
+      maxSummand = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      Tbias = op.attributes().getAttrType("Tbias");
+      Tsummand = op.attributes().getAttrType("Tsummand");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java
index 3dabec4356c..6c6d3b373fd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java
@@ -19,15 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -67,13 +70,13 @@ private QuantizedConv2d(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedConv2D operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param filter filter's input_depth dimension must match input's depth dimensions.
    * @param minInput The float value that the lowest quantized input value represents.
    * @param maxInput The float value that the highest quantized input value represents.
    * @param minFilter The float value that the lowest quantized filter value represents.
    * @param maxFilter The float value that the highest quantized filter value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param strides The stride of the sliding window for each dimension of the input
    * tensor.
    * @param padding The type of padding algorithm to use.
@@ -141,7 +144,7 @@ public static Options dilations(List<Long> dilations) {
    * depth dimensions must be 1.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -211,4 +214,88 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedConv2d<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * filter's input_depth dimension must match input's depth dimensions.
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The float value that the lowest quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the highest quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The float value that the lowest quantized filter value represents.
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The float value that the highest quantized filter value represents.
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The Tfilter attribute
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * tensor.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    /**
+     * 1-D tensor of length 4.  The dilation factor for each dimension of
+     * `input`. If set to k > 1, there will be k-1 skipped cells between each
+     * filter element on that dimension. The dimension order is determined by the
+     * value of `data_format`, see above for details. Dilations in the batch and
+     * depth dimensions must be 1.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConv2d<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java
index 4c830ea0e04..2471c3ab08f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -67,7 +70,7 @@ private QuantizedDepthwiseConv2D(Operation operation) {
    * @param maxFilter The float value that the maximum quantized filter value represents.
    * @param outType The type of the output.
    * @param strides List of stride values.
-   * @param padding the value of the padding property
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedDepthwiseConv2D} output and operands
    * @return a new instance of QuantizedDepthwiseConv2D
@@ -124,7 +127,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations List of dilation values.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -186,4 +189,83 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedDepthwiseConv2D<?>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The original filter tensor.
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The float value that the minimum quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the maximum quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The float value that the minimum quantized filter value represents.
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The float value that the maximum quantized filter value represents.
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The type of the input.
+     */
+    public final DataType Tinput;
+
+    /**
+     * The type of the filter.
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType outType;
+
+    /**
+     * List of stride values.
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * List of dilation values.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedDepthwiseConv2D<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java
index b408de31728..4240f955a8d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -68,7 +71,7 @@ private QuantizedDepthwiseConv2DWithBias(Operation operation) {
    * @param maxFilter The float value that the maximum quantized filter value represents.
    * @param outType The type of the output.
    * @param strides List of stride values.
-   * @param padding the value of the padding property
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedDepthwiseConv2DWithBias} output and operands
    * @return a new instance of QuantizedDepthwiseConv2DWithBias
@@ -126,7 +129,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations List of dilation values.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -188,4 +191,89 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedDepthwiseConv2DWithBias<?>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The original filter tensor.
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The original bias tensor.
+     */
+    public final Operand<TFloat32> bias;
+
+    /**
+     * The float value that the minimum quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the maximum quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The float value that the minimum quantized filter value represents.
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The float value that the maximum quantized filter value represents.
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The type of the input.
+     */
+    public final DataType Tinput;
+
+    /**
+     * The type of the filter.
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType outType;
+
+    /**
+     * List of stride values.
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * List of dilation values.
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedDepthwiseConv2DWithBias<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<TFloat32>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java
index 70d0b72d0d1..b15046296b5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -68,7 +71,7 @@ private QuantizedDepthwiseConv2DWithBiasAndRelu(Operation operation) {
    * @param maxFilter The float value that the maximum quantized filter value represents.
    * @param outType The type of the output.
    * @param strides List of stride values.
-   * @param padding the value of the padding property
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code QuantizedDepthwiseConv2DWithBiasAndRelu} output and operands
    * @return a new instance of QuantizedDepthwiseConv2DWithBiasAndRelu
@@ -133,7 +136,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations List of dilation values.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -153,7 +156,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -239,4 +242,95 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedDepthwiseConv2DWithBiasAndRelu<?>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The original filter tensor.
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The original bias tensor.
+     */
+    public final Operand<TFloat32> bias;
+
+    /**
+     * The float value that the minimum quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the maximum quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The float value that the minimum quantized filter value represents.
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The float value that the maximum quantized filter value represents.
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The type of the input.
+     */
+    public final DataType Tinput;
+
+    /**
+     * The type of the filter.
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType outType;
+
+    /**
+     * List of stride values.
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * List of dilation values.
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedDepthwiseConv2DWithBiasAndRelu<>(op), op, Arrays.asList("Tinput", "Tfilter", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<TFloat32>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java
index 42c8519fdac..8b39158ccee 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -70,7 +73,7 @@ private QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize(Operation operation
    * @param maxFreezedOutput The maximum float value of the output tensor.
    * @param outType The type of the output.
    * @param strides List of stride values.
-   * @param padding the value of the padding property
+   * @param padding The value of the padding attribute
    * @param options carries optional attribute values
    * @param <W> data type for {@code QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize} output and operands
    * @return a new instance of QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
@@ -138,7 +141,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations List of dilation values.
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -158,7 +161,7 @@ public static Options paddingList(List<Long> paddingList) {
    * @param paddingList the paddingList option
    * @return this Options instance.
    */
-  public static Options paddingList(Long[] paddingList) {
+  public static Options paddingList(Long... paddingList) {
     return new Options().paddingList(paddingList);
   }
 
@@ -244,4 +247,113 @@ public Options paddingList(Long... paddingList) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize<?>> {
+    /**
+     * The original input tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The original filter tensor.
+     */
+    public final Operand<? extends TNumber> filter;
+
+    /**
+     * The original bias tensor.
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The float value that the minimum quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the maximum quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The float value that the minimum quantized filter value represents.
+     */
+    public final Operand<TFloat32> minFilter;
+
+    /**
+     * The float value that the maximum quantized filter value represents.
+     */
+    public final Operand<TFloat32> maxFilter;
+
+    /**
+     * The minimum float value of the output tensor.
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maximum float value of the output tensor.
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The type of the input.
+     */
+    public final DataType Tinput;
+
+    /**
+     * The type of the filter.
+     */
+    public final DataType Tfilter;
+
+    /**
+     * The type of the bias.
+     */
+    public final DataType Tbias;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType outType;
+
+    /**
+     * List of stride values.
+     */
+    public final long[] strides;
+
+    /**
+     * The padding attribute
+     */
+    public final String padding;
+
+    /**
+     * List of dilation values.
+     */
+    public final long[] dilations;
+
+    /**
+     * The paddingList attribute
+     */
+    public final long[] paddingList;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize<>(op), op, Arrays.asList("Tinput", "Tfilter", "Tbias", "out_type", "strides", "padding", "dilations", "padding_list"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      filter = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      minFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFilter = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      Tfilter = op.attributes().getAttrType("Tfilter");
+      Tbias = op.attributes().getAttrType("Tbias");
+      outType = op.attributes().getAttrType("out_type");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+      dilations = op.attributes().getAttrIntList("dilations");
+      paddingList = op.attributes().getAttrIntList("padding_list");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java
index 7c7ccfe2d62..3fcc9015f32 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -251,4 +255,67 @@ public Options minSeparation(Float minSeparation) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizedInstanceNorm<T>> {
+    /**
+     * A 4D input Tensor.
+     */
+    public final Operand<T> x;
+
+    /**
+     * The value represented by the lowest quantized input.
+     */
+    public final Operand<TFloat32> xMin;
+
+    /**
+     * The value represented by the highest quantized input.
+     */
+    public final Operand<TFloat32> xMax;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, `given_y_min` and `given_y_min`
+     * and `given_y_max` are used as the output range. Otherwise,
+     * the implementation computes the output range.
+     */
+    public final boolean outputRangeGiven;
+
+    /**
+     * Output in `y_min` if `output_range_given` is True.
+     */
+    public final float givenYMin;
+
+    /**
+     * Output in `y_max` if `output_range_given` is True.
+     */
+    public final float givenYMax;
+
+    /**
+     * A small float number to avoid dividing by 0.
+     */
+    public final float varianceEpsilon;
+
+    /**
+     * Minimum value of `y_max - y_min`
+     */
+    public final float minSeparation;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedInstanceNorm<>(op), op, Arrays.asList("T", "output_range_given", "given_y_min", "given_y_max", "variance_epsilon", "min_separation"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      xMin = (Operand<TFloat32>) op.input(inputIndex++);
+      xMax = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outputRangeGiven = op.attributes().getAttrBool("output_range_given");
+      givenYMin = op.attributes().getAttrFloat("given_y_min");
+      givenYMax = op.attributes().getAttrFloat("given_y_max");
+      varianceEpsilon = op.attributes().getAttrFloat("variance_epsilon");
+      minSeparation = op.attributes().getAttrFloat("min_separation");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java
index 9e31416dc48..57d54424778 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -122,4 +126,55 @@ public Output<TFloat32> minOutput() {
   public Output<TFloat32> maxOutput() {
     return maxOutput;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizedMaxPool<T>> {
+    /**
+     * The 4D (batch x rows x cols x depth) Tensor to MaxReduce over.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The float value that the lowest quantized input value represents.
+     */
+    public final Operand<TFloat32> minInput;
+
+    /**
+     * The float value that the highest quantized input value represents.
+     */
+    public final Operand<TFloat32> maxInput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The size of the window for each dimension of the input tensor.
+     * The length must be 4 to match the number of dimensions of the input.
+     */
+    public final long[] ksize;
+
+    /**
+     * The stride of the sliding window for each dimension of the input
+     * tensor. The length must be 4 to match the number of dimensions of the input.
+     */
+    public final long[] strides;
+
+    /**
+     * The type of padding algorithm to use.
+     */
+    public final String padding;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMaxPool<>(op), op, Arrays.asList("T", "ksize", "strides", "padding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      minInput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxInput = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      padding = op.attributes().getAttrString("padding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java
index a8021cf2c53..0f84eb38f99 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -61,10 +65,10 @@ private QuantizedRelu(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedRelu operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param minFeatures The float value that the lowest quantized value represents.
    * @param maxFeatures The float value that the highest quantized value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code QuantizedRelu} output and operands
    * @return a new instance of QuantizedRelu
    */
@@ -108,4 +112,41 @@ public Output<TFloat32> minActivations() {
   public Output<TFloat32> maxActivations() {
     return maxActivations;
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedRelu<?>> {
+    /**
+     * The features input
+     */
+    public final Operand<? extends TNumber> features;
+
+    /**
+     * The float value that the lowest quantized value represents.
+     */
+    public final Operand<TFloat32> minFeatures;
+
+    /**
+     * The float value that the highest quantized value represents.
+     */
+    public final Operand<TFloat32> maxFeatures;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedRelu<>(op), op, Arrays.asList("Tinput", "out_type"));
+      int inputIndex = 0;
+      features = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minFeatures = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFeatures = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java
index 713f3e800c3..ff29633a598 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -61,10 +65,10 @@ private QuantizedRelu6(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedRelu6 operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param minFeatures The float value that the lowest quantized value represents.
    * @param maxFeatures The float value that the highest quantized value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code QuantizedRelu6} output and operands
    * @return a new instance of QuantizedRelu6
    */
@@ -108,4 +112,41 @@ public Output<TFloat32> minActivations() {
   public Output<TFloat32> maxActivations() {
     return maxActivations;
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedRelu6<?>> {
+    /**
+     * The features input
+     */
+    public final Operand<? extends TNumber> features;
+
+    /**
+     * The float value that the lowest quantized value represents.
+     */
+    public final Operand<TFloat32> minFeatures;
+
+    /**
+     * The float value that the highest quantized value represents.
+     */
+    public final Operand<TFloat32> maxFeatures;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedRelu6<>(op), op, Arrays.asList("Tinput", "out_type"));
+      int inputIndex = 0;
+      features = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minFeatures = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFeatures = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java
index 199e22b049c..0e479563b8b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -61,11 +65,11 @@ private QuantizedReluX(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedReluX operation.
    *
    * @param scope current scope
-   * @param features the features value
-   * @param maxValue the maxValue value
+   * @param features The features value
+   * @param maxValue The maxValue value
    * @param minFeatures The float value that the lowest quantized value represents.
    * @param maxFeatures The float value that the highest quantized value represents.
-   * @param outType the value of the outType property
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code QuantizedReluX} output and operands
    * @return a new instance of QuantizedReluX
    */
@@ -110,4 +114,47 @@ public Output<TFloat32> minActivations() {
   public Output<TFloat32> maxActivations() {
     return maxActivations;
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedReluX<?>> {
+    /**
+     * The features input
+     */
+    public final Operand<? extends TNumber> features;
+
+    /**
+     * The maxValue input
+     */
+    public final Operand<TFloat32> maxValue;
+
+    /**
+     * The float value that the lowest quantized value represents.
+     */
+    public final Operand<TFloat32> minFeatures;
+
+    /**
+     * The float value that the highest quantized value represents.
+     */
+    public final Operand<TFloat32> maxFeatures;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedReluX<>(op), op, Arrays.asList("Tinput", "out_type"));
+      int inputIndex = 0;
+      features = (Operand<? extends TNumber>) op.input(inputIndex++);
+      maxValue = (Operand<TFloat32>) op.input(inputIndex++);
+      minFeatures = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFeatures = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java
index cbf2f6c2278..cb2a3ac068e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -63,7 +67,7 @@ private Relu(Operation operation) {
    * Factory method to create a class wrapping a new Relu operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Relu} output and operands
    * @return a new instance of Relu
    */
@@ -89,4 +93,23 @@ public Output<T> activations() {
   public Output<T> asOutput() {
     return activations;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Relu<T>> {
+    /**
+     * The features input
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Relu<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java
index 0e31636c3cf..6a076656bd5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Relu6(Operation operation) {
    * Factory method to create a class wrapping a new Relu6 operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Relu6} output and operands
    * @return a new instance of Relu6
    */
@@ -79,4 +83,23 @@ public Output<T> activations() {
   public Output<T> asOutput() {
     return activations;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Relu6<T>> {
+    /**
+     * The features input
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Relu6<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java
index 5ec8c04501c..a661ce63ea0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -80,4 +84,30 @@ public Output<T> backprops() {
   public Output<T> asOutput() {
     return backprops;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Relu6Grad<T>> {
+    /**
+     * The backpropagated gradients to the corresponding Relu6 operation.
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The features passed as input to the corresponding Relu6 operation, or
+     * its output; using either one produces the same result.
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Relu6Grad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java
index 3e0eacee22d..88ac8d1f067 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -79,4 +83,30 @@ public Output<T> backprops() {
   public Output<T> asOutput() {
     return backprops;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<ReluGrad<T>> {
+    /**
+     * The backpropagated gradients to the corresponding Relu operation.
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The features passed as input to the corresponding Relu operation, OR
+     * the outputs of that operation (both work equivalently).
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ReluGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java
index d05637ab93c..f4bde617501 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -58,7 +62,7 @@ private Selu(Operation operation) {
    * Factory method to create a class wrapping a new Selu operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Selu} output and operands
    * @return a new instance of Selu
    */
@@ -84,4 +88,23 @@ public Output<T> activations() {
   public Output<T> asOutput() {
     return activations;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Selu<T>> {
+    /**
+     * The features input
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Selu<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java
index 5516e9bd369..4beb213c767 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -79,4 +83,29 @@ public Output<T> backprops() {
   public Output<T> asOutput() {
     return backprops;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SeluGrad<T>> {
+    /**
+     * The backpropagated gradients to the corresponding Selu operation.
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The outputs of the corresponding Selu operation.
+     */
+    public final Operand<T> outputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SeluGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      outputs = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java
index 306bcc22794..5bd51a5ac65 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -83,4 +87,23 @@ public Output<T> softmax() {
   public Output<T> asOutput() {
     return softmax;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Softmax<T>> {
+    /**
+     * 2-D with shape {@code [batch_size, num_classes]}.
+     */
+    public final Operand<T> logits;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Softmax<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      logits = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
index d703a649978..3d3cb903166 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -92,4 +96,31 @@ public Output<T> loss() {
   public Output<T> backprop() {
     return backprop;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SoftmaxCrossEntropyWithLogits<T>> {
+    /**
+     * batch_size x num_classes matrix
+     */
+    public final Operand<T> features;
+
+    /**
+     * batch_size x num_classes matrix
+     * The caller must ensure that each batch of labels represents a valid
+     * probability distribution.
+     */
+    public final Operand<T> labels;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SoftmaxCrossEntropyWithLogits<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      labels = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java
index 67fa8f4211a..9d17f898281 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -53,7 +57,7 @@ private Softsign(Operation operation) {
    * Factory method to create a class wrapping a new Softsign operation.
    *
    * @param scope current scope
-   * @param features the features value
+   * @param features The features value
    * @param <T> data type for {@code Softsign} output and operands
    * @return a new instance of Softsign
    */
@@ -79,4 +83,23 @@ public Output<T> activations() {
   public Output<T> asOutput() {
     return activations;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Softsign<T>> {
+    /**
+     * The features input
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Softsign<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java
index c73893bd640..ba0d7d3c380 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -78,4 +82,29 @@ public Output<T> backprops() {
   public Output<T> asOutput() {
     return backprops;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SoftsignGrad<T>> {
+    /**
+     * The backpropagated gradients to the corresponding softsign operation.
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The features passed as input to the corresponding softsign operation.
+     */
+    public final Operand<T> features;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SoftsignGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      features = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java
index 66ac883c8a6..31b8b5d34ab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -129,7 +133,7 @@ private SpaceToBatch(Operation operation) {
    *   height_pad = pad_top + height + pad_bottom
    *   width_pad = pad_left + width + pad_right
    * </pre>
-   * @param blockSize the value of the blockSize property
+   * @param blockSize The value of the blockSize attribute
    * @param <T> data type for {@code SpaceToBatch} output and operands
    * @return a new instance of SpaceToBatch
    */
@@ -158,4 +162,50 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SpaceToBatch<T>> {
+    /**
+     * 4-D with shape {@code [batch, height, width, depth]}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 2-D tensor of non-negative integers with shape {@code [2, 2]}. It specifies
+     * the padding of the input with zeros across the spatial dimensions as follows:
+     * <pre>
+     *   paddings = [[pad_top, pad_bottom], [pad_left, pad_right]]
+     * </pre>
+     * <p>The effective spatial dimensions of the zero-padded input tensor will be:
+     * <pre>
+     *   height_pad = pad_top + height + pad_bottom
+     *   width_pad = pad_left + width + pad_right
+     * </pre>
+     */
+    public final Operand<? extends TNumber> paddings;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tpaddings attribute
+     */
+    public final DataType Tpaddings;
+
+    /**
+     * The blockSize attribute
+     */
+    public final long blockSize;
+
+    public Inputs(GraphOperation op) {
+      super(new SpaceToBatch<>(op), op, Arrays.asList("T", "Tpaddings", "block_size"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      paddings = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tpaddings = op.attributes().getAttrType("Tpaddings");
+      blockSize = op.attributes().getAttrInt("block_size");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java
index 2c15ddacb58..6fe32cec477 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -121,7 +125,7 @@ private SpaceToDepth(Operation operation) {
    * Factory method to create a class wrapping a new SpaceToDepth operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param blockSize The size of the spatial block.
    * @param options carries optional attribute values
    * @param <T> data type for {@code SpaceToDepth} output and operands
@@ -189,4 +193,35 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SpaceToDepth<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The size of the spatial block.
+     */
+    public final long blockSize;
+
+    /**
+     * The dataFormat attribute
+     */
+    public final String dataFormat;
+
+    public Inputs(GraphOperation op) {
+      super(new SpaceToDepth<>(op), op, Arrays.asList("T", "block_size", "data_format"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      blockSize = op.attributes().getAttrInt("block_size");
+      dataFormat = op.attributes().getAttrString("data_format");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
index 399274a39d7..5935d7eeb8f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -95,4 +99,36 @@ public Output<T> loss() {
   public Output<T> backprop() {
     return backprop;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSoftmaxCrossEntropyWithLogits<T>> {
+    /**
+     * batch_size x num_classes matrix
+     */
+    public final Operand<T> features;
+
+    /**
+     * batch_size vector with values in [0, num_classes).
+     * This is the label for the given minibatch entry.
+     */
+    public final Operand<? extends TNumber> labels;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tlabels attribute
+     */
+    public final DataType Tlabels;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSoftmaxCrossEntropyWithLogits<>(op), op, Arrays.asList("T", "Tlabels"));
+      int inputIndex = 0;
+      features = (Operand<T>) op.input(inputIndex++);
+      labels = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tlabels = op.attributes().getAttrType("Tlabels");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java
index f7ecda41e2c..d549f556f17 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.nn;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -141,4 +145,37 @@ public Options sorted(Boolean sorted) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<TopK<T>> {
+    /**
+     * 1-D or higher with last dimension at least {@code k}.
+     */
+    public final Operand<T> input;
+
+    /**
+     * 0-D.  Number of top elements to look for along the last dimension (along each
+     * row for matrices).
+     */
+    public final Operand<TInt32> k;
+
+    /**
+     * If true the resulting `k` elements will be sorted by the values in
+     * descending order.
+     */
+    public final boolean sorted;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TopK<>(op), op, Arrays.asList("sorted", "T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      k = (Operand<TInt32>) op.input(inputIndex++);
+      sorted = op.attributes().getAttrBool("sorted");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java
index 9d4c2e4cbea..053689d7023 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -98,7 +102,7 @@ private Dequantize(Operation operation) {
    * Factory method to create a class wrapping a new Dequantize operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param minRange The minimum scalar value possibly produced for the input.
    * @param maxRange The maximum scalar value possibly produced for the input.
    * @param dtype Type of the output tensor. Currently Dequantize supports float and bfloat16.
@@ -138,7 +142,7 @@ public static <U extends TNumber> Dequantize<U> create(Scope scope,
    * Factory method to create a class wrapping a new Dequantize operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param minRange The minimum scalar value possibly produced for the input.
    * @param maxRange The maximum scalar value possibly produced for the input.
    * @param options carries optional attribute values
@@ -242,4 +246,60 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Dequantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The minimum scalar value possibly produced for the input.
+     */
+    public final Operand<TFloat32> minRange;
+
+    /**
+     * The maximum scalar value possibly produced for the input.
+     */
+    public final Operand<TFloat32> maxRange;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The mode attribute
+     */
+    public final String mode;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    /**
+     * The axis attribute
+     */
+    public final long axis;
+
+    /**
+     * Type of the output tensor. Currently Dequantize supports float and bfloat16.
+     * If 'dtype' is 'bfloat16', it only supports 'MIN_COMBINED' mode.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new Dequantize<>(op), op, Arrays.asList("T", "mode", "narrow_range", "axis", "dtype"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minRange = (Operand<TFloat32>) op.input(inputIndex++);
+      maxRange = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      mode = op.attributes().getAttrString("mode");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+      axis = op.attributes().getAttrInt("axis");
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgs.java
index aeb3f5bfbba..932f2420685 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgs.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -71,7 +74,7 @@ private FakeQuantWithMinMaxArgs(Operation operation) {
    * Factory method to create a class wrapping a new FakeQuantWithMinMaxArgs operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
+   * @param inputs The inputs value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxArgs
    */
@@ -214,4 +217,41 @@ public Options narrowRange(Boolean narrowRange) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FakeQuantWithMinMaxArgs> {
+    /**
+     * The inputs input
+     */
+    public final Operand<TFloat32> inputs;
+
+    /**
+     * The min attribute
+     */
+    public final float min;
+
+    /**
+     * The max attribute
+     */
+    public final float max;
+
+    /**
+     * The numBits attribute
+     */
+    public final long numBits;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    public Inputs(GraphOperation op) {
+      super(new FakeQuantWithMinMaxArgs(op), op, Arrays.asList("min", "max", "num_bits", "narrow_range"));
+      int inputIndex = 0;
+      inputs = (Operand<TFloat32>) op.input(inputIndex++);
+      min = op.attributes().getAttrFloat("min");
+      max = op.attributes().getAttrFloat("max");
+      numBits = op.attributes().getAttrInt("num_bits");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java
index e02dbb09041..a87262d29e5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxArgsGradient.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -197,4 +200,47 @@ public Options narrowRange(Boolean narrowRange) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FakeQuantWithMinMaxArgsGradient> {
+    /**
+     * Backpropagated gradients above the FakeQuantWithMinMaxArgs operation.
+     */
+    public final Operand<TFloat32> gradients;
+
+    /**
+     * Values passed as inputs to the FakeQuantWithMinMaxArgs operation.
+     */
+    public final Operand<TFloat32> inputs;
+
+    /**
+     * The min attribute
+     */
+    public final float min;
+
+    /**
+     * The max attribute
+     */
+    public final float max;
+
+    /**
+     * The numBits attribute
+     */
+    public final long numBits;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    public Inputs(GraphOperation op) {
+      super(new FakeQuantWithMinMaxArgsGradient(op), op, Arrays.asList("min", "max", "num_bits", "narrow_range"));
+      int inputIndex = 0;
+      gradients = (Operand<TFloat32>) op.input(inputIndex++);
+      inputs = (Operand<TFloat32>) op.input(inputIndex++);
+      min = op.attributes().getAttrFloat("min");
+      max = op.attributes().getAttrFloat("max");
+      numBits = op.attributes().getAttrInt("num_bits");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java
index 718a9acfb6a..d94a0b1442a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVars.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -74,9 +77,9 @@ private FakeQuantWithMinMaxVars(Operation operation) {
    * Factory method to create a class wrapping a new FakeQuantWithMinMaxVars operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
-   * @param min the min value
-   * @param max the max value
+   * @param inputs The inputs value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVars
    */
@@ -169,4 +172,41 @@ public Options narrowRange(Boolean narrowRange) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FakeQuantWithMinMaxVars> {
+    /**
+     * The inputs input
+     */
+    public final Operand<TFloat32> inputs;
+
+    /**
+     * The min input
+     */
+    public final Operand<TFloat32> min;
+
+    /**
+     * The max input
+     */
+    public final Operand<TFloat32> max;
+
+    /**
+     * The numBits attribute
+     */
+    public final long numBits;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    public Inputs(GraphOperation op) {
+      super(new FakeQuantWithMinMaxVars(op), op, Arrays.asList("num_bits", "narrow_range"));
+      int inputIndex = 0;
+      inputs = (Operand<TFloat32>) op.input(inputIndex++);
+      min = (Operand<TFloat32>) op.input(inputIndex++);
+      max = (Operand<TFloat32>) op.input(inputIndex++);
+      numBits = op.attributes().getAttrInt("num_bits");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsGradient.java
index c7f5e1eff1c..38090987274 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsGradient.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -60,8 +63,8 @@ private FakeQuantWithMinMaxVarsGradient(Operation operation) {
    * @param gradients Backpropagated gradients above the FakeQuantWithMinMaxVars operation.
    * @param inputs Values passed as inputs to the FakeQuantWithMinMaxVars operation.
    * min, max: Quantization interval, scalar floats.
-   * @param min the min value
-   * @param max the max value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVarsGradient
    */
@@ -171,4 +174,48 @@ public Options narrowRange(Boolean narrowRange) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FakeQuantWithMinMaxVarsGradient> {
+    /**
+     * Backpropagated gradients above the FakeQuantWithMinMaxVars operation.
+     */
+    public final Operand<TFloat32> gradients;
+
+    /**
+     * Values passed as inputs to the FakeQuantWithMinMaxVars operation.
+     * min, max: Quantization interval, scalar floats.
+     */
+    public final Operand<TFloat32> inputs;
+
+    /**
+     * The min input
+     */
+    public final Operand<TFloat32> min;
+
+    /**
+     * The max input
+     */
+    public final Operand<TFloat32> max;
+
+    /**
+     * The bitwidth of the quantization; between 2 and 8, inclusive.
+     */
+    public final long numBits;
+
+    /**
+     * Whether to quantize into 2^num_bits - 1 distinct values.
+     */
+    public final boolean narrowRange;
+
+    public Inputs(GraphOperation op) {
+      super(new FakeQuantWithMinMaxVarsGradient(op), op, Arrays.asList("num_bits", "narrow_range"));
+      int inputIndex = 0;
+      gradients = (Operand<TFloat32>) op.input(inputIndex++);
+      inputs = (Operand<TFloat32>) op.input(inputIndex++);
+      min = (Operand<TFloat32>) op.input(inputIndex++);
+      max = (Operand<TFloat32>) op.input(inputIndex++);
+      numBits = op.attributes().getAttrInt("num_bits");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannel.java
index 9ebe8dc4567..8fba3a49f46 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannel.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannel.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -75,9 +78,9 @@ private FakeQuantWithMinMaxVarsPerChannel(Operation operation) {
    * Factory method to create a class wrapping a new FakeQuantWithMinMaxVarsPerChannel operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
-   * @param min the min value
-   * @param max the max value
+   * @param inputs The inputs value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVarsPerChannel
    */
@@ -170,4 +173,41 @@ public Options narrowRange(Boolean narrowRange) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FakeQuantWithMinMaxVarsPerChannel> {
+    /**
+     * The inputs input
+     */
+    public final Operand<TFloat32> inputs;
+
+    /**
+     * The min input
+     */
+    public final Operand<TFloat32> min;
+
+    /**
+     * The max input
+     */
+    public final Operand<TFloat32> max;
+
+    /**
+     * The numBits attribute
+     */
+    public final long numBits;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    public Inputs(GraphOperation op) {
+      super(new FakeQuantWithMinMaxVarsPerChannel(op), op, Arrays.asList("num_bits", "narrow_range"));
+      int inputIndex = 0;
+      inputs = (Operand<TFloat32>) op.input(inputIndex++);
+      min = (Operand<TFloat32>) op.input(inputIndex++);
+      max = (Operand<TFloat32>) op.input(inputIndex++);
+      numBits = op.attributes().getAttrInt("num_bits");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannelGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannelGradient.java
index 66b9e432de6..5ee0cbf2450 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannelGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/FakeQuantWithMinMaxVarsPerChannelGradient.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -62,8 +65,8 @@ private FakeQuantWithMinMaxVarsPerChannelGradient(Operation operation) {
    * @param inputs Values passed as inputs to the FakeQuantWithMinMaxVars operation, shape
    * same as {@code gradients}.
    * min, max: Quantization interval, floats of shape {@code [d]}.
-   * @param min the min value
-   * @param max the max value
+   * @param min The min value
+   * @param max The max value
    * @param options carries optional attribute values
    * @return a new instance of FakeQuantWithMinMaxVarsPerChannelGradient
    */
@@ -175,4 +178,50 @@ public Options narrowRange(Boolean narrowRange) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<FakeQuantWithMinMaxVarsPerChannelGradient> {
+    /**
+     * Backpropagated gradients above the FakeQuantWithMinMaxVars operation,
+     * shape one of: {@code [d]}, {@code [b, d]},  {@code [b, h, w, d]}.
+     */
+    public final Operand<TFloat32> gradients;
+
+    /**
+     * Values passed as inputs to the FakeQuantWithMinMaxVars operation, shape
+     * same as {@code gradients}.
+     * min, max: Quantization interval, floats of shape {@code [d]}.
+     */
+    public final Operand<TFloat32> inputs;
+
+    /**
+     * The min input
+     */
+    public final Operand<TFloat32> min;
+
+    /**
+     * The max input
+     */
+    public final Operand<TFloat32> max;
+
+    /**
+     * The bitwidth of the quantization; between 2 and 16, inclusive.
+     */
+    public final long numBits;
+
+    /**
+     * Whether to quantize into 2^num_bits - 1 distinct values.
+     */
+    public final boolean narrowRange;
+
+    public Inputs(GraphOperation op) {
+      super(new FakeQuantWithMinMaxVarsPerChannelGradient(op), op, Arrays.asList("num_bits", "narrow_range"));
+      int inputIndex = 0;
+      gradients = (Operand<TFloat32>) op.input(inputIndex++);
+      inputs = (Operand<TFloat32>) op.input(inputIndex++);
+      min = (Operand<TFloat32>) op.input(inputIndex++);
+      max = (Operand<TFloat32>) op.input(inputIndex++);
+      numBits = op.attributes().getAttrInt("num_bits");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java
index 7710a448c9a..d3223aa4e9d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -152,7 +156,7 @@ private Quantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizeV2 operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param minRange The minimum value of the quantization range. This value may be adjusted by the
    * op depending on other parameters. The adjusted value is written to {@code output_min}.
    * If the {@code axis} attribute is specified, this must be a 1-D tensor whose size
@@ -161,7 +165,7 @@ private Quantize(Operation operation) {
    * op depending on other parameters. The adjusted value is written to {@code output_max}.
    * If the {@code axis} attribute is specified, this must be a 1-D tensor whose size
    * matches the {@code axis} dimension of the input and output tensors.
-   * @param T the value of the T property
+   * @param T The value of the T attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeV2} output and operands
    * @return a new instance of Quantize
@@ -353,4 +357,71 @@ public Options ensureMinimumRange(Float ensureMinimumRange) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Quantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<TFloat32> input;
+
+    /**
+     * The minimum value of the quantization range. This value may be adjusted by the
+     * op depending on other parameters. The adjusted value is written to {@code output_min}.
+     * If the {@code axis} attribute is specified, this must be a 1-D tensor whose size
+     * matches the {@code axis} dimension of the input and output tensors.
+     */
+    public final Operand<TFloat32> minRange;
+
+    /**
+     * The maximum value of the quantization range. This value may be adjusted by the
+     * op depending on other parameters. The adjusted value is written to {@code output_max}.
+     * If the {@code axis} attribute is specified, this must be a 1-D tensor whose size
+     * matches the {@code axis} dimension of the input and output tensors.
+     */
+    public final Operand<TFloat32> maxRange;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The mode attribute
+     */
+    public final String mode;
+
+    /**
+     * The roundMode attribute
+     */
+    public final String roundMode;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    /**
+     * The axis attribute
+     */
+    public final long axis;
+
+    /**
+     * The ensureMinimumRange attribute
+     */
+    public final float ensureMinimumRange;
+
+    public Inputs(GraphOperation op) {
+      super(new Quantize<>(op), op, Arrays.asList("T", "mode", "round_mode", "narrow_range", "axis", "ensure_minimum_range"));
+      int inputIndex = 0;
+      input = (Operand<TFloat32>) op.input(inputIndex++);
+      minRange = (Operand<TFloat32>) op.input(inputIndex++);
+      maxRange = (Operand<TFloat32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      mode = op.attributes().getAttrString("mode");
+      roundMode = op.attributes().getAttrString("round_mode");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+      axis = op.attributes().getAttrInt("axis");
+      ensureMinimumRange = op.attributes().getAttrFloat("ensure_minimum_range");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java
index e5bd785c488..4209187b9ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -56,10 +60,10 @@ private QuantizeAndDequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizeAndDequantizeV3 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param inputMin the inputMin value
-   * @param inputMax the inputMax value
-   * @param numBits the numBits value
+   * @param input The input value
+   * @param inputMin The inputMin value
+   * @param inputMax The inputMax value
+   * @param numBits The numBits value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeAndDequantizeV3} output and operands
    * @return a new instance of QuantizeAndDequantize
@@ -206,4 +210,65 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizeAndDequantize<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The inputMin input
+     */
+    public final Operand<T> inputMin;
+
+    /**
+     * The inputMax input
+     */
+    public final Operand<T> inputMax;
+
+    /**
+     * The numBits input
+     */
+    public final Operand<TInt32> numBits;
+
+    /**
+     * The signedInput attribute
+     */
+    public final boolean signedInput;
+
+    /**
+     * The rangeGiven attribute
+     */
+    public final boolean rangeGiven;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    /**
+     * The axis attribute
+     */
+    public final long axis;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizeAndDequantize<>(op), op, Arrays.asList("signed_input", "range_given", "T", "narrow_range", "axis"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      inputMin = (Operand<T>) op.input(inputIndex++);
+      inputMax = (Operand<T>) op.input(inputIndex++);
+      numBits = (Operand<TInt32>) op.input(inputIndex++);
+      signedInput = op.attributes().getAttrBool("signed_input");
+      rangeGiven = op.attributes().getAttrBool("range_given");
+      T = op.attributes().getAttrType("T");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+      axis = op.attributes().getAttrInt("axis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java
index 475443feab6..4e2eff27b37 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -56,10 +60,10 @@ private QuantizeAndDequantizeV3(Operation operation) {
    * Factory method to create a class wrapping a new QuantizeAndDequantizeV3 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param inputMin the inputMin value
-   * @param inputMax the inputMax value
-   * @param numBits the numBits value
+   * @param input The input value
+   * @param inputMin The inputMin value
+   * @param inputMax The inputMax value
+   * @param numBits The numBits value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeAndDequantizeV3} output and operands
    * @return a new instance of QuantizeAndDequantizeV3
@@ -206,4 +210,65 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizeAndDequantizeV3<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The inputMin input
+     */
+    public final Operand<T> inputMin;
+
+    /**
+     * The inputMax input
+     */
+    public final Operand<T> inputMax;
+
+    /**
+     * The numBits input
+     */
+    public final Operand<TInt32> numBits;
+
+    /**
+     * The signedInput attribute
+     */
+    public final boolean signedInput;
+
+    /**
+     * The rangeGiven attribute
+     */
+    public final boolean rangeGiven;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The narrowRange attribute
+     */
+    public final boolean narrowRange;
+
+    /**
+     * The axis attribute
+     */
+    public final long axis;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizeAndDequantizeV3<>(op), op, Arrays.asList("signed_input", "range_given", "T", "narrow_range", "axis"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      inputMin = (Operand<T>) op.input(inputIndex++);
+      inputMax = (Operand<T>) op.input(inputIndex++);
+      numBits = (Operand<TInt32>) op.input(inputIndex++);
+      signedInput = op.attributes().getAttrBool("signed_input");
+      rangeGiven = op.attributes().getAttrBool("range_given");
+      T = op.attributes().getAttrType("T");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+      axis = op.attributes().getAttrInt("axis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java
index 61c58c8c21c..2b80e1cac70 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -281,4 +285,85 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizeAndDequantizeV4<T>> {
+    /**
+     * Tensor to quantize and then dequantize.
+     */
+    public final Operand<T> input;
+
+    /**
+     * If {@code range_given == True}, this specifies the minimum input value that needs to
+     * be represented, otherwise it is determined from the min value of the {@code input}
+     * tensor.
+     */
+    public final Operand<T> inputMin;
+
+    /**
+     * If {@code range_given == True}, this specifies the maximum input value that needs to
+     * be represented, otherwise it is determined from the max value of the {@code input}
+     * tensor.
+     */
+    public final Operand<T> inputMax;
+
+    /**
+     * Whether the quantization is signed or unsigned. (actually this parameter should
+     * have been called <b>`signed_output`</b>)
+     */
+    public final boolean signedInput;
+
+    /**
+     * The bitwidth of the quantization.
+     */
+    public final long numBits;
+
+    /**
+     * Whether the range is given or should be determined from the `input` tensor.
+     */
+    public final boolean rangeGiven;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The 'round_mode' attribute controls which rounding tie-breaking algorithm is
+     * used when rounding float values to their quantized equivalents. The following
+     * rounding modes are currently supported:
+     *
+     * *   HALF_TO_EVEN: this is the default round_mode.
+     * *   HALF_UP: round towards positive. In this mode 7.5 rounds up to 8 and -7.5
+     *     rounds up to -7.
+     */
+    public final String roundMode;
+
+    /**
+     * If True, then the absolute value of the quantized minimum value is the same as
+     * the quantized maximum value, instead of 1 greater.
+     * i.e. for 8 bit quantization, the minimum value is -127 instead of -128.
+     */
+    public final boolean narrowRange;
+
+    /**
+     * If specified, this axis is treated as a channel or slice axis, and a separate
+     * quantization range is used for each channel or slice along this axis.
+     */
+    public final long axis;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizeAndDequantizeV4<>(op), op, Arrays.asList("signed_input", "num_bits", "range_given", "T", "round_mode", "narrow_range", "axis"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      inputMin = (Operand<T>) op.input(inputIndex++);
+      inputMax = (Operand<T>) op.input(inputIndex++);
+      signedInput = op.attributes().getAttrBool("signed_input");
+      numBits = op.attributes().getAttrInt("num_bits");
+      rangeGiven = op.attributes().getAttrBool("range_given");
+      T = op.attributes().getAttrType("T");
+      roundMode = op.attributes().getAttrString("round_mode");
+      narrowRange = op.attributes().getAttrBool("narrow_range");
+      axis = op.attributes().getAttrInt("axis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java
index 80210f3fe28..7a70dd57298 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -61,10 +65,10 @@ private QuantizeAndDequantizeV4Grad(Operation operation) {
    * Factory method to create a class wrapping a new QuantizeAndDequantizeV4Grad operation.
    *
    * @param scope current scope
-   * @param gradients the gradients value
-   * @param input the input value
-   * @param inputMin the inputMin value
-   * @param inputMax the inputMax value
+   * @param gradients The gradients value
+   * @param input The input value
+   * @param inputMin The inputMin value
+   * @param inputMax The inputMax value
    * @param options carries optional attribute values
    * @param <T> data type for {@code QuantizeAndDequantizeV4Grad} output and operands
    * @return a new instance of QuantizeAndDequantizeV4Grad
@@ -147,4 +151,47 @@ public Options axis(Long axis) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<QuantizeAndDequantizeV4Grad<T>> {
+    /**
+     * The gradients input
+     */
+    public final Operand<T> gradients;
+
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The inputMin input
+     */
+    public final Operand<T> inputMin;
+
+    /**
+     * The inputMax input
+     */
+    public final Operand<T> inputMax;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The axis attribute
+     */
+    public final long axis;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizeAndDequantizeV4Grad<>(op), op, Arrays.asList("T", "axis"));
+      int inputIndex = 0;
+      gradients = (Operand<T>) op.input(inputIndex++);
+      input = (Operand<T>) op.input(inputIndex++);
+      inputMin = (Operand<T>) op.input(inputIndex++);
+      inputMax = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      axis = op.attributes().getAttrInt("axis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java
index d5e658a7f77..20302f5e4ad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -80,7 +84,7 @@ private QuantizeDownAndShrinkRange(Operation operation) {
    * Factory method to create a class wrapping a new QuantizeDownAndShrinkRange operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param inputMin The float value that the minimum quantized input value represents.
    * @param inputMax The float value that the maximum quantized input value represents.
    * @param outType The type of the output. Should be a lower bit depth than Tinput.
@@ -127,4 +131,41 @@ public Output<TFloat32> outputMin() {
   public Output<TFloat32> outputMax() {
     return outputMax;
   }
+
+  public static class Inputs extends RawOpInputs<QuantizeDownAndShrinkRange<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The float value that the minimum quantized input value represents.
+     */
+    public final Operand<TFloat32> inputMin;
+
+    /**
+     * The float value that the maximum quantized input value represents.
+     */
+    public final Operand<TFloat32> inputMax;
+
+    /**
+     * The type of the input.
+     */
+    public final DataType Tinput;
+
+    /**
+     * The type of the output. Should be a lower bit depth than Tinput.
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizeDownAndShrinkRange<>(op), op, Arrays.asList("Tinput", "out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      inputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      inputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java
index 249fd86aa6f..f95f901d0d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
@@ -113,4 +117,49 @@ public Output<TFloat32> outputMin() {
   public Output<TFloat32> outputMax() {
     return outputMax;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<QuantizedConcat<T>> {
+    /**
+     * 0-D.  The dimension along which to concatenate.  Must be in the
+     * range [0, rank(values)).
+     */
+    public final Operand<TInt32> concatDim;
+
+    /**
+     * The {@code N} Tensors to concatenate. Their ranks and types must match,
+     * and their sizes must match in all dimensions except {@code concat_dim}.
+     */
+    public final Iterable<Operand<T>> values;
+
+    /**
+     * The minimum scalar values for each of the input tensors.
+     */
+    public final Iterable<Operand<TFloat32>> inputMins;
+
+    /**
+     * The maximum scalar values for each of the input tensors.
+     */
+    public final Iterable<Operand<TFloat32>> inputMaxes;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedConcat<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      concatDim = (Operand<TInt32>) op.input(inputIndex++);
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      int inputMinsLength = op.inputListLength("input_mins");
+      inputMins = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, inputMinsLength));
+      inputIndex += inputMinsLength;
+      int inputMaxesLength = op.inputListLength("input_maxes");
+      inputMaxes = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, inputMaxesLength));
+      inputIndex += inputMaxesLength;
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java
index e807fbaa2ab..b600d7992f9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -51,16 +55,16 @@ private QuantizedMatMulWithBiasAndDequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedMatMulWithBiasAndDequantize operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param b the b value
-   * @param bias the bias value
-   * @param minA the minA value
-   * @param maxA the maxA value
-   * @param minB the minB value
-   * @param maxB the maxB value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param Toutput the value of the Toutput property
+   * @param a The a value
+   * @param b The b value
+   * @param bias The bias value
+   * @param minA The minA value
+   * @param maxA The maxA value
+   * @param minB The minB value
+   * @param maxB The maxB value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param Toutput The value of the Toutput attribute
    * @param options carries optional attribute values
    * @param <W> data type for {@code QuantizedMatMulWithBiasAndDequantize} output and operands
    * @return a new instance of QuantizedMatMulWithBiasAndDequantize
@@ -190,4 +194,107 @@ public Options inputQuantMode(String inputQuantMode) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedMatMulWithBiasAndDequantize<?>> {
+    /**
+     * The a input
+     */
+    public final Operand<? extends TNumber> a;
+
+    /**
+     * The b input
+     */
+    public final Operand<? extends TNumber> b;
+
+    /**
+     * The bias input
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The minA input
+     */
+    public final Operand<TFloat32> minA;
+
+    /**
+     * The maxA input
+     */
+    public final Operand<TFloat32> maxA;
+
+    /**
+     * The minB input
+     */
+    public final Operand<TFloat32> minB;
+
+    /**
+     * The maxB input
+     */
+    public final Operand<TFloat32> maxB;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    /**
+     * The transposeA attribute
+     */
+    public final boolean transposeA;
+
+    /**
+     * The transposeB attribute
+     */
+    public final boolean transposeB;
+
+    /**
+     * The inputQuantMode attribute
+     */
+    public final String inputQuantMode;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMatMulWithBiasAndDequantize<>(op), op, Arrays.asList("T1", "T2", "Tbias", "Toutput", "transpose_a", "transpose_b", "input_quant_mode"));
+      int inputIndex = 0;
+      a = (Operand<? extends TNumber>) op.input(inputIndex++);
+      b = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minA = (Operand<TFloat32>) op.input(inputIndex++);
+      maxA = (Operand<TFloat32>) op.input(inputIndex++);
+      minB = (Operand<TFloat32>) op.input(inputIndex++);
+      maxB = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Tbias = op.attributes().getAttrType("Tbias");
+      Toutput = op.attributes().getAttrType("Toutput");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      inputQuantMode = op.attributes().getAttrString("input_quant_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java
index b173c0f94fa..2e8463dad54 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -57,16 +61,16 @@ private QuantizedMatMulWithBiasAndRequantize(Operation operation) {
    * Factory method to create a class wrapping a new QuantizedMatMulWithBiasAndRequantize operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param b the b value
-   * @param bias the bias value
-   * @param minA the minA value
-   * @param maxA the maxA value
-   * @param minB the minB value
-   * @param maxB the maxB value
-   * @param minFreezedOutput the minFreezedOutput value
-   * @param maxFreezedOutput the maxFreezedOutput value
-   * @param Toutput the value of the Toutput property
+   * @param a The a value
+   * @param b The b value
+   * @param bias The bias value
+   * @param minA The minA value
+   * @param maxA The maxA value
+   * @param minB The minB value
+   * @param maxB The maxB value
+   * @param minFreezedOutput The minFreezedOutput value
+   * @param maxFreezedOutput The maxFreezedOutput value
+   * @param Toutput The value of the Toutput attribute
    * @param options carries optional attribute values
    * @param <W> data type for {@code QuantizedMatMulWithBiasAndRequantize} output and operands
    * @return a new instance of QuantizedMatMulWithBiasAndRequantize
@@ -209,4 +213,107 @@ public Options inputQuantMode(String inputQuantMode) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<QuantizedMatMulWithBiasAndRequantize<?>> {
+    /**
+     * The a input
+     */
+    public final Operand<? extends TNumber> a;
+
+    /**
+     * The b input
+     */
+    public final Operand<? extends TNumber> b;
+
+    /**
+     * The bias input
+     */
+    public final Operand<? extends TNumber> bias;
+
+    /**
+     * The minA input
+     */
+    public final Operand<TFloat32> minA;
+
+    /**
+     * The maxA input
+     */
+    public final Operand<TFloat32> maxA;
+
+    /**
+     * The minB input
+     */
+    public final Operand<TFloat32> minB;
+
+    /**
+     * The maxB input
+     */
+    public final Operand<TFloat32> maxB;
+
+    /**
+     * The minFreezedOutput input
+     */
+    public final Operand<TFloat32> minFreezedOutput;
+
+    /**
+     * The maxFreezedOutput input
+     */
+    public final Operand<TFloat32> maxFreezedOutput;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The Tbias attribute
+     */
+    public final DataType Tbias;
+
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    /**
+     * The transposeA attribute
+     */
+    public final boolean transposeA;
+
+    /**
+     * The transposeB attribute
+     */
+    public final boolean transposeB;
+
+    /**
+     * The inputQuantMode attribute
+     */
+    public final String inputQuantMode;
+
+    public Inputs(GraphOperation op) {
+      super(new QuantizedMatMulWithBiasAndRequantize<>(op), op, Arrays.asList("T1", "T2", "Tbias", "Toutput", "transpose_a", "transpose_b", "input_quant_mode"));
+      int inputIndex = 0;
+      a = (Operand<? extends TNumber>) op.input(inputIndex++);
+      b = (Operand<? extends TNumber>) op.input(inputIndex++);
+      bias = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minA = (Operand<TFloat32>) op.input(inputIndex++);
+      maxA = (Operand<TFloat32>) op.input(inputIndex++);
+      minB = (Operand<TFloat32>) op.input(inputIndex++);
+      maxB = (Operand<TFloat32>) op.input(inputIndex++);
+      minFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      maxFreezedOutput = (Operand<TFloat32>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      Tbias = op.attributes().getAttrType("Tbias");
+      Toutput = op.attributes().getAttrType("Toutput");
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      inputQuantMode = op.attributes().getAttrString("input_quant_mode");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/RequantizationRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/RequantizationRange.java
index 17dddee3427..ad1515a3e56 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/RequantizationRange.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/RequantizationRange.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -59,7 +63,7 @@ private RequantizationRange(Operation operation) {
    * Factory method to create a class wrapping a new RequantizationRange operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param inputMin The float value that the minimum quantized input value represents.
    * @param inputMax The float value that the maximum quantized input value represents.
    * @return a new instance of RequantizationRange
@@ -93,4 +97,35 @@ public Output<TFloat32> outputMin() {
   public Output<TFloat32> outputMax() {
     return outputMax;
   }
+
+  public static class Inputs extends RawOpInputs<RequantizationRange> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The float value that the minimum quantized input value represents.
+     */
+    public final Operand<TFloat32> inputMin;
+
+    /**
+     * The float value that the maximum quantized input value represents.
+     */
+    public final Operand<TFloat32> inputMax;
+
+    /**
+     * The type of the input.
+     */
+    public final DataType Tinput;
+
+    public Inputs(GraphOperation op) {
+      super(new RequantizationRange(op), op, Arrays.asList("Tinput"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      inputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      inputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java
index 26c3c26e422..0790db45399 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.quantization;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -67,7 +71,7 @@ private Requantize(Operation operation) {
    * Factory method to create a class wrapping a new Requantize operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param inputMin The float value that the minimum quantized input value represents.
    * @param inputMax The float value that the maximum quantized input value represents.
    * @param requestedOutputMin The float value that the minimum quantized output value represents.
@@ -119,4 +123,53 @@ public Output<TFloat32> outputMin() {
   public Output<TFloat32> outputMax() {
     return outputMax;
   }
+
+  public static class Inputs extends RawOpInputs<Requantize<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The float value that the minimum quantized input value represents.
+     */
+    public final Operand<TFloat32> inputMin;
+
+    /**
+     * The float value that the maximum quantized input value represents.
+     */
+    public final Operand<TFloat32> inputMax;
+
+    /**
+     * The float value that the minimum quantized output value represents.
+     */
+    public final Operand<TFloat32> requestedOutputMin;
+
+    /**
+     * The float value that the maximum quantized output value represents.
+     */
+    public final Operand<TFloat32> requestedOutputMax;
+
+    /**
+     * The type of the input.
+     */
+    public final DataType Tinput;
+
+    /**
+     * The type of the output. Should be a lower bit depth than Tinput.
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new Requantize<>(op), op, Arrays.asList("Tinput", "out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      inputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      inputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      requestedOutputMin = (Operand<TFloat32>) op.input(inputIndex++);
+      requestedOutputMax = (Operand<TFloat32>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java
index 833005da978..0de4dea307e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -137,4 +141,55 @@ public Options binaryOutput(Boolean binaryOutput) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<RaggedBincount<U>> {
+    /**
+     * 1D int64 {@code Tensor}.
+     */
+    public final Operand<TInt64> splits;
+
+    /**
+     * 2D int {@code Tensor}.
+     */
+    public final Operand<T> values;
+
+    /**
+     * non-negative int scalar {@code Tensor}.
+     */
+    public final Operand<T> sizeOutput;
+
+    /**
+     * is an int32, int64, float32, or float64 {@code Tensor} with the same
+     * shape as {@code input}, or a length-0 {@code Tensor}, in which case it acts as all weights
+     * equal to 1.
+     */
+    public final Operand<U> weights;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * bool; Whether the kernel should count the appearance or number of occurrences.
+     */
+    public final boolean binaryOutput;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedBincount<>(op), op, Arrays.asList("Tidx", "T", "binary_output"));
+      int inputIndex = 0;
+      splits = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<T>) op.input(inputIndex++);
+      sizeOutput = (Operand<T>) op.input(inputIndex++);
+      weights = (Operand<U>) op.input(inputIndex++);
+      Tidx = op.attributes().getAttrType("Tidx");
+      T = op.attributes().getAttrType("T");
+      binaryOutput = op.attributes().getAttrBool("binary_output");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java
index 9849d5192ff..6eff8ab6395 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -176,4 +180,60 @@ public Options maxlength(Long maxlength) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<RaggedCountSparseOutput<U>> {
+    /**
+     * Tensor containing the row splits of the ragged tensor to count.
+     */
+    public final Operand<TInt64> splits;
+
+    /**
+     * Tensor containing values of the sparse tensor to count.
+     */
+    public final Operand<? extends TNumber> values;
+
+    /**
+     * A Tensor of the same shape as indices containing per-index weight values.
+     * May also be the empty tensor if no weights are used.
+     */
+    public final Operand<U> weights;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Minimum value to count. Can be set to -1 for no minimum.
+     */
+    public final long minlength;
+
+    /**
+     * Maximum value to count. Can be set to -1 for no maximum.
+     */
+    public final long maxlength;
+
+    /**
+     * Whether to output the number of occurrences of each value or 1.
+     */
+    public final boolean binaryOutput;
+
+    /**
+     * Dtype of the output values tensor.
+     */
+    public final DataType outputType;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedCountSparseOutput<>(op), op, Arrays.asList("T", "minlength", "maxlength", "binary_output", "output_type"));
+      int inputIndex = 0;
+      splits = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<? extends TNumber>) op.input(inputIndex++);
+      weights = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      minlength = op.attributes().getAttrInt("minlength");
+      maxlength = op.attributes().getAttrInt("maxlength");
+      binaryOutput = op.attributes().getAttrBool("binary_output");
+      outputType = op.attributes().getAttrType("output_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java
index 75cde85a9f8..9336beb882a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -68,11 +72,11 @@ private RaggedCross(Operation operation) {
    * this string specifies the type of the {@code i}th input, and is one of: 'R' (ragged),
    * 'D' (dense), or 'S' (sparse).  This attr is used to ensure that the crossed
    * values are combined in the order of the inputs from the call to tf.ragged.cross.
-   * @param hashedOutput the value of the hashedOutput property
-   * @param numBuckets the value of the numBuckets property
-   * @param hashKey the value of the hashKey property
-   * @param outValuesType the value of the outValuesType property
-   * @param outRowSplitsType the value of the outRowSplitsType property
+   * @param hashedOutput The value of the hashedOutput attribute
+   * @param numBuckets The value of the numBuckets attribute
+   * @param hashKey The value of the hashKey attribute
+   * @param outValuesType The value of the outValuesType attribute
+   * @param outRowSplitsType The value of the outRowSplitsType attribute
    * @param <T> data type for {@code RaggedCross} output and operands
    * @param <U> data type for {@code RaggedCross} output and operands
    * @return a new instance of RaggedCross
@@ -119,4 +123,122 @@ public Output<T> outputValues() {
   public Output<U> outputRowSplits() {
     return outputRowSplits;
   }
+
+  public static class Inputs extends RawOpInputs<RaggedCross<?, ?>> {
+    /**
+     * The values tensor for each RaggedTensor input.
+     */
+    public final Iterable<Operand<?>> raggedValues;
+
+    /**
+     * The row_splits tensor for each RaggedTensor input.
+     */
+    public final Iterable<Operand<?>> raggedRowSplits;
+
+    /**
+     * The indices tensor for each SparseTensor input.
+     */
+    public final Iterable<Operand<TInt64>> sparseIndices;
+
+    /**
+     * The values tensor for each SparseTensor input.
+     */
+    public final Iterable<Operand<?>> sparseValues;
+
+    /**
+     * The dense_shape tensor for each SparseTensor input.
+     */
+    public final Iterable<Operand<TInt64>> sparseShape;
+
+    /**
+     * The tf.Tensor inputs.
+     */
+    public final Iterable<Operand<?>> denseInputs;
+
+    /**
+     * String specifying the tensor type for each input.  The `i`th character in
+     * this string specifies the type of the `i`th input, and is one of: 'R' (ragged),
+     * 'D' (dense), or 'S' (sparse).  This attr is used to ensure that the crossed
+     * values are combined in the order of the inputs from the call to tf.ragged.cross.
+     */
+    public final String inputOrder;
+
+    /**
+     * The hashedOutput attribute
+     */
+    public final boolean hashedOutput;
+
+    /**
+     * The numBuckets attribute
+     */
+    public final long numBuckets;
+
+    /**
+     * The hashKey attribute
+     */
+    public final long hashKey;
+
+    /**
+     * The raggedValuesTypes attribute
+     */
+    public final DataType[] raggedValuesTypes;
+
+    /**
+     * The raggedSplitsTypes attribute
+     */
+    public final DataType[] raggedSplitsTypes;
+
+    /**
+     * The sparseValuesTypes attribute
+     */
+    public final DataType[] sparseValuesTypes;
+
+    /**
+     * The denseTypes attribute
+     */
+    public final DataType[] denseTypes;
+
+    /**
+     * The outValuesType attribute
+     */
+    public final DataType outValuesType;
+
+    /**
+     * The outRowSplitsType attribute
+     */
+    public final DataType outRowSplitsType;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedCross<>(op), op, Arrays.asList("input_order", "hashed_output", "num_buckets", "hash_key", "ragged_values_types", "ragged_splits_types", "sparse_values_types", "dense_types", "out_values_type", "out_row_splits_type"));
+      int inputIndex = 0;
+      int raggedValuesLength = op.inputListLength("ragged_values");
+      raggedValues = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, raggedValuesLength));
+      inputIndex += raggedValuesLength;
+      int raggedRowSplitsLength = op.inputListLength("ragged_row_splits");
+      raggedRowSplits = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, raggedRowSplitsLength));
+      inputIndex += raggedRowSplitsLength;
+      int sparseIndicesLength = op.inputListLength("sparse_indices");
+      sparseIndices = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, sparseIndicesLength));
+      inputIndex += sparseIndicesLength;
+      int sparseValuesLength = op.inputListLength("sparse_values");
+      sparseValues = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, sparseValuesLength));
+      inputIndex += sparseValuesLength;
+      int sparseShapeLength = op.inputListLength("sparse_shape");
+      sparseShape = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, sparseShapeLength));
+      inputIndex += sparseShapeLength;
+      int denseInputsLength = op.inputListLength("dense_inputs");
+      denseInputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, denseInputsLength));
+      inputIndex += denseInputsLength;
+      inputOrder = op.attributes().getAttrString("input_order");
+      hashedOutput = op.attributes().getAttrBool("hashed_output");
+      numBuckets = op.attributes().getAttrInt("num_buckets");
+      hashKey = op.attributes().getAttrInt("hash_key");
+      raggedValuesTypes = op.attributes().getAttrTypeList("ragged_values_types");
+      raggedSplitsTypes = op.attributes().getAttrTypeList("ragged_splits_types");
+      sparseValuesTypes = op.attributes().getAttrTypeList("sparse_values_types");
+      denseTypes = op.attributes().getAttrTypeList("dense_types");
+      outValuesType = op.attributes().getAttrType("out_values_type");
+      outRowSplitsType = op.attributes().getAttrType("out_row_splits_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java
index 29020d73c27..05747069d47 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -125,4 +128,53 @@ public List<Output<T>> outputNestedSplits() {
   public Output<U> outputDenseValues() {
     return outputDenseValues;
   }
+
+  public static class Inputs<T extends TNumber, U extends TType> extends RawOpInputs<RaggedGather<T, U>> {
+    /**
+     * The {@code nested_row_splits} tensors that define the row-partitioning for the
+     * {@code params} RaggedTensor input.
+     */
+    public final Iterable<Operand<T>> paramsNestedSplits;
+
+    /**
+     * The {@code flat_values} for the {@code params} RaggedTensor. There was a terminology change
+     * at the python level from dense_values to flat_values, so dense_values is the
+     * deprecated name.
+     */
+    public final Operand<U> paramsDenseValues;
+
+    /**
+     * Indices in the outermost dimension of {@code params} of the values that should be
+     * gathered.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The Tvalues attribute
+     */
+    public final DataType Tvalues;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedGather<>(op), op, Arrays.asList("Tvalues", "Tindices", "Tsplits"));
+      int inputIndex = 0;
+      int paramsNestedSplitsLength = op.inputListLength("params_nested_splits");
+      paramsNestedSplits = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, paramsNestedSplitsLength));
+      inputIndex += paramsNestedSplitsLength;
+      paramsDenseValues = (Operand<U>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Tvalues = op.attributes().getAttrType("Tvalues");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java
index ae472c28100..98dcc92980a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -72,7 +76,7 @@ private RaggedRange(Operation operation) {
    * @param starts The starts of each range.
    * @param limits The limits of each range.
    * @param deltas The deltas of each range.
-   * @param Tsplits the value of the Tsplits property
+   * @param Tsplits The value of the Tsplits attribute
    * @param <U> data type for {@code RaggedRange} output and operands
    * @param <T> data type for {@code RaggedRange} output and operands
    * @return a new instance of RaggedRange
@@ -125,4 +129,41 @@ public Output<U> rtNestedSplits() {
   public Output<T> rtDenseValues() {
     return rtDenseValues;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RaggedRange<?, T>> {
+    /**
+     * The starts of each range.
+     */
+    public final Operand<T> starts;
+
+    /**
+     * The limits of each range.
+     */
+    public final Operand<T> limits;
+
+    /**
+     * The deltas of each range.
+     */
+    public final Operand<T> deltas;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedRange<>(op), op, Arrays.asList("T", "Tsplits"));
+      int inputIndex = 0;
+      starts = (Operand<T>) op.input(inputIndex++);
+      limits = (Operand<T>) op.input(inputIndex++);
+      deltas = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java
index 22dd0d2803f..e5d5e2c0d79 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -78,8 +81,8 @@ private RaggedTensorFromVariant(Operation operation) {
    * -1, this is inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}
    * @param outputRaggedRank The expected ragged rank of the output {@code RaggedTensor}. The following must hold:
    * {@code output_ragged_rank = rank(encoded_ragged) + input_ragged_rank}.
-   * @param Tvalues the value of the Tvalues property
-   * @param Tsplits the value of the Tsplits property
+   * @param Tvalues The value of the Tvalues attribute
+   * @param Tsplits The value of the Tsplits attribute
    * @param <T> data type for {@code RaggedTensorFromVariant} output and operands
    * @param <U> data type for {@code RaggedTensorFromVariant} output and operands
    * @return a new instance of RaggedTensorFromVariant
@@ -108,7 +111,7 @@ public static <T extends TNumber, U extends TType> RaggedTensorFromVariant<T, U>
    * -1, this is inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}
    * @param outputRaggedRank The expected ragged rank of the output {@code RaggedTensor}. The following must hold:
    * {@code output_ragged_rank = rank(encoded_ragged) + input_ragged_rank}.
-   * @param Tvalues the value of the Tvalues property
+   * @param Tvalues The value of the Tvalues attribute
    * @param <U> data type for {@code RaggedTensorFromVariant} output and operands
    * @return a new instance of RaggedTensorFromVariant, with default output types
    */
@@ -139,4 +142,36 @@ public List<Output<T>> outputNestedSplits() {
   public Output<U> outputDenseValues() {
     return outputDenseValues;
   }
+
+  public static class Inputs extends RawOpInputs<RaggedTensorFromVariant<?, ?>> {
+    /**
+     * A {@code variant} Tensor containing encoded {@code RaggedTensor}s.
+     */
+    public final Operand<? extends TType> encodedRagged;
+
+    /**
+     * The ragged rank of each encoded `RaggedTensor` component in the input. If set to
+     * -1, this is inferred as `output_ragged_rank` - `rank(encoded_ragged)`
+     */
+    public final long inputRaggedRank;
+
+    /**
+     * The Tvalues attribute
+     */
+    public final DataType Tvalues;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedTensorFromVariant<>(op), op, Arrays.asList("input_ragged_rank", "Tvalues", "Tsplits"));
+      int inputIndex = 0;
+      encodedRagged = (Operand<? extends TType>) op.input(inputIndex++);
+      inputRaggedRank = op.attributes().getAttrInt("input_ragged_rank");
+      Tvalues = op.attributes().getAttrType("Tvalues");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java
index 36cde5a2809..6c15ca7797c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -103,4 +107,37 @@ public Output<U> sparseValues() {
   public Output<TInt64> sparseDenseShape() {
     return sparseDenseShape;
   }
+
+  public static class Inputs<U extends TType> extends RawOpInputs<RaggedTensorToSparse<U>> {
+    /**
+     * The {@code row_splits} for the {@code RaggedTensor}.
+     */
+    public final Iterable<Operand<? extends TNumber>> rtNestedSplits;
+
+    /**
+     * The {@code flat_values} for the {@code RaggedTensor}.
+     */
+    public final Operand<U> rtDenseValues;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedTensorToSparse<>(op), op, Arrays.asList("T", "Tsplits"));
+      int inputIndex = 0;
+      int rtNestedSplitsLength = op.inputListLength("rt_nested_splits");
+      rtNestedSplits = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, rtNestedSplitsLength));
+      inputIndex += rtNestedSplitsLength;
+      rtDenseValues = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java
index abe485f6628..3ad46ad6aee 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -90,7 +94,7 @@ private RaggedTensorToTensor(Operation operation) {
    * then overwritten by values in the ragged tensor. The default value must be
    * compatible with this broadcast operation, and must have fewer dimensions than
    * the value tensor.
-   * @param rowPartitionTensors the rowPartitionTensors value
+   * @param rowPartitionTensors The rowPartitionTensors value
    * @param rowPartitionTypes The types of the row partition tensors. At present, these can be:
    * <ul>
    * <li>&quot;ROW_SPLITS&quot;: the row_splits tensor from the ragged tensor.</li>
@@ -134,4 +138,85 @@ public Output<U> result() {
   public Output<U> asOutput() {
     return result;
   }
+
+  public static class Inputs<U extends TType> extends RawOpInputs<RaggedTensorToTensor<U>> {
+    /**
+     * The desired shape of the output tensor. If left unspecified (empty),
+     * the minimal shape required to contain all the elements in the ragged tensor
+     * (the natural shape) will be used. If some dimensions are left unspecified, then
+     * the size of the natural shape is used in that dimension.
+     * <p>Note that dense dimensions cannot be modified by the shape argument. Trying to
+     * change the size of a dense dimension will cause the op to fail.
+     * Examples:
+     * natural shape: [4, 5, 6]
+     * shape: -1
+     * output shape: [4, 5, 6]
+     * <p>natural shape: [4, 5, 6]
+     * shape: [3, -1, 2]
+     * output shape: [3, 5, 2]
+     * <p>natural shape: [4, 5, 6]
+     * shape: [3, 7, 2]
+     * output shape: [3, 7, 2]
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * A 1D tensor representing the values of the ragged tensor.
+     */
+    public final Operand<U> values;
+
+    /**
+     * The default_value when the shape is larger than the ragged tensor. The
+     * default_value is broadcast until it is the shape of the output tensor, and
+     * then overwritten by values in the ragged tensor. The default value must be
+     * compatible with this broadcast operation, and must have fewer dimensions than
+     * the value tensor.
+     */
+    public final Operand<U> defaultValue;
+
+    /**
+     * The rowPartitionTensors input
+     */
+    public final Iterable<Operand<? extends TNumber>> rowPartitionTensors;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindex attribute
+     */
+    public final DataType Tindex;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    /**
+     * The types of the row partition tensors. At present, these can be:
+     * * "ROW_SPLITS": the row_splits tensor from the ragged tensor.
+     * * "VALUE_ROWIDS": the value_rowids tensor from the ragged tensor.
+     * * "FIRST_DIM_SIZE": if value_rowids is used for the first dimension, then it
+     *   is preceeded by "FIRST_DIM_SIZE".
+     * The tensors are in the order of the dimensions.
+     */
+    public final String[] rowPartitionTypes;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedTensorToTensor<>(op), op, Arrays.asList("T", "Tindex", "Tshape", "row_partition_types"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      values = (Operand<U>) op.input(inputIndex++);
+      defaultValue = (Operand<U>) op.input(inputIndex++);
+      int rowPartitionTensorsLength = op.inputListLength("row_partition_tensors");
+      rowPartitionTensors = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, rowPartitionTensorsLength));
+      inputIndex += rowPartitionTensorsLength;
+      T = op.attributes().getAttrType("T");
+      Tindex = op.attributes().getAttrType("Tindex");
+      Tshape = op.attributes().getAttrType("Tshape");
+      rowPartitionTypes = op.attributes().getAttrStringList("row_partition_types");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java
index c757c916ad2..7d02bcaf565 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -93,4 +97,44 @@ public Output<? extends TType> encodedRagged() {
   public Output<TType> asOutput() {
     return (Output<TType>) encodedRagged;
   }
+
+  public static class Inputs extends RawOpInputs<RaggedTensorToVariant> {
+    /**
+     * A list of one or more Tensors representing the splits of the input
+     * {@code RaggedTensor}.
+     */
+    public final Iterable<Operand<? extends TNumber>> rtNestedSplits;
+
+    /**
+     * A Tensor representing the values of the input {@code RaggedTensor}.
+     */
+    public final Operand<? extends TType> rtDenseValues;
+
+    /**
+     * The Tvalues attribute
+     */
+    public final DataType Tvalues;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    /**
+     * A `bool` denoting whether the input is a batched `RaggedTensor`.
+     */
+    public final boolean batchedInput;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedTensorToVariant(op), op, Arrays.asList("Tvalues", "Tsplits", "batched_input"));
+      int inputIndex = 0;
+      int rtNestedSplitsLength = op.inputListLength("rt_nested_splits");
+      rtNestedSplits = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, rtNestedSplitsLength));
+      inputIndex += rtNestedSplitsLength;
+      rtDenseValues = (Operand<? extends TType>) op.input(inputIndex++);
+      Tvalues = op.attributes().getAttrType("Tvalues");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+      batchedInput = op.attributes().getAttrBool("batched_input");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java
index 6179c50fae2..92dd3f247d5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.ragged;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -60,7 +64,7 @@ private RaggedTensorToVariantGradient(Operation operation) {
    * @param rowSplits Outermost row-splits that were used as input to the RaggedTensorToVariant op.
    * @param denseValuesShape Shape of the dense_values that was used as an input to the
    * RaggedTensorToVariant op.
-   * @param Tvalues the value of the Tvalues property
+   * @param Tvalues The value of the Tvalues attribute
    * @param <U> data type for {@code RaggedTensorToVariantGradient} output and operands
    * @return a new instance of RaggedTensorToVariantGradient
    */
@@ -91,4 +95,42 @@ public Output<U> denseValuesGrad() {
   public Output<U> asOutput() {
     return denseValuesGrad;
   }
+
+  public static class Inputs extends RawOpInputs<RaggedTensorToVariantGradient<?>> {
+    /**
+     * A {@code variant} Tensor containing encoded {@code RaggedTensor} gradients.
+     */
+    public final Operand<? extends TType> encodedRaggedGrad;
+
+    /**
+     * Outermost row-splits that were used as input to the RaggedTensorToVariant op.
+     */
+    public final Operand<? extends TNumber> rowSplits;
+
+    /**
+     * Shape of the dense_values that was used as an input to the
+     * RaggedTensorToVariant op.
+     */
+    public final Operand<TInt32> denseValuesShape;
+
+    /**
+     * The Tvalues attribute
+     */
+    public final DataType Tvalues;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new RaggedTensorToVariantGradient<>(op), op, Arrays.asList("Tvalues", "Tsplits"));
+      int inputIndex = 0;
+      encodedRaggedGrad = (Operand<? extends TType>) op.input(inputIndex++);
+      rowSplits = (Operand<? extends TNumber>) op.input(inputIndex++);
+      denseValuesShape = (Operand<TInt32>) op.input(inputIndex++);
+      Tvalues = op.attributes().getAttrType("Tvalues");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AllCandidateSampler.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AllCandidateSampler.java
index 2eac70e8b6b..c22544c3206 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AllCandidateSampler.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AllCandidateSampler.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -188,4 +191,52 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AllCandidateSampler> {
+    /**
+     * A batch_size * num_true matrix, in which each row contains the
+     * IDs of the num_true target_classes in the corresponding original label.
+     */
+    public final Operand<TInt64> trueClasses;
+
+    /**
+     * Number of true labels per context.
+     */
+    public final long numTrue;
+
+    /**
+     * Number of candidates to produce.
+     */
+    public final long numSampled;
+
+    /**
+     * If unique is true, we sample with rejection, so that all sampled
+     * candidates in a batch are unique. This requires some approximation to
+     * estimate the post-rejection sampling probabilities.
+     */
+    public final boolean unique;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new AllCandidateSampler(op), op, Arrays.asList("num_true", "num_sampled", "unique", "seed", "seed2"));
+      int inputIndex = 0;
+      trueClasses = (Operand<TInt64>) op.input(inputIndex++);
+      numTrue = op.attributes().getAttrInt("num_true");
+      numSampled = op.attributes().getAttrInt("num_sampled");
+      unique = op.attributes().getAttrBool("unique");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousRandomSeedGenerator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousRandomSeedGenerator.java
index 00f7806ee8d..44c47dd9bdf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousRandomSeedGenerator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousRandomSeedGenerator.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -52,8 +55,8 @@ private AnonymousRandomSeedGenerator(Operation operation) {
    * Factory method to create a class wrapping a new AnonymousRandomSeedGenerator operation.
    *
    * @param scope current scope
-   * @param seed the seed value
-   * @param seed2 the seed2 value
+   * @param seed The seed value
+   * @param seed2 The seed2 value
    * @return a new instance of AnonymousRandomSeedGenerator
    */
   @Endpoint(
@@ -84,4 +87,23 @@ public Output<? extends TType> handle() {
   public Output<? extends TType> deleter() {
     return deleter;
   }
+
+  public static class Inputs extends RawOpInputs<AnonymousRandomSeedGenerator> {
+    /**
+     * The seed input
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * The seed2 input
+     */
+    public final Operand<TInt64> seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new AnonymousRandomSeedGenerator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      seed2 = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousSeedGenerator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousSeedGenerator.java
index d9fa99bec9c..09f83de9c76 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousSeedGenerator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/AnonymousSeedGenerator.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -53,9 +56,9 @@ private AnonymousSeedGenerator(Operation operation) {
    * Factory method to create a class wrapping a new AnonymousSeedGenerator operation.
    *
    * @param scope current scope
-   * @param seed the seed value
-   * @param seed2 the seed2 value
-   * @param reshuffle the reshuffle value
+   * @param seed The seed value
+   * @param seed2 The seed2 value
+   * @param reshuffle The reshuffle value
    * @return a new instance of AnonymousSeedGenerator
    */
   @Endpoint(
@@ -87,4 +90,29 @@ public Output<? extends TType> handle() {
   public Output<? extends TType> deleter() {
     return deleter;
   }
+
+  public static class Inputs extends RawOpInputs<AnonymousSeedGenerator> {
+    /**
+     * The seed input
+     */
+    public final Operand<TInt64> seed;
+
+    /**
+     * The seed2 input
+     */
+    public final Operand<TInt64> seed2;
+
+    /**
+     * The reshuffle input
+     */
+    public final Operand<TBool> reshuffle;
+
+    public Inputs(GraphOperation op) {
+      super(new AnonymousSeedGenerator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      seed = (Operand<TInt64>) op.input(inputIndex++);
+      seed2 = (Operand<TInt64>) op.input(inputIndex++);
+      reshuffle = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteRandomSeedGenerator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteRandomSeedGenerator.java
index 934a3184728..6dad0b8957e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteRandomSeedGenerator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteRandomSeedGenerator.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -42,8 +45,8 @@ private DeleteRandomSeedGenerator(Operation operation) {
    * Factory method to create a class wrapping a new DeleteRandomSeedGenerator operation.
    *
    * @param scope current scope
-   * @param handle the handle value
-   * @param deleter the deleter value
+   * @param handle The handle value
+   * @param deleter The deleter value
    * @return a new instance of DeleteRandomSeedGenerator
    */
   @Endpoint(
@@ -56,4 +59,23 @@ public static DeleteRandomSeedGenerator create(Scope scope, Operand<? extends TT
     opBuilder.addInput(deleter.asOutput());
     return new DeleteRandomSeedGenerator(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DeleteRandomSeedGenerator> {
+    /**
+     * The handle input
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The deleter input
+     */
+    public final Operand<? extends TType> deleter;
+
+    public Inputs(GraphOperation op) {
+      super(new DeleteRandomSeedGenerator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      deleter = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteSeedGenerator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteSeedGenerator.java
index e3b8b8deb23..33bcd5d5714 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteSeedGenerator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DeleteSeedGenerator.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -42,8 +45,8 @@ private DeleteSeedGenerator(Operation operation) {
    * Factory method to create a class wrapping a new DeleteSeedGenerator operation.
    *
    * @param scope current scope
-   * @param handle the handle value
-   * @param deleter the deleter value
+   * @param handle The handle value
+   * @param deleter The deleter value
    * @return a new instance of DeleteSeedGenerator
    */
   @Endpoint(
@@ -56,4 +59,23 @@ public static DeleteSeedGenerator create(Scope scope, Operand<? extends TType> h
     opBuilder.addInput(deleter.asOutput());
     return new DeleteSeedGenerator(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<DeleteSeedGenerator> {
+    /**
+     * The handle input
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The deleter input
+     */
+    public final Operand<? extends TType> deleter;
+
+    public Inputs(GraphOperation op) {
+      super(new DeleteSeedGenerator(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      deleter = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DummySeedGenerator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DummySeedGenerator.java
index 29de27f6982..0eafa99d317 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DummySeedGenerator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/DummySeedGenerator.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -72,4 +75,11 @@ public Output<? extends TType> handle() {
   public Output<TType> asOutput() {
     return (Output<TType>) handle;
   }
+
+  public static class Inputs extends RawOpInputs<DummySeedGenerator> {
+    public Inputs(GraphOperation op) {
+      super(new DummySeedGenerator(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/LogUniformCandidateSampler.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/LogUniformCandidateSampler.java
index a07c10ab017..b49dd8fcd72 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/LogUniformCandidateSampler.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/LogUniformCandidateSampler.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -190,4 +193,58 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LogUniformCandidateSampler> {
+    /**
+     * A batch_size * num_true matrix, in which each row contains the
+     * IDs of the num_true target_classes in the corresponding original label.
+     */
+    public final Operand<TInt64> trueClasses;
+
+    /**
+     * Number of true labels per context.
+     */
+    public final long numTrue;
+
+    /**
+     * Number of candidates to randomly sample.
+     */
+    public final long numSampled;
+
+    /**
+     * If unique is true, we sample with rejection, so that all sampled
+     * candidates in a batch are unique. This requires some approximation to
+     * estimate the post-rejection sampling probabilities.
+     */
+    public final boolean unique;
+
+    /**
+     * The sampler will sample integers from the interval [0, range_max).
+     */
+    public final long rangeMax;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new LogUniformCandidateSampler(op), op, Arrays.asList("num_true", "num_sampled", "unique", "range_max", "seed", "seed2"));
+      int inputIndex = 0;
+      trueClasses = (Operand<TInt64>) op.input(inputIndex++);
+      numTrue = op.attributes().getAttrInt("num_true");
+      numSampled = op.attributes().getAttrInt("num_sampled");
+      unique = op.attributes().getAttrBool("unique");
+      rangeMax = op.attributes().getAttrInt("range_max");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java
index dbcae3bd724..14af4090bd8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
@@ -59,7 +63,7 @@ private Multinomial(Operation operation) {
    * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}.  Each slice {@code [i, :]}
    * represents the unnormalized log probabilities for all classes.
    * @param numSamples 0-D.  Number of independent samples to draw for each row slice.
-   * @param outputDtype the value of the outputDtype property
+   * @param outputDtype The value of the outputDtype attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code Multinomial} output and operands
    * @return a new instance of Multinomial
@@ -175,4 +179,49 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Multinomial<?>> {
+    /**
+     * 2-D Tensor with shape {@code [batch_size, num_classes]}.  Each slice {@code [i, :]}
+     * represents the unnormalized log probabilities for all classes.
+     */
+    public final Operand<? extends TNumber> logits;
+
+    /**
+     * 0-D.  Number of independent samples to draw for each row slice.
+     */
+    public final Operand<TInt32> numSamples;
+
+    /**
+     * If either seed or seed2 is set to be non-zero, the internal random number
+     * generator is seeded by the given seed.  Otherwise, a random seed is used.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outputDtype attribute
+     */
+    public final DataType outputDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new Multinomial<>(op), op, Arrays.asList("seed", "seed2", "T", "output_dtype"));
+      int inputIndex = 0;
+      logits = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSamples = (Operand<TInt32>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      T = op.attributes().getAttrType("T");
+      outputDtype = op.attributes().getAttrType("output_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java
index 85b5e80aab5..bbf03174017 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -95,4 +99,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<NonDeterministicInts<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TType> shape;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shapeDtype attribute
+     */
+    public final DataType shapeDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new NonDeterministicInts<>(op), op, Arrays.asList("dtype", "shape_dtype"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shapeDtype = op.attributes().getAttrType("shape_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java
index bd1553dfbfa..bce121c2d44 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -162,4 +166,68 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<ParameterizedTruncatedNormal<U>> {
+    /**
+     * The shape of the output tensor. Batches are indexed by the 0th dimension.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The mean parameter of each batch.
+     */
+    public final Operand<U> means;
+
+    /**
+     * The standard deviation parameter of each batch. Must be greater than 0.
+     */
+    public final Operand<U> stdevs;
+
+    /**
+     * The minimum cutoff. May be -infinity.
+     */
+    public final Operand<U> minvals;
+
+    /**
+     * The maximum cutoff. May be +infinity, and must be more than the minval
+     * for each batch.
+     */
+    public final Operand<U> maxvals;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ParameterizedTruncatedNormal<>(op), op, Arrays.asList("seed", "seed2", "dtype", "T"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      means = (Operand<U>) op.input(inputIndex++);
+      stdevs = (Operand<U>) op.input(inputIndex++);
+      minvals = (Operand<U>) op.input(inputIndex++);
+      maxvals = (Operand<U>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java
index e16823d482c..eecd013f0af 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -158,4 +162,51 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<RandomGamma<U>> {
+    /**
+     * 1-D integer tensor. Shape of independent samples to draw from each
+     * distribution described by the shape parameters given in alpha.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * A tensor in which each scalar is a &quot;shape&quot; parameter describing the
+     * associated gamma distribution.
+     */
+    public final Operand<U> alpha;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The S attribute
+     */
+    public final DataType S;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomGamma<>(op), op, Arrays.asList("seed", "seed2", "S", "T"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      alpha = (Operand<U>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      S = op.attributes().getAttrType("S");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java
index 09c333cfa32..2355dde788e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RandomGammaGrad(Operation operation) {
    * Factory method to create a class wrapping a new RandomGammaGrad operation.
    *
    * @param scope current scope
-   * @param alpha the alpha value
-   * @param sample the sample value
+   * @param alpha The alpha value
+   * @param sample The sample value
    * @param <T> data type for {@code RandomGammaGrad} output and operands
    * @return a new instance of RandomGammaGrad
    */
@@ -78,4 +82,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RandomGammaGrad<T>> {
+    /**
+     * The alpha input
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * The sample input
+     */
+    public final Operand<T> sample;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomGammaGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      alpha = (Operand<T>) op.input(inputIndex++);
+      sample = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java
index e38a0d7cff3..2e98623df39 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -67,7 +71,7 @@ private RandomPoisson(Operation operation) {
    * distribution described by the shape parameters given in rate.
    * @param rate A tensor in which each scalar is a &quot;rate&quot; parameter describing the
    * associated poisson distribution.
-   * @param dtype the value of the dtype property
+   * @param dtype The value of the dtype attribute
    * @param options carries optional attribute values
    * @param <V> data type for {@code RandomPoissonV2} output and operands
    * @return a new instance of RandomPoisson
@@ -187,4 +191,57 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RandomPoisson<?>> {
+    /**
+     * 1-D integer tensor. Shape of independent samples to draw from each
+     * distribution described by the shape parameters given in rate.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * A tensor in which each scalar is a &quot;rate&quot; parameter describing the
+     * associated poisson distribution.
+     */
+    public final Operand<? extends TNumber> rate;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The S attribute
+     */
+    public final DataType S;
+
+    /**
+     * The R attribute
+     */
+    public final DataType R;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomPoisson<>(op), op, Arrays.asList("seed", "seed2", "S", "R", "dtype"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      rate = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      S = op.attributes().getAttrType("S");
+      R = op.attributes().getAttrType("R");
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java
index 1fae5771e0a..35dad551e97 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -158,4 +162,37 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RandomShuffle<T>> {
+    /**
+     * The tensor to be shuffled.
+     */
+    public final Operand<T> value;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomShuffle<>(op), op, Arrays.asList("seed", "seed2", "T"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java
index 2d6d6bdd0a7..fee428b29b7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -153,4 +157,43 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RandomStandardNormal<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomStandardNormal<>(op), op, Arrays.asList("seed", "seed2", "dtype", "T"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java
index 87228ae9475..25ded48d9bf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -154,4 +158,43 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RandomUniform<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomUniform<>(op), op, Arrays.asList("seed", "seed2", "dtype", "T"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java
index 9b33f2c9862..417766f1e2a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -159,4 +163,55 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<RandomUniformInt<U>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 0-D.  Inclusive lower bound on the generated integers.
+     */
+    public final Operand<U> minval;
+
+    /**
+     * 0-D.  Exclusive upper bound on the generated integers.
+     */
+    public final Operand<U> maxval;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RandomUniformInt<>(op), op, Arrays.asList("seed", "seed2", "Tout", "T"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minval = (Operand<U>) op.input(inputIndex++);
+      maxval = (Operand<U>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      Tout = op.attributes().getAttrType("Tout");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RecordInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RecordInput.java
index f9539c97f95..9b4cb861f58 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RecordInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RecordInput.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -249,4 +252,55 @@ public Options compressionType(String compressionType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RecordInput> {
+    /**
+     * Glob pattern for the data files.
+     */
+    public final String filePattern;
+
+    /**
+     * Random seeds used to produce randomized records.
+     */
+    public final long fileRandomSeed;
+
+    /**
+     * Shifts the list of files after the list is randomly
+     * shuffled.
+     */
+    public final float fileShuffleShiftRatio;
+
+    /**
+     * The randomization shuffling buffer.
+     */
+    public final long fileBufferSize;
+
+    /**
+     * How many sstables are opened and concurrently iterated over.
+     */
+    public final long fileParallelism;
+
+    /**
+     * The batch size.
+     */
+    public final long batchSize;
+
+    /**
+     * The type of compression for the file. Currently ZLIB and
+     * GZIP are supported. Defaults to none.
+     */
+    public final String compressionType;
+
+    public Inputs(GraphOperation op) {
+      super(new RecordInput(op), op, Arrays.asList("file_pattern", "file_random_seed", "file_shuffle_shift_ratio", "file_buffer_size", "file_parallelism", "batch_size", "compression_type"));
+      int inputIndex = 0;
+      filePattern = op.attributes().getAttrString("file_pattern");
+      fileRandomSeed = op.attributes().getAttrInt("file_random_seed");
+      fileShuffleShiftRatio = op.attributes().getAttrFloat("file_shuffle_shift_ratio");
+      fileBufferSize = op.attributes().getAttrInt("file_buffer_size");
+      fileParallelism = op.attributes().getAttrInt("file_parallelism");
+      batchSize = op.attributes().getAttrInt("batch_size");
+      compressionType = op.attributes().getAttrString("compression_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngReadAndSkip.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngReadAndSkip.java
index 00540eed36a..d6ceea1475b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngReadAndSkip.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngReadAndSkip.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -83,4 +86,29 @@ public Output<TInt64> value() {
   public Output<TInt64> asOutput() {
     return value;
   }
+
+  public static class Inputs extends RawOpInputs<RngReadAndSkip> {
+    /**
+     * The handle of the resource variable that stores the state of the RNG.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The RNG algorithm.
+     */
+    public final Operand<TInt32> alg;
+
+    /**
+     * The amount of advancement.
+     */
+    public final Operand<? extends TType> delta;
+
+    public Inputs(GraphOperation op) {
+      super(new RngReadAndSkip(op), op, Arrays.asList());
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      alg = (Operand<TInt32>) op.input(inputIndex++);
+      delta = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngSkip.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngSkip.java
index 0e41e2bcfd8..e7eaaa81283 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngSkip.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RngSkip.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -63,4 +66,29 @@ public static RngSkip create(Scope scope, Operand<? extends TType> resource,
     opBuilder.addInput(delta.asOutput());
     return new RngSkip(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<RngSkip> {
+    /**
+     * The handle of the resource variable that stores the state of the RNG.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The RNG algorithm.
+     */
+    public final Operand<TInt64> algorithm;
+
+    /**
+     * The amount of advancement.
+     */
+    public final Operand<TInt64> delta;
+
+    public Inputs(GraphOperation op) {
+      super(new RngSkip(op), op, Arrays.asList());
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = (Operand<TInt64>) op.input(inputIndex++);
+      delta = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java
index 69eddaf8ab8..8f1467afe73 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -56,12 +60,12 @@ private StatefulRandomBinomial(Operation operation) {
    * Factory method to create a class wrapping a new StatefulRandomBinomial operation.
    *
    * @param scope current scope
-   * @param resource the resource value
-   * @param algorithm the algorithm value
-   * @param shape the shape value
-   * @param counts the counts value
-   * @param probs the probs value
-   * @param dtype the value of the dtype property
+   * @param resource The resource value
+   * @param algorithm The algorithm value
+   * @param shape The shape value
+   * @param counts The counts value
+   * @param probs The probs value
+   * @param dtype The value of the dtype attribute
    * @param <V> data type for {@code StatefulRandomBinomial} output and operands
    * @param <U> data type for {@code StatefulRandomBinomial} output and operands
    * @return a new instance of StatefulRandomBinomial
@@ -86,11 +90,11 @@ public static <V extends TNumber, U extends TNumber> StatefulRandomBinomial<V> c
    * Factory method to create a class wrapping a new StatefulRandomBinomial operation, with the default output types.
    *
    * @param scope current scope
-   * @param resource the resource value
-   * @param algorithm the algorithm value
-   * @param shape the shape value
-   * @param counts the counts value
-   * @param probs the probs value
+   * @param resource The resource value
+   * @param algorithm The algorithm value
+   * @param shape The shape value
+   * @param counts The counts value
+   * @param probs The probs value
    * @param <U> data type for {@code StatefulRandomBinomial} output and operands
    * @return a new instance of StatefulRandomBinomial, with default output types
    */
@@ -116,4 +120,59 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<StatefulRandomBinomial<?>> {
+    /**
+     * The resource input
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The algorithm input
+     */
+    public final Operand<TInt64> algorithm;
+
+    /**
+     * The shape input
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The counts input
+     */
+    public final Operand<U> counts;
+
+    /**
+     * The probs input
+     */
+    public final Operand<U> probs;
+
+    /**
+     * The S attribute
+     */
+    public final DataType S;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulRandomBinomial<>(op), op, Arrays.asList("S", "T", "dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = (Operand<TInt64>) op.input(inputIndex++);
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      counts = (Operand<U>) op.input(inputIndex++);
+      probs = (Operand<U>) op.input(inputIndex++);
+      S = op.attributes().getAttrType("S");
+      T = op.attributes().getAttrType("T");
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java
index 8655e171171..f85677851fe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -109,4 +113,41 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatefulStandardNormal<?>> {
+    /**
+     * The handle of the resource variable that stores the state of the RNG.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The RNG algorithm.
+     */
+    public final Operand<TInt64> algorithm;
+
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TType> shape;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shapeDtype attribute
+     */
+    public final DataType shapeDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulStandardNormal<>(op), op, Arrays.asList("dtype", "shape_dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = (Operand<TInt64>) op.input(inputIndex++);
+      shape = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shapeDtype = op.attributes().getAttrType("shape_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java
index 4e0742112e2..ded58540672 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -107,4 +111,41 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatefulTruncatedNormal<?>> {
+    /**
+     * The handle of the resource variable that stores the state of the RNG.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The RNG algorithm.
+     */
+    public final Operand<TInt64> algorithm;
+
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TType> shape;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shapeDtype attribute
+     */
+    public final DataType shapeDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulTruncatedNormal<>(op), op, Arrays.asList("dtype", "shape_dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = (Operand<TInt64>) op.input(inputIndex++);
+      shape = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shapeDtype = op.attributes().getAttrType("shape_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java
index 8b2e28317d1..4605231e1cb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -105,4 +109,41 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatefulUniform<?>> {
+    /**
+     * The handle of the resource variable that stores the state of the RNG.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The RNG algorithm.
+     */
+    public final Operand<TInt64> algorithm;
+
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TType> shape;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shapeDtype attribute
+     */
+    public final DataType shapeDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulUniform<>(op), op, Arrays.asList("dtype", "shape_dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = (Operand<TInt64>) op.input(inputIndex++);
+      shape = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shapeDtype = op.attributes().getAttrType("shape_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java
index 2f858cfd43e..527c1649f40 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -86,4 +90,41 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatefulUniformFullInt<?>> {
+    /**
+     * The handle of the resource variable that stores the state of the RNG.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The RNG algorithm.
+     */
+    public final Operand<TInt64> algorithm;
+
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TType> shape;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shapeDtype attribute
+     */
+    public final DataType shapeDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulUniformFullInt<>(op), op, Arrays.asList("dtype", "shape_dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = (Operand<TInt64>) op.input(inputIndex++);
+      shape = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shapeDtype = op.attributes().getAttrType("shape_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java
index ff5940afe1c..e9d475b2d72 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -92,4 +96,53 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<U extends TType> extends RawOpInputs<StatefulUniformInt<U>> {
+    /**
+     * The handle of the resource variable that stores the state of the RNG.
+     */
+    public final Operand<? extends TType> resource;
+
+    /**
+     * The RNG algorithm.
+     */
+    public final Operand<TInt64> algorithm;
+
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TType> shape;
+
+    /**
+     * Minimum value (inclusive, scalar).
+     */
+    public final Operand<U> minval;
+
+    /**
+     * Maximum value (exclusive, scalar).
+     */
+    public final Operand<U> maxval;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shapeDtype attribute
+     */
+    public final DataType shapeDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatefulUniformInt<>(op), op, Arrays.asList("dtype", "shape_dtype"));
+      int inputIndex = 0;
+      resource = (Operand<? extends TType>) op.input(inputIndex++);
+      algorithm = (Operand<TInt64>) op.input(inputIndex++);
+      shape = (Operand<? extends TType>) op.input(inputIndex++);
+      minval = (Operand<U>) op.input(inputIndex++);
+      maxval = (Operand<U>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shapeDtype = op.attributes().getAttrType("shape_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java
index 49bfb4df2e3..6d09e4dd755 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
@@ -60,7 +64,7 @@ private StatelessMultinomial(Operation operation) {
    * represents the unnormalized log probabilities for all classes.
    * @param numSamples 0-D.  Number of independent samples to draw for each row slice.
    * @param seed 2 seeds (shape [2]).
-   * @param outputDtype the value of the outputDtype property
+   * @param outputDtype The value of the outputDtype attribute
    * @param <V> data type for {@code StatelessMultinomial} output and operands
    * @return a new instance of StatelessMultinomial
    */
@@ -110,4 +114,48 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessMultinomial<?>> {
+    /**
+     * 2-D Tensor with shape {@code [batch_size, num_classes]}.  Each slice {@code [i, :]}
+     * represents the unnormalized log probabilities for all classes.
+     */
+    public final Operand<? extends TNumber> logits;
+
+    /**
+     * 0-D.  Number of independent samples to draw for each row slice.
+     */
+    public final Operand<TInt32> numSamples;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    /**
+     * The outputDtype attribute
+     */
+    public final DataType outputDtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessMultinomial<>(op), op, Arrays.asList("T", "Tseed", "output_dtype"));
+      int inputIndex = 0;
+      logits = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSamples = (Operand<TInt32>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+      outputDtype = op.attributes().getAttrType("output_dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java
index c7c31649a51..70f982ac127 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -89,4 +93,66 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs<V extends TNumber> extends RawOpInputs<StatelessParameterizedTruncatedNormal<V>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The mean parameter of each batch.
+     */
+    public final Operand<V> means;
+
+    /**
+     * The standard deviation parameter of each batch. Must be greater than 0.
+     */
+    public final Operand<V> stddevs;
+
+    /**
+     * The minimum cutoff. May be -infinity.
+     */
+    public final Operand<V> minvals;
+
+    /**
+     * The maximum cutoff. May be +infinity, and must be more than the minval
+     * for each batch.
+     */
+    public final Operand<V> maxvals;
+
+    /**
+     * The S attribute
+     */
+    public final DataType S;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessParameterizedTruncatedNormal<>(op), op, Arrays.asList("S", "Tseed", "dtype"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      means = (Operand<V>) op.input(inputIndex++);
+      stddevs = (Operand<V>) op.input(inputIndex++);
+      minvals = (Operand<V>) op.input(inputIndex++);
+      maxvals = (Operand<V>) op.input(inputIndex++);
+      S = op.attributes().getAttrType("S");
+      Tseed = op.attributes().getAttrType("Tseed");
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java
index f2fe43de2f2..555f7113290 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -114,4 +118,61 @@ public Output<W> output() {
   public Output<W> asOutput() {
     return output;
   }
+
+  public static class Inputs<V extends TNumber> extends RawOpInputs<StatelessRandomBinomial<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The counts of the binomial distribution. Must be broadcastable with {@code probs},
+     * and broadcastable with the rightmost dimensions of {@code shape}.
+     */
+    public final Operand<V> counts;
+
+    /**
+     * The probability of success for the binomial distribution. Must be broadcastable
+     * with {@code counts} and broadcastable with the rightmost dimensions of {@code shape}.
+     */
+    public final Operand<V> probs;
+
+    /**
+     * The S attribute
+     */
+    public final DataType S;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomBinomial<>(op), op, Arrays.asList("S", "Tseed", "T", "dtype"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      counts = (Operand<V>) op.input(inputIndex++);
+      probs = (Operand<V>) op.input(inputIndex++);
+      S = op.attributes().getAttrType("S");
+      Tseed = op.attributes().getAttrType("Tseed");
+      T = op.attributes().getAttrType("T");
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java
index b8301f3e4ad..b5383fa2d8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -83,4 +87,48 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs<V extends TNumber> extends RawOpInputs<StatelessRandomGamma<V>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The concentration of the gamma distribution. Shape must match the rightmost
+     * dimensions of {@code shape}.
+     */
+    public final Operand<V> alpha;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomGamma<>(op), op, Arrays.asList("dtype", "T", "Tseed"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      alpha = (Operand<V>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGetKeyCounterAlg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGetKeyCounterAlg.java
index 19876715299..762d5f95512 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGetKeyCounterAlg.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGetKeyCounterAlg.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -96,4 +100,23 @@ public Output<? extends TType> counter() {
   public Output<TInt32> alg() {
     return alg;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomGetKeyCounterAlg> {
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomGetKeyCounterAlg(op), op, Arrays.asList("Tseed"));
+      int inputIndex = 0;
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java
index 433499b7e86..dc42caec6c2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -104,4 +108,41 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomNormal<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomNormal<>(op), op, Arrays.asList("dtype", "T", "Tseed"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java
index 244ecf26652..09e30c2e27c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -110,4 +114,47 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomNormalV2<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * Key for the counter-based RNG algorithm (shape uint64[1]).
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.
+     */
+    public final Operand<? extends TType> counter;
+
+    /**
+     * The RNG algorithm (shape int32[]).
+     */
+    public final Operand<TInt32> alg;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomNormalV2<>(op), op, Arrays.asList("dtype", "Tshape"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      counter = (Operand<? extends TType>) op.input(inputIndex++);
+      alg = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java
index 0d38215c5e4..4986962addd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -87,4 +91,54 @@ public Output<W> output() {
   public Output<W> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomPoisson<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The rate of the Poisson distribution. Shape must match the rightmost dimensions
+     * of {@code shape}.
+     */
+    public final Operand<? extends TNumber> lam;
+
+    /**
+     * The Rtype attribute
+     */
+    public final DataType Rtype;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomPoisson<>(op), op, Arrays.asList("Rtype", "dtype", "T", "Tseed"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      lam = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Rtype = op.attributes().getAttrType("Rtype");
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java
index a64ec02b6f2..6ea9c4ff4b9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -105,4 +109,41 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomUniform<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomUniform<>(op), op, Arrays.asList("dtype", "T", "Tseed"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java
index 2a9fb099f03..4857e11b0b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -83,4 +87,41 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomUniformFullInt<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomUniformFullInt<>(op), op, Arrays.asList("dtype", "T", "Tseed"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java
index 1375e8b1675..d31fd80c989 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -90,4 +94,47 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomUniformFullIntV2<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * Key for the counter-based RNG algorithm (shape uint64[1]).
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.
+     */
+    public final Operand<? extends TType> counter;
+
+    /**
+     * The RNG algorithm (shape int32[]).
+     */
+    public final Operand<TInt32> alg;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomUniformFullIntV2<>(op), op, Arrays.asList("dtype", "Tshape"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      counter = (Operand<? extends TType>) op.input(inputIndex++);
+      alg = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java
index 6574e658ef3..413724622a7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -85,4 +89,53 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs<V extends TNumber> extends RawOpInputs<StatelessRandomUniformInt<V>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * Minimum value (inclusive, scalar).
+     */
+    public final Operand<V> minval;
+
+    /**
+     * Maximum value (exclusive, scalar).
+     */
+    public final Operand<V> maxval;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomUniformInt<>(op), op, Arrays.asList("dtype", "T", "Tseed"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      minval = (Operand<V>) op.input(inputIndex++);
+      maxval = (Operand<V>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java
index f46ac81e12d..133643bc187 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -91,4 +95,59 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<StatelessRandomUniformIntV2<U>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * Key for the counter-based RNG algorithm (shape uint64[1]).
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.
+     */
+    public final Operand<? extends TType> counter;
+
+    /**
+     * The RNG algorithm (shape int32[]).
+     */
+    public final Operand<TInt32> alg;
+
+    /**
+     * Minimum value (inclusive, scalar).
+     */
+    public final Operand<U> minval;
+
+    /**
+     * Maximum value (exclusive, scalar).
+     */
+    public final Operand<U> maxval;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomUniformIntV2<>(op), op, Arrays.asList("dtype", "Tshape"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      counter = (Operand<? extends TType>) op.input(inputIndex++);
+      alg = (Operand<TInt32>) op.input(inputIndex++);
+      minval = (Operand<U>) op.input(inputIndex++);
+      maxval = (Operand<U>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java
index e6a8f7b5047..e6414b181d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -111,4 +115,47 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomUniformV2<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * Key for the counter-based RNG algorithm (shape uint64[1]).
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.
+     */
+    public final Operand<? extends TType> counter;
+
+    /**
+     * The RNG algorithm (shape int32[]).
+     */
+    public final Operand<TInt32> alg;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomUniformV2<>(op), op, Arrays.asList("dtype", "Tshape"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      counter = (Operand<? extends TType>) op.input(inputIndex++);
+      alg = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java
index 5e27e6fad9f..bc78fb53e6f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -106,4 +110,41 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessTruncatedNormal<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessTruncatedNormal<>(op), op, Arrays.asList("dtype", "T", "Tseed"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java
index b66df2e0f67..da649d92ac0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -112,4 +116,47 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessTruncatedNormalV2<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * Key for the counter-based RNG algorithm (shape uint64[1]).
+     */
+    public final Operand<? extends TType> key;
+
+    /**
+     * Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.
+     */
+    public final Operand<? extends TType> counter;
+
+    /**
+     * The RNG algorithm (shape int32[]).
+     */
+    public final Operand<TInt32> alg;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessTruncatedNormalV2<>(op), op, Arrays.asList("dtype", "Tshape"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      key = (Operand<? extends TType>) op.input(inputIndex++);
+      counter = (Operand<? extends TType>) op.input(inputIndex++);
+      alg = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java
index 2413cecd2e0..2f0d60114e5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -156,4 +160,43 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TruncatedNormal<?>> {
+    /**
+     * The shape of the output tensor.
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * If either `seed` or `seed2` are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * A second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    /**
+     * The type of the output.
+     */
+    public final DataType dtype;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TruncatedNormal<>(op), op, Arrays.asList("seed", "seed2", "dtype", "T"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+      dtype = op.attributes().getAttrType("dtype");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/UniformCandidateSampler.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/UniformCandidateSampler.java
index c43eba10640..5d95242967d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/UniformCandidateSampler.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/UniformCandidateSampler.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.random;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -190,4 +193,58 @@ public Options seed2(Long seed2) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<UniformCandidateSampler> {
+    /**
+     * A batch_size * num_true matrix, in which each row contains the
+     * IDs of the num_true target_classes in the corresponding original label.
+     */
+    public final Operand<TInt64> trueClasses;
+
+    /**
+     * Number of true labels per context.
+     */
+    public final long numTrue;
+
+    /**
+     * Number of candidates to randomly sample.
+     */
+    public final long numSampled;
+
+    /**
+     * If unique is true, we sample with rejection, so that all sampled
+     * candidates in a batch are unique. This requires some approximation to
+     * estimate the post-rejection sampling probabilities.
+     */
+    public final boolean unique;
+
+    /**
+     * The sampler will sample integers from the interval [0, range_max).
+     */
+    public final long rangeMax;
+
+    /**
+     * If either seed or seed2 are set to be non-zero, the random number
+     * generator is seeded by the given seed.  Otherwise, it is seeded by a
+     * random seed.
+     */
+    public final long seed;
+
+    /**
+     * An second seed to avoid seed collision.
+     */
+    public final long seed2;
+
+    public Inputs(GraphOperation op) {
+      super(new UniformCandidateSampler(op), op, Arrays.asList("num_true", "num_sampled", "unique", "range_max", "seed", "seed2"));
+      int inputIndex = 0;
+      trueClasses = (Operand<TInt64>) op.input(inputIndex++);
+      numTrue = op.attributes().getAttrInt("num_true");
+      numSampled = op.attributes().getAttrInt("num_sampled");
+      unique = op.attributes().getAttrBool("unique");
+      rangeMax = op.attributes().getAttrInt("range_max");
+      seed = op.attributes().getAttrInt("seed");
+      seed2 = op.attributes().getAttrInt("seed2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastRecvV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastRecvV2.java
index 9dc30db94d9..167ed5dd8c8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastRecvV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastRecvV2.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -52,11 +56,11 @@ private CollectiveBcastRecvV2(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveBcastRecvV2 operation.
    *
    * @param scope current scope
-   * @param groupSize the groupSize value
-   * @param groupKey the groupKey value
-   * @param instanceKey the instanceKey value
-   * @param shape the shape value
-   * @param T the value of the T property
+   * @param groupSize The groupSize value
+   * @param groupKey The groupKey value
+   * @param instanceKey The instanceKey value
+   * @param shape The shape value
+   * @param T The value of the T attribute
    * @param options carries optional attribute values
    * @param <U> data type for {@code CollectiveBcastRecvV2} output and operands
    * @return a new instance of CollectiveBcastRecvV2
@@ -153,4 +157,59 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<CollectiveBcastRecvV2<?>> {
+    /**
+     * The groupSize input
+     */
+    public final Operand<TInt32> groupSize;
+
+    /**
+     * The groupKey input
+     */
+    public final Operand<TInt32> groupKey;
+
+    /**
+     * The instanceKey input
+     */
+    public final Operand<TInt32> instanceKey;
+
+    /**
+     * The shape input
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new CollectiveBcastRecvV2<>(op), op, Arrays.asList("T", "Tshape", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      groupSize = (Operand<TInt32>) op.input(inputIndex++);
+      groupKey = (Operand<TInt32>) op.input(inputIndex++);
+      instanceKey = (Operand<TInt32>) op.input(inputIndex++);
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tshape = op.attributes().getAttrType("Tshape");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastSendV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastSendV2.java
index 3bfa4f56fea..afce1f5da7f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastSendV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/CollectiveBcastSendV2.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -50,10 +54,10 @@ private CollectiveBcastSendV2(Operation operation) {
    * Factory method to create a class wrapping a new CollectiveBcastSendV2 operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param groupSize the groupSize value
-   * @param groupKey the groupKey value
-   * @param instanceKey the instanceKey value
+   * @param input The input value
+   * @param groupSize The groupSize value
+   * @param groupKey The groupKey value
+   * @param instanceKey The instanceKey value
    * @param options carries optional attribute values
    * @param <T> data type for {@code CollectiveBcastSendV2} output and operands
    * @return a new instance of CollectiveBcastSendV2
@@ -149,4 +153,53 @@ public Options timeoutSeconds(Float timeoutSeconds) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<CollectiveBcastSendV2<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The groupSize input
+     */
+    public final Operand<TInt32> groupSize;
+
+    /**
+     * The groupKey input
+     */
+    public final Operand<TInt32> groupKey;
+
+    /**
+     * The instanceKey input
+     */
+    public final Operand<TInt32> instanceKey;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The communicationHint attribute
+     */
+    public final String communicationHint;
+
+    /**
+     * The timeoutSeconds attribute
+     */
+    public final float timeoutSeconds;
+
+    public Inputs(GraphOperation op) {
+      super(new CollectiveBcastSendV2<>(op), op, Arrays.asList("T", "communication_hint", "timeout_seconds"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      groupSize = (Operand<TInt32>) op.input(inputIndex++);
+      groupKey = (Operand<TInt32>) op.input(inputIndex++);
+      instanceKey = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      communicationHint = op.attributes().getAttrString("communication_hint");
+      timeoutSeconds = op.attributes().getAttrFloat("timeout_seconds");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/GetOptions.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/GetOptions.java
index 17144898ed1..472e350db9e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/GetOptions.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/GetOptions.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -73,4 +76,17 @@ public Output<TString> serializedOptions() {
   public Output<TString> asOutput() {
     return serializedOptions;
   }
+
+  public static class Inputs extends RawOpInputs<GetOptions> {
+    /**
+     * A variant tensor representing the input dataset.
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    public Inputs(GraphOperation op) {
+      super(new GetOptions(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParameters.java
index bf8befa00bd..10afcd94130 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -49,8 +52,8 @@ private LoadTPUEmbeddingFrequencyEstimatorParameters(Operation operation) {
    * @param scope current scope
    * @param parameters Value of parameters used in the frequency estimator optimization algorithm.
    * @param lastHitStep Value of last_hit_step used in the frequency estimator optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingFrequencyEstimatorParameters
    */
@@ -157,4 +160,53 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingFrequencyEstimatorParameters> {
+    /**
+     * Value of parameters used in the frequency estimator optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of last_hit_step used in the frequency estimator optimization algorithm.
+     */
+    public final Operand<TFloat32> lastHitStep;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingFrequencyEstimatorParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      lastHitStep = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java
index 4d620783b32..0ccf337801b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug(Operation ope
    * @param lastHitStep Value of last_hit_step used in the frequency estimator optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the frequency estimator optimization
    * algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
    */
@@ -160,4 +163,60 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the frequency estimator optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of last_hit_step used in the frequency estimator optimization algorithm.
+     */
+    public final Operand<TFloat32> lastHitStep;
+
+    /**
+     * Value of gradient_accumulators used in the frequency estimator optimization
+     * algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      lastHitStep = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParameters.java
index bc7e7cc35a0..37ad5cf9e4b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -53,8 +56,8 @@ private RetrieveTPUEmbeddingFrequencyEstimatorParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingFrequencyEstimatorParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingFrequencyEstimatorParameters
    */
@@ -177,4 +180,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingFrequencyEstimatorParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingFrequencyEstimatorParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java
index 03cfdd595fc..4a9031c45e1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug(Operation
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
    */
@@ -190,4 +193,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetAlg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetAlg.java
index d73bbace62c..e5daa87691e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetAlg.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetAlg.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -71,4 +74,11 @@ public Output<TInt32> alg() {
   public Output<TInt32> asOutput() {
     return alg;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomGetAlg> {
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomGetAlg(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetKeyCounter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetKeyCounter.java
index 9be0d0463d3..16c50e5c0ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetKeyCounter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/rawops/StatelessRandomGetKeyCounter.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.rawops;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -82,4 +86,23 @@ public Output<? extends TType> key() {
   public Output<? extends TType> counter() {
     return counter;
   }
+
+  public static class Inputs extends RawOpInputs<StatelessRandomGetKeyCounter> {
+    /**
+     * 2 seeds (shape [2]).
+     */
+    public final Operand<? extends TNumber> seed;
+
+    /**
+     * The Tseed attribute
+     */
+    public final DataType Tseed;
+
+    public Inputs(GraphOperation op) {
+      super(new StatelessRandomGetKeyCounter(op), op, Arrays.asList("Tseed"));
+      int inputIndex = 0;
+      seed = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Tseed = op.attributes().getAttrType("Tseed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAbs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAbs.java
index 62a9ded2e42..a1bfbcd2bc3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAbs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAbs.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscAbs(Operation operation) {
    * Factory method to create a class wrapping a new RiscAbs operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscAbs} output and operands
    * @return a new instance of RiscAbs
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscAbs<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscAbs<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAdd.java
index 9c264ee76c4..cbaeb97e7db 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscAdd.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -52,8 +56,8 @@ private RiscAdd(Operation operation) {
    * Factory method to create a class wrapping a new RiscAdd operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscAdd} output and operands
    * @return a new instance of RiscAdd
    */
@@ -80,4 +84,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscAdd<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscAdd<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryArithmetic.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryArithmetic.java
index 80c390630cf..ffe646419f5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryArithmetic.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryArithmetic.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,9 +53,9 @@ private RiscBinaryArithmetic(Operation operation) {
    * Factory method to create a class wrapping a new RiscBinaryArithmetic operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
-   * @param opType the value of the opType property
+   * @param x The x value
+   * @param y The y value
+   * @param opType The value of the opType attribute
    * @param <T> data type for {@code RiscBinaryArithmetic} output and operands
    * @return a new instance of RiscBinaryArithmetic
    */
@@ -80,4 +84,35 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscBinaryArithmetic<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The opType attribute
+     */
+    public final String opType;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscBinaryArithmetic<>(op), op, Arrays.asList("op_type", "T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      opType = op.attributes().getAttrString("op_type");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryComparison.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryComparison.java
index bfd597f5663..d0221df4424 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryComparison.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBinaryComparison.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -48,9 +52,9 @@ private RiscBinaryComparison(Operation operation) {
    * Factory method to create a class wrapping a new RiscBinaryComparison operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
-   * @param opType the value of the opType property
+   * @param x The x value
+   * @param y The y value
+   * @param opType The value of the opType attribute
    * @param <T> data type for {@code RiscBinaryComparison} output and operands
    * @return a new instance of RiscBinaryComparison
    */
@@ -79,4 +83,35 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscBinaryComparison> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The opType attribute
+     */
+    public final String opType;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscBinaryComparison(op), op, Arrays.asList("op_type", "T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      opType = op.attributes().getAttrString("op_type");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBitcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBitcast.java
index 9eab1ea3e64..9e13bc53c9a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBitcast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBitcast.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -50,8 +54,8 @@ private RiscBitcast(Operation operation) {
    * Factory method to create a class wrapping a new RiscBitcast operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param DstT the value of the DstT property
+   * @param x The x value
+   * @param DstT The value of the DstT attribute
    * @param <U> data type for {@code RiscBitcast} output and operands
    * @return a new instance of RiscBitcast
    */
@@ -79,4 +83,29 @@ public Output<U> y() {
   public Output<U> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<RiscBitcast<?>> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TType> x;
+
+    /**
+     * The SrcT attribute
+     */
+    public final DataType SrcT;
+
+    /**
+     * The DstT attribute
+     */
+    public final DataType DstT;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscBitcast<>(op), op, Arrays.asList("SrcT", "DstT"));
+      int inputIndex = 0;
+      x = (Operand<? extends TType>) op.input(inputIndex++);
+      SrcT = op.attributes().getAttrType("SrcT");
+      DstT = op.attributes().getAttrType("DstT");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBroadcast.java
index a61a489b630..f23d678ee3c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBroadcast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscBroadcast.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -50,8 +54,8 @@ private RiscBroadcast(Operation operation) {
    * Factory method to create a class wrapping a new RiscBroadcast operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param shape the shape value
+   * @param input The input value
+   * @param shape The shape value
    * @param <T> data type for {@code RiscBroadcast} output and operands
    * @return a new instance of RiscBroadcast
    */
@@ -79,4 +83,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RiscBroadcast<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The shape input
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscBroadcast<>(op), op, Arrays.asList("T", "Tidx"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCast.java
index 43630d9b0fc..19713cb9325 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCast.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -50,8 +54,8 @@ private RiscCast(Operation operation) {
    * Factory method to create a class wrapping a new RiscCast operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param DstT the value of the DstT property
+   * @param x The x value
+   * @param DstT The value of the DstT attribute
    * @param <U> data type for {@code RiscCast} output and operands
    * @return a new instance of RiscCast
    */
@@ -79,4 +83,29 @@ public Output<U> y() {
   public Output<U> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<RiscCast<?>> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TType> x;
+
+    /**
+     * The SrcT attribute
+     */
+    public final DataType SrcT;
+
+    /**
+     * The DstT attribute
+     */
+    public final DataType DstT;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscCast<>(op), op, Arrays.asList("SrcT", "DstT"));
+      int inputIndex = 0;
+      x = (Operand<? extends TType>) op.input(inputIndex++);
+      SrcT = op.attributes().getAttrType("SrcT");
+      DstT = op.attributes().getAttrType("DstT");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCeil.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCeil.java
index e50de40805e..993e6fe0c4f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCeil.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCeil.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscCeil(Operation operation) {
    * Factory method to create a class wrapping a new RiscCeil operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscCeil} output and operands
    * @return a new instance of RiscCeil
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscCeil<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscCeil<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCholesky.java
index e8ff60545ed..214e0f0729c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCholesky.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCholesky.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscCholesky(Operation operation) {
    * Factory method to create a class wrapping a new RiscCholesky operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code RiscCholesky} output and operands
    * @return a new instance of RiscCholesky
    */
@@ -75,4 +79,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscCholesky<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscCholesky<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConcat.java
index 26c4d01d62a..b09c64975f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConcat.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -51,8 +55,8 @@ private RiscConcat(Operation operation) {
    * Factory method to create a class wrapping a new RiscConcat operation.
    *
    * @param scope current scope
-   * @param values the values value
-   * @param axis the axis value
+   * @param values The values value
+   * @param axis The axis value
    * @param <T> data type for {@code RiscConcat} output and operands
    * @return a new instance of RiscConcat
    */
@@ -80,4 +84,37 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RiscConcat<T>> {
+    /**
+     * The values input
+     */
+    public final Iterable<Operand<T>> values;
+
+    /**
+     * The axis input
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscConcat<>(op), op, Arrays.asList("T", "Tidx"));
+      int inputIndex = 0;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCondition.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCondition.java
index cfafe938468..4799eeaea37 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCondition.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCondition.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -52,12 +56,12 @@ private RiscCondition(Operation operation) {
    * Factory method to create a class wrapping a new RiscCondition operation.
    *
    * @param scope current scope
-   * @param pred the pred value
-   * @param inputTrue the inputTrue value
-   * @param inputFalse the inputFalse value
-   * @param funcTrue the value of the funcTrue property
-   * @param funcFalse the value of the funcFalse property
-   * @param DstT the value of the DstT property
+   * @param pred The pred value
+   * @param inputTrue The inputTrue value
+   * @param inputFalse The inputFalse value
+   * @param funcTrue The value of the funcTrue attribute
+   * @param funcFalse The value of the funcFalse attribute
+   * @param DstT The value of the DstT attribute
    * @param <U> data type for {@code RiscCondition} output and operands
    * @param <T> data type for {@code RiscCondition} output and operands
    * @return a new instance of RiscCondition
@@ -91,4 +95,41 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscCondition<?>> {
+    /**
+     * The pred input
+     */
+    public final Operand<TBool> pred;
+
+    /**
+     * The inputTrue input
+     */
+    public final Operand<T> inputTrue;
+
+    /**
+     * The inputFalse input
+     */
+    public final Operand<T> inputFalse;
+
+    /**
+     * The SrcT attribute
+     */
+    public final DataType SrcT;
+
+    /**
+     * The DstT attribute
+     */
+    public final DataType DstT;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscCondition<>(op), op, Arrays.asList("SrcT", "DstT"));
+      int inputIndex = 0;
+      pred = (Operand<TBool>) op.input(inputIndex++);
+      inputTrue = (Operand<T>) op.input(inputIndex++);
+      inputFalse = (Operand<T>) op.input(inputIndex++);
+      SrcT = op.attributes().getAttrType("SrcT");
+      DstT = op.attributes().getAttrType("DstT");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConv.java
index e5f8100456d..eef8246faa8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscConv.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -51,9 +54,9 @@ private RiscConv(Operation operation) {
    * Factory method to create a class wrapping a new RiscConv operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param filter the filter value
-   * @param strides the value of the strides property
+   * @param input The input value
+   * @param filter The filter value
+   * @param strides The value of the strides attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code RiscConv} output and operands
    * @return a new instance of RiscConv
@@ -114,7 +117,7 @@ public static Options dilations(List<Long> dilations) {
    * @param dilations the dilations option
    * @return this Options instance.
    */
-  public static Options dilations(Long[] dilations) {
+  public static Options dilations(Long... dilations) {
     return new Options().dilations(dilations);
   }
 
@@ -176,4 +179,47 @@ public Options dilations(Long... dilations) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscConv<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The filter input
+     */
+    public final Operand<T> filter;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The dataFormat attribute
+     */
+    public final String dataFormat;
+
+    /**
+     * The dilations attribute
+     */
+    public final long[] dilations;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscConv<>(op), op, Arrays.asList("T", "strides", "data_format", "dilations"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      filter = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      strides = op.attributes().getAttrIntList("strides");
+      dataFormat = op.attributes().getAttrString("data_format");
+      dilations = op.attributes().getAttrIntList("dilations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCos.java
index c82fa527614..db02acbfcdf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCos.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscCos.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscCos(Operation operation) {
    * Factory method to create a class wrapping a new RiscCos operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscCos} output and operands
    * @return a new instance of RiscCos
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscCos<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscCos<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDiv.java
index aa272b56121..6dcdf4e796b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDiv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDiv.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscDiv(Operation operation) {
    * Factory method to create a class wrapping a new RiscDiv operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscDiv} output and operands
    * @return a new instance of RiscDiv
    */
@@ -77,4 +81,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscDiv<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscDiv<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDot.java
index ddae24dbde4..a3db102582d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDot.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscDot.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscDot(Operation operation) {
    * Factory method to create a class wrapping a new RiscDot operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param b the b value
+   * @param a The a value
+   * @param b The b value
    * @param options carries optional attribute values
    * @param <T> data type for {@code RiscDot} output and operands
    * @return a new instance of RiscDot
@@ -143,4 +147,41 @@ public Options transposeB(Boolean transposeB) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscDot<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The b input
+     */
+    public final Operand<T> b;
+
+    /**
+     * The transposeA attribute
+     */
+    public final boolean transposeA;
+
+    /**
+     * The transposeB attribute
+     */
+    public final boolean transposeB;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscDot<>(op), op, Arrays.asList("transpose_a", "transpose_b", "T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscExp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscExp.java
index 07e4e22f52d..6868da2c4bb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscExp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscExp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscExp(Operation operation) {
    * Factory method to create a class wrapping a new RiscExp operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscExp} output and operands
    * @return a new instance of RiscExp
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscExp<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscExp<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFft.java
index c835dc4e652..31b27b88913 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFft.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -49,7 +53,7 @@ private RiscFft(Operation operation) {
    * Factory method to create a class wrapping a new RiscFft operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code RiscFft} output and operands
    * @return a new instance of RiscFft
    */
@@ -75,4 +79,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RiscFft<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscFft<>(op), op, Arrays.asList("Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFloor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFloor.java
index 4f3d19c6ac2..aabcfb22dc7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFloor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscFloor.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscFloor(Operation operation) {
    * Factory method to create a class wrapping a new RiscFloor operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscFloor} output and operands
    * @return a new instance of RiscFloor
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscFloor<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscFloor<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscGather.java
index 3db996340a5..f4128861b39 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscGather.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -50,9 +54,9 @@ private RiscGather(Operation operation) {
    * Factory method to create a class wrapping a new RiscGather operation.
    *
    * @param scope current scope
-   * @param params the params value
-   * @param indices the indices value
-   * @param axis the axis value
+   * @param params The params value
+   * @param indices The indices value
+   * @param axis The axis value
    * @param options carries optional attribute values
    * @param <T> data type for {@code RiscGather} output and operands
    * @return a new instance of RiscGather
@@ -120,4 +124,53 @@ public Options batchDims(Long batchDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RiscGather<T>> {
+    /**
+     * The params input
+     */
+    public final Operand<T> params;
+
+    /**
+     * The indices input
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The axis input
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The batchDims attribute
+     */
+    public final long batchDims;
+
+    /**
+     * The Tparams attribute
+     */
+    public final DataType Tparams;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Taxis attribute
+     */
+    public final DataType Taxis;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscGather<>(op), op, Arrays.asList("batch_dims", "Tparams", "Tindices", "Taxis"));
+      int inputIndex = 0;
+      params = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      batchDims = op.attributes().getAttrInt("batch_dims");
+      Tparams = op.attributes().getAttrType("Tparams");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Taxis = op.attributes().getAttrType("Taxis");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscImag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscImag.java
index 0b48641bf62..120bb80b8ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscImag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscImag.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -52,8 +56,8 @@ private RiscImag(Operation operation) {
    * Factory method to create a class wrapping a new RiscImag operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code RiscImag} output and operands
    * @return a new instance of RiscImag
    */
@@ -72,7 +76,7 @@ public static <U extends TNumber> RiscImag<U> create(Scope scope, Operand<? exte
    * Factory method to create a class wrapping a new RiscImag operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of RiscImag, with default output types
    */
   @Endpoint(
@@ -95,4 +99,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<RiscImag<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscImag<>(op), op, Arrays.asList("T", "Tout"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscIsFinite.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscIsFinite.java
index 79371c4fa1e..b87b3932c05 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscIsFinite.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscIsFinite.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
 
@@ -48,7 +52,7 @@ private RiscIsFinite(Operation operation) {
    * Factory method to create a class wrapping a new RiscIsFinite operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of RiscIsFinite
    */
   @Endpoint(
@@ -73,4 +77,23 @@ public Output<TBool> y() {
   public Output<TBool> asOutput() {
     return y;
   }
+
+  public static class Inputs extends RawOpInputs<RiscIsFinite> {
+    /**
+     * The x input
+     */
+    public final Operand<? extends TNumber> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscIsFinite(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLog.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLog.java
index e04167ef115..b4428844f90 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLog.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLog.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscLog(Operation operation) {
    * Factory method to create a class wrapping a new RiscLog operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscLog} output and operands
    * @return a new instance of RiscLog
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscLog<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscLog<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalAnd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalAnd.java
index 72bbd770a90..a4ef38dd73d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalAnd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalAnd.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -47,8 +50,8 @@ private RiscLogicalAnd(Operation operation) {
    * Factory method to create a class wrapping a new RiscLogicalAnd operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @return a new instance of RiscLogicalAnd
    */
   @Endpoint(
@@ -74,4 +77,23 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs extends RawOpInputs<RiscLogicalAnd> {
+    /**
+     * The x input
+     */
+    public final Operand<TBool> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<TBool> y;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscLogicalAnd(op), op, Arrays.asList());
+      int inputIndex = 0;
+      x = (Operand<TBool>) op.input(inputIndex++);
+      y = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalNot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalNot.java
index 74c9a634ea8..c67de8825d5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalNot.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalNot.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -47,7 +50,7 @@ private RiscLogicalNot(Operation operation) {
    * Factory method to create a class wrapping a new RiscLogicalNot operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @return a new instance of RiscLogicalNot
    */
   @Endpoint(
@@ -72,4 +75,17 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs extends RawOpInputs<RiscLogicalNot> {
+    /**
+     * The x input
+     */
+    public final Operand<TBool> x;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscLogicalNot(op), op, Arrays.asList());
+      int inputIndex = 0;
+      x = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalOr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalOr.java
index d22cbd7de03..59273fb3f82 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalOr.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscLogicalOr.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -47,8 +50,8 @@ private RiscLogicalOr(Operation operation) {
    * Factory method to create a class wrapping a new RiscLogicalOr operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @return a new instance of RiscLogicalOr
    */
   @Endpoint(
@@ -74,4 +77,23 @@ public Output<TBool> z() {
   public Output<TBool> asOutput() {
     return z;
   }
+
+  public static class Inputs extends RawOpInputs<RiscLogicalOr> {
+    /**
+     * The x input
+     */
+    public final Operand<TBool> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<TBool> y;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscLogicalOr(op), op, Arrays.asList());
+      int inputIndex = 0;
+      x = (Operand<TBool>) op.input(inputIndex++);
+      y = (Operand<TBool>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMax.java
index e415799e553..c5a73463a66 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMax.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -51,8 +55,8 @@ private RiscMax(Operation operation) {
    * Factory method to create a class wrapping a new RiscMax operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscMax} output and operands
    * @return a new instance of RiscMax
    */
@@ -79,4 +83,29 @@ public Output<T> max() {
   public Output<T> asOutput() {
     return max;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscMax<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscMax<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMin.java
index 2063b4a32fb..5d565b09d10 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMin.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscMin(Operation operation) {
    * Factory method to create a class wrapping a new RiscMin operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscMin} output and operands
    * @return a new instance of RiscMin
    */
@@ -77,4 +81,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscMin<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscMin<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMul.java
index 6bc95f2f430..64285c41c37 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscMul.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscMul(Operation operation) {
    * Factory method to create a class wrapping a new RiscMul operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscMul} output and operands
    * @return a new instance of RiscMul
    */
@@ -77,4 +81,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscMul<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscMul<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscNeg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscNeg.java
index 0ac4df637da..9a759a04a6f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscNeg.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscNeg.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscNeg(Operation operation) {
    * Factory method to create a class wrapping a new RiscNeg operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscNeg} output and operands
    * @return a new instance of RiscNeg
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscNeg<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscNeg<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPad.java
index d237088a626..96d50ba86d5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,9 +53,9 @@ private RiscPad(Operation operation) {
    * Factory method to create a class wrapping a new RiscPad operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param paddings the paddings value
-   * @param constantValues the constantValues value
+   * @param input The input value
+   * @param paddings The paddings value
+   * @param constantValues The constantValues value
    * @param <T> data type for {@code RiscPad} output and operands
    * @return a new instance of RiscPad
    */
@@ -80,4 +84,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscPad<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The paddings input
+     */
+    public final Operand<? extends TNumber> paddings;
+
+    /**
+     * The constantValues input
+     */
+    public final Operand<T> constantValues;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tpaddings attribute
+     */
+    public final DataType Tpaddings;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscPad<>(op), op, Arrays.asList("T", "Tpaddings"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      paddings = (Operand<? extends TNumber>) op.input(inputIndex++);
+      constantValues = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tpaddings = op.attributes().getAttrType("Tpaddings");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPool.java
index 66fd3cbe326..0ee16aa7da8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPool.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -50,10 +54,10 @@ private RiscPool(Operation operation) {
    * Factory method to create a class wrapping a new RiscPool operation.
    *
    * @param scope current scope
-   * @param value the value value
-   * @param ksize the value of the ksize property
-   * @param strides the value of the strides property
-   * @param poolingType the value of the poolingType property
+   * @param value The value value
+   * @param ksize The value of the ksize attribute
+   * @param strides The value of the strides attribute
+   * @param poolingType The value of the poolingType attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code RiscPool} output and operands
    * @return a new instance of RiscPool
@@ -130,4 +134,47 @@ public Options dataFormat(String dataFormat) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscPool<T>> {
+    /**
+     * The value input
+     */
+    public final Operand<T> value;
+
+    /**
+     * The ksize attribute
+     */
+    public final long[] ksize;
+
+    /**
+     * The strides attribute
+     */
+    public final long[] strides;
+
+    /**
+     * The poolingType attribute
+     */
+    public final String poolingType;
+
+    /**
+     * The dataFormat attribute
+     */
+    public final String dataFormat;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscPool<>(op), op, Arrays.asList("ksize", "strides", "pooling_type", "data_format", "T"));
+      int inputIndex = 0;
+      value = (Operand<T>) op.input(inputIndex++);
+      ksize = op.attributes().getAttrIntList("ksize");
+      strides = op.attributes().getAttrIntList("strides");
+      poolingType = op.attributes().getAttrString("pooling_type");
+      dataFormat = op.attributes().getAttrString("data_format");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPow.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPow.java
index 57261654a6d..531ea2570e0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPow.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscPow.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscPow(Operation operation) {
    * Factory method to create a class wrapping a new RiscPow operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscPow} output and operands
    * @return a new instance of RiscPow
    */
@@ -77,4 +81,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscPow<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscPow<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRandomUniform.java
index 194bbf3a944..b5b1c995a4e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRandomUniform.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRandomUniform.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -48,7 +52,7 @@ private RiscRandomUniform(Operation operation) {
    * Factory method to create a class wrapping a new RiscRandomUniform operation.
    *
    * @param scope current scope
-   * @param shape the shape value
+   * @param shape The shape value
    * @param options carries optional attribute values
    * @return a new instance of RiscRandomUniform
    */
@@ -113,4 +117,29 @@ public Options seed(Long seed) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RiscRandomUniform> {
+    /**
+     * The shape input
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The seed attribute
+     */
+    public final long seed;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscRandomUniform(op), op, Arrays.asList("seed", "T"));
+      int inputIndex = 0;
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      seed = op.attributes().getAttrInt("seed");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReal.java
index 2751bd35a2e..4c0e1b00708 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReal.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -52,8 +56,8 @@ private RiscReal(Operation operation) {
    * Factory method to create a class wrapping a new RiscReal operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param Tout the value of the Tout property
+   * @param input The input value
+   * @param Tout The value of the Tout attribute
    * @param <U> data type for {@code RiscReal} output and operands
    * @return a new instance of RiscReal
    */
@@ -72,7 +76,7 @@ public static <U extends TNumber> RiscReal<U> create(Scope scope, Operand<? exte
    * Factory method to create a class wrapping a new RiscReal operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of RiscReal, with default output types
    */
   @Endpoint(
@@ -95,4 +99,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<RiscReal<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscReal<>(op), op, Arrays.asList("T", "Tout"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tout = op.attributes().getAttrType("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReduce.java
index 6fdba24a2a3..68a4fb6e6cb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReduce.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,9 +53,9 @@ private RiscReduce(Operation operation) {
    * Factory method to create a class wrapping a new RiscReduce operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
-   * @param axis the axis value
-   * @param reduceType the value of the reduceType property
+   * @param tensor The tensor value
+   * @param axis The axis value
+   * @param reduceType The value of the reduceType attribute
    * @param <T> data type for {@code RiscReduce} output and operands
    * @return a new instance of RiscReduce
    */
@@ -80,4 +84,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscReduce<T>> {
+    /**
+     * The tensor input
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * The axis input
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The reduceType attribute
+     */
+    public final String reduceType;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscReduce<>(op), op, Arrays.asList("reduce_type", "Index", "T"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      reduceType = op.attributes().getAttrString("reduce_type");
+      Index = op.attributes().getAttrType("Index");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRem.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRem.java
index a5afe0bc654..a05a200a662 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRem.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscRem.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscRem(Operation operation) {
    * Factory method to create a class wrapping a new RiscRem operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscRem} output and operands
    * @return a new instance of RiscRem
    */
@@ -77,4 +81,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscRem<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscRem<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReshape.java
index e38b38da3b8..1d31b746200 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReshape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReshape.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscReshape(Operation operation) {
    * Factory method to create a class wrapping a new RiscReshape operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
-   * @param shape the shape value
+   * @param tensor The tensor value
+   * @param shape The shape value
    * @param <T> data type for {@code RiscReshape} output and operands
    * @return a new instance of RiscReshape
    */
@@ -78,4 +82,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscReshape<T>> {
+    /**
+     * The tensor input
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * The shape input
+     */
+    public final Operand<? extends TNumber> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tshape attribute
+     */
+    public final DataType Tshape;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscReshape<>(op), op, Arrays.asList("T", "Tshape"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      shape = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tshape = op.attributes().getAttrType("Tshape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReverse.java
index 01bc414dcea..6c63576cece 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReverse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscReverse.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscReverse(Operation operation) {
    * Factory method to create a class wrapping a new RiscReverse operation.
    *
    * @param scope current scope
-   * @param tensor the tensor value
-   * @param axis the axis value
+   * @param tensor The tensor value
+   * @param axis The axis value
    * @param <T> data type for {@code RiscReverse} output and operands
    * @return a new instance of RiscReverse
    */
@@ -78,4 +82,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscReverse<T>> {
+    /**
+     * The tensor input
+     */
+    public final Operand<T> tensor;
+
+    /**
+     * The axis input
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscReverse<>(op), op, Arrays.asList("Tidx", "T"));
+      int inputIndex = 0;
+      tensor = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Tidx = op.attributes().getAttrType("Tidx");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscScatter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscScatter.java
index 7cff6bf97d7..9d4b7e75a5f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscScatter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscScatter.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,9 +53,9 @@ private RiscScatter(Operation operation) {
    * Factory method to create a class wrapping a new RiscScatter operation.
    *
    * @param scope current scope
-   * @param indices the indices value
-   * @param updates the updates value
-   * @param shape the shape value
+   * @param indices The indices value
+   * @param updates The updates value
+   * @param shape The shape value
    * @param <U> data type for {@code RiscScatter} output and operands
    * @param <T> data type for {@code RiscScatter} output and operands
    * @return a new instance of RiscScatter
@@ -81,4 +85,41 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<RiscScatter<U>> {
+    /**
+     * The indices input
+     */
+    public final Operand<T> indices;
+
+    /**
+     * The updates input
+     */
+    public final Operand<U> updates;
+
+    /**
+     * The shape input
+     */
+    public final Operand<T> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscScatter<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      indices = (Operand<T>) op.input(inputIndex++);
+      updates = (Operand<U>) op.input(inputIndex++);
+      shape = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscShape.java
index e62af54f8ab..48b15342aa8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscShape.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -51,8 +55,8 @@ private RiscShape(Operation operation) {
    * Factory method to create a class wrapping a new RiscShape operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param outType the value of the outType property
+   * @param input The input value
+   * @param outType The value of the outType attribute
    * @param <U> data type for {@code RiscShape} output and operands
    * @return a new instance of RiscShape
    */
@@ -71,7 +75,7 @@ public static <U extends TNumber> RiscShape<U> create(Scope scope,
    * Factory method to create a class wrapping a new RiscShape operation, with the default output types.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of RiscShape, with default output types
    */
   @Endpoint(
@@ -94,4 +98,29 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<RiscShape<?>> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The outType attribute
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscShape<>(op), op, Arrays.asList("T", "out_type"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSign.java
index adc02df655b..d9dc1645279 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSign.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,7 +53,7 @@ private RiscSign(Operation operation) {
    * Factory method to create a class wrapping a new RiscSign operation.
    *
    * @param scope current scope
-   * @param x the x value
+   * @param x The x value
    * @param <T> data type for {@code RiscSign} output and operands
    * @return a new instance of RiscSign
    */
@@ -75,4 +79,23 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscSign<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscSign<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSlice.java
index 021766472b9..17c1ae867f8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSlice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSlice.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,9 +53,9 @@ private RiscSlice(Operation operation) {
    * Factory method to create a class wrapping a new RiscSlice operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param begin the begin value
-   * @param sizeOutput the sizeOutput value
+   * @param input The input value
+   * @param begin The begin value
+   * @param sizeOutput The sizeOutput value
    * @param <T> data type for {@code RiscSlice} output and operands
    * @param <U> data type for {@code RiscSlice} output and operands
    * @return a new instance of RiscSlice
@@ -81,4 +85,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<RiscSlice<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The begin input
+     */
+    public final Operand<U> begin;
+
+    /**
+     * The sizeOutput input
+     */
+    public final Operand<U> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscSlice<>(op), op, Arrays.asList("T", "Index"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      begin = (Operand<U>) op.input(inputIndex++);
+      sizeOutput = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Index = op.attributes().getAttrType("Index");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSort.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSort.java
index 8740f1e2b38..05f439e84d7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSort.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSort.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,9 +53,9 @@ private RiscSort(Operation operation) {
    * Factory method to create a class wrapping a new RiscSort operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param axis the axis value
-   * @param direction the value of the direction property
+   * @param input The input value
+   * @param axis The axis value
+   * @param direction The value of the direction attribute
    * @param <T> data type for {@code RiscSort} output and operands
    * @return a new instance of RiscSort
    */
@@ -80,4 +84,41 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscSort<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The axis input
+     */
+    public final Operand<? extends TNumber> axis;
+
+    /**
+     * The Index attribute
+     */
+    public final DataType Index;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The direction attribute
+     */
+    public final String direction;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscSort<>(op), op, Arrays.asList("Index", "T", "direction"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      axis = (Operand<? extends TNumber>) op.input(inputIndex++);
+      Index = op.attributes().getAttrType("Index");
+      T = op.attributes().getAttrType("T");
+      direction = op.attributes().getAttrString("direction");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSqueeze.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSqueeze.java
index 0f4aa6bb852..c10e67550b5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSqueeze.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSqueeze.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -51,7 +54,7 @@ private RiscSqueeze(Operation operation) {
    * Factory method to create a class wrapping a new RiscSqueeze operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code RiscSqueeze} output and operands
    * @return a new instance of RiscSqueeze
@@ -93,7 +96,7 @@ public static Options squeezeDims(List<Long> squeezeDims) {
    * @param squeezeDims the squeezeDims option
    * @return this Options instance.
    */
-  public static Options squeezeDims(Long[] squeezeDims) {
+  public static Options squeezeDims(Long... squeezeDims) {
     return new Options().squeezeDims(squeezeDims);
   }
 
@@ -142,4 +145,29 @@ public Options squeezeDims(Long... squeezeDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RiscSqueeze<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The squeezeDims attribute
+     */
+    public final long[] squeezeDims;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscSqueeze<>(op), op, Arrays.asList("T", "squeeze_dims"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      squeezeDims = op.attributes().getAttrIntList("squeeze_dims");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSub.java
index d52f056319e..2da64a6b5fa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSub.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscSub.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscSub(Operation operation) {
    * Factory method to create a class wrapping a new RiscSub operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param y the y value
+   * @param x The x value
+   * @param y The y value
    * @param <T> data type for {@code RiscSub} output and operands
    * @return a new instance of RiscSub
    */
@@ -77,4 +81,29 @@ public Output<T> z() {
   public Output<T> asOutput() {
     return z;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscSub<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The y input
+     */
+    public final Operand<T> y;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscSub<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      y = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTranspose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTranspose.java
index 3d84b52f2c8..58d0eb662d5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTranspose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTranspose.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -50,8 +54,8 @@ private RiscTranspose(Operation operation) {
    * Factory method to create a class wrapping a new RiscTranspose operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param perm the perm value
+   * @param x The x value
+   * @param perm The perm value
    * @param <T> data type for {@code RiscTranspose} output and operands
    * @return a new instance of RiscTranspose
    */
@@ -79,4 +83,35 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RiscTranspose<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The perm input
+     */
+    public final Operand<? extends TNumber> perm;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tperm attribute
+     */
+    public final DataType Tperm;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscTranspose<>(op), op, Arrays.asList("T", "Tperm"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      perm = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tperm = op.attributes().getAttrType("Tperm");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTriangularSolve.java
index d7e8df3c8c1..cfd5976bb4c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTriangularSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscTriangularSolve.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscTriangularSolve(Operation operation) {
    * Factory method to create a class wrapping a new RiscTriangularSolve operation.
    *
    * @param scope current scope
-   * @param matrix the matrix value
-   * @param rhs the rhs value
+   * @param matrix The matrix value
+   * @param rhs The rhs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code RiscTriangularSolve} output and operands
    * @return a new instance of RiscTriangularSolve
@@ -143,4 +147,41 @@ public Options adjoint(Boolean adjoint) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscTriangularSolve<T>> {
+    /**
+     * The matrix input
+     */
+    public final Operand<T> matrix;
+
+    /**
+     * The rhs input
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * The lower attribute
+     */
+    public final boolean lower;
+
+    /**
+     * The adjoint attribute
+     */
+    public final boolean adjoint;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscTriangularSolve<>(op), op, Arrays.asList("lower", "adjoint", "T"));
+      int inputIndex = 0;
+      matrix = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      lower = op.attributes().getAttrBool("lower");
+      adjoint = op.attributes().getAttrBool("adjoint");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscUnary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscUnary.java
index 0af89d9cfa0..59b52dc8a17 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscUnary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscUnary.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.risc;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -49,8 +53,8 @@ private RiscUnary(Operation operation) {
    * Factory method to create a class wrapping a new RiscUnary operation.
    *
    * @param scope current scope
-   * @param x the x value
-   * @param opType the value of the opType property
+   * @param x The x value
+   * @param opType The value of the opType attribute
    * @param <T> data type for {@code RiscUnary} output and operands
    * @return a new instance of RiscUnary
    */
@@ -77,4 +81,29 @@ public Output<T> y() {
   public Output<T> asOutput() {
     return y;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<RiscUnary<T>> {
+    /**
+     * The x input
+     */
+    public final Operand<T> x;
+
+    /**
+     * The opType attribute
+     */
+    public final String opType;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscUnary<>(op), op, Arrays.asList("op_type", "T"));
+      int inputIndex = 0;
+      x = (Operand<T>) op.input(inputIndex++);
+      opType = op.attributes().getAttrString("op_type");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscWhile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscWhile.java
index ba34e5122b5..010f239e8db 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscWhile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/risc/RiscWhile.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,8 +29,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -56,9 +59,9 @@ private RiscWhile(Operation operation) {
    * Factory method to create a class wrapping a new RiscWhile operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param cond the value of the cond property
-   * @param body the value of the body property
+   * @param input The input value
+   * @param cond The value of the cond attribute
+   * @param body The value of the body attribute
    * @param options carries optional attribute values
    * @return a new instance of RiscWhile
    */
@@ -104,7 +107,7 @@ public static Options outputShapes(List<Shape> outputShapes) {
    * @param outputShapes the outputShapes option
    * @return this Options instance.
    */
-  public static Options outputShapes(Shape[] outputShapes) {
+  public static Options outputShapes(Shape... outputShapes) {
     return new Options().outputShapes(outputShapes);
   }
 
@@ -177,4 +180,37 @@ public Options parallelIterations(Long parallelIterations) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RiscWhile> {
+    /**
+     * The input input
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    /**
+     * The outputShapes attribute
+     */
+    public final Shape[] outputShapes;
+
+    /**
+     * The parallelIterations attribute
+     */
+    public final long parallelIterations;
+
+    public Inputs(GraphOperation op) {
+      super(new RiscWhile(op), op, Arrays.asList("T", "output_shapes", "parallel_iterations"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      T = op.attributes().getAttrTypeList("T");
+      outputShapes = op.attributes().getAttrShapeList("output_shapes");
+      parallelIterations = op.attributes().getAttrInt("parallel_iterations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft.java
index 742b9fe08c4..31fdd2bb931 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private BatchFft(Operation operation) {
    * Factory method to create a class wrapping a new BatchFFT operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchFft
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<BatchFft> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchFft(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft2d.java
index 6767347af52..1b7fb596496 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft2d.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private BatchFft2d(Operation operation) {
    * Factory method to create a class wrapping a new BatchFFT2D operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchFft2d
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<BatchFft2d> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchFft2d(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft3d.java
index 91e241a7754..35c940d8abf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchFft3d.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private BatchFft3d(Operation operation) {
    * Factory method to create a class wrapping a new BatchFFT3D operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchFft3d
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<BatchFft3d> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchFft3d(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft.java
index f9268e359ae..9fedc13692e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private BatchIfft(Operation operation) {
    * Factory method to create a class wrapping a new BatchIFFT operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchIfft
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<BatchIfft> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchIfft(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft2d.java
index 163b0271985..c7cf6cb1e96 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft2d.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private BatchIfft2d(Operation operation) {
    * Factory method to create a class wrapping a new BatchIFFT2D operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchIfft2d
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<BatchIfft2d> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchIfft2d(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft3d.java
index 32011d3e585..c23e16b79a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/BatchIfft3d.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private BatchIfft3d(Operation operation) {
    * Factory method to create a class wrapping a new BatchIFFT3D operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @return a new instance of BatchIfft3d
    */
   @Endpoint(
@@ -78,4 +81,17 @@ public Output<? extends TType> output() {
   public Output<TType> asOutput() {
     return (Output<TType>) output;
   }
+
+  public static class Inputs extends RawOpInputs<BatchIfft3d> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchIfft3d(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java
index f4a1f5c64d8..bf800846caa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -85,4 +89,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Fft<T>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Fft<>(op), op, Arrays.asList("Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java
index 63778ffca11..097ea3cf43d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -85,4 +89,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Fft2d<T>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Fft2d<>(op), op, Arrays.asList("Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java
index 41ce94f46c3..7fcf6354abe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -85,4 +89,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Fft3d<T>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Fft3d<>(op), op, Arrays.asList("Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java
index 2a4b7b56db8..787c57575df 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -85,4 +89,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Ifft<T>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Ifft<>(op), op, Arrays.asList("Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java
index 6dbd0bc7d93..fc3e42c7d18 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -85,4 +89,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Ifft2d<T>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Ifft2d<>(op), op, Arrays.asList("Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java
index 4b427df602d..9d9910f20b6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -85,4 +89,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Ifft3d<T>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Ifft3d<>(op), op, Arrays.asList("Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java
index 2501fca9f4f..bf619275e89 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -70,7 +74,7 @@ private Irfft(Operation operation) {
    * @param scope current scope
    * @param input A complex tensor.
    * @param fftLength An int32 tensor of shape [1]. The FFT length.
-   * @param Treal the value of the Treal property
+   * @param Treal The value of the Treal attribute
    * @param <U> data type for {@code IRFFT} output and operands
    * @return a new instance of Irfft
    */
@@ -120,4 +124,35 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Irfft<?>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * An int32 tensor of shape [1]. The FFT length.
+     */
+    public final Operand<TInt32> fftLength;
+
+    /**
+     * The Treal attribute
+     */
+    public final DataType Treal;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Irfft<>(op), op, Arrays.asList("Treal", "Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      fftLength = (Operand<TInt32>) op.input(inputIndex++);
+      Treal = op.attributes().getAttrType("Treal");
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java
index 3ec6240540a..76ef5401d06 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -71,7 +75,7 @@ private Irfft2d(Operation operation) {
    * @param scope current scope
    * @param input A complex tensor.
    * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension.
-   * @param Treal the value of the Treal property
+   * @param Treal The value of the Treal attribute
    * @param <U> data type for {@code IRFFT2D} output and operands
    * @return a new instance of Irfft2d
    */
@@ -121,4 +125,35 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Irfft2d<?>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * An int32 tensor of shape [2]. The FFT length for each dimension.
+     */
+    public final Operand<TInt32> fftLength;
+
+    /**
+     * The Treal attribute
+     */
+    public final DataType Treal;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Irfft2d<>(op), op, Arrays.asList("Treal", "Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      fftLength = (Operand<TInt32>) op.input(inputIndex++);
+      Treal = op.attributes().getAttrType("Treal");
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java
index 8fb04f1d567..951d90c24f5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
@@ -71,7 +75,7 @@ private Irfft3d(Operation operation) {
    * @param scope current scope
    * @param input A complex tensor.
    * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension.
-   * @param Treal the value of the Treal property
+   * @param Treal The value of the Treal attribute
    * @param <U> data type for {@code IRFFT3D} output and operands
    * @return a new instance of Irfft3d
    */
@@ -121,4 +125,35 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Irfft3d<?>> {
+    /**
+     * A complex tensor.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * An int32 tensor of shape [3]. The FFT length for each dimension.
+     */
+    public final Operand<TInt32> fftLength;
+
+    /**
+     * The Treal attribute
+     */
+    public final DataType Treal;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Irfft3d<>(op), op, Arrays.asList("Treal", "Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      fftLength = (Operand<TInt32>) op.input(inputIndex++);
+      Treal = op.attributes().getAttrType("Treal");
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java
index 7fcf1e8931c..aaecb285947 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -66,7 +70,7 @@ private Rfft(Operation operation) {
    * @param scope current scope
    * @param input A float32 tensor.
    * @param fftLength An int32 tensor of shape [1]. The FFT length.
-   * @param Tcomplex the value of the Tcomplex property
+   * @param Tcomplex The value of the Tcomplex attribute
    * @param <U> data type for {@code RFFT} output and operands
    * @return a new instance of Rfft
    */
@@ -100,4 +104,35 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Rfft<?>> {
+    /**
+     * A float32 tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * An int32 tensor of shape [1]. The FFT length.
+     */
+    public final Operand<TInt32> fftLength;
+
+    /**
+     * The Treal attribute
+     */
+    public final DataType Treal;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Rfft<>(op), op, Arrays.asList("Treal", "Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      fftLength = (Operand<TInt32>) op.input(inputIndex++);
+      Treal = op.attributes().getAttrType("Treal");
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java
index 786c0be03b0..1fc337c853f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -67,7 +71,7 @@ private Rfft2d(Operation operation) {
    * @param scope current scope
    * @param input A float32 tensor.
    * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension.
-   * @param Tcomplex the value of the Tcomplex property
+   * @param Tcomplex The value of the Tcomplex attribute
    * @param <U> data type for {@code RFFT2D} output and operands
    * @return a new instance of Rfft2d
    */
@@ -102,4 +106,35 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Rfft2d<?>> {
+    /**
+     * A float32 tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * An int32 tensor of shape [2]. The FFT length for each dimension.
+     */
+    public final Operand<TInt32> fftLength;
+
+    /**
+     * The Treal attribute
+     */
+    public final DataType Treal;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Rfft2d<>(op), op, Arrays.asList("Treal", "Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      fftLength = (Operand<TInt32>) op.input(inputIndex++);
+      Treal = op.attributes().getAttrType("Treal");
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java
index 180d73ea184..e10cc8b9879 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.signal;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -67,7 +71,7 @@ private Rfft3d(Operation operation) {
    * @param scope current scope
    * @param input A float32 tensor.
    * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension.
-   * @param Tcomplex the value of the Tcomplex property
+   * @param Tcomplex The value of the Tcomplex attribute
    * @param <U> data type for {@code RFFT3D} output and operands
    * @return a new instance of Rfft3d
    */
@@ -102,4 +106,35 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Rfft3d<?>> {
+    /**
+     * A float32 tensor.
+     */
+    public final Operand<? extends TNumber> input;
+
+    /**
+     * An int32 tensor of shape [3]. The FFT length for each dimension.
+     */
+    public final Operand<TInt32> fftLength;
+
+    /**
+     * The Treal attribute
+     */
+    public final DataType Treal;
+
+    /**
+     * The Tcomplex attribute
+     */
+    public final DataType Tcomplex;
+
+    public Inputs(GraphOperation op) {
+      super(new Rfft3d<>(op), op, Arrays.asList("Treal", "Tcomplex"));
+      int inputIndex = 0;
+      input = (Operand<? extends TNumber>) op.input(inputIndex++);
+      fftLength = (Operand<TInt32>) op.input(inputIndex++);
+      Treal = op.attributes().getAttrType("Treal");
+      Tcomplex = op.attributes().getAttrType("Tcomplex");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java
index 06ae4329408..7757774ace2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -170,4 +174,50 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AddManySparseToTensorsMap> {
+    /**
+     * 2-D.  The {@code indices} of the minibatch {@code SparseTensor}.
+     * {@code sparse_indices[:, 0]} must be ordered values in {@code [0, N)}.
+     */
+    public final Operand<TInt64> sparseIndices;
+
+    /**
+     * 1-D.  The {@code values} of the minibatch {@code SparseTensor}.
+     */
+    public final Operand<? extends TType> sparseValues;
+
+    /**
+     * 1-D.  The {@code shape} of the minibatch {@code SparseTensor}.
+     * The minibatch size {@code N == sparse_shape[0]}.
+     */
+    public final Operand<TInt64> sparseShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The container name for the `SparseTensorsMap` created by this op.
+     */
+    public final String container;
+
+    /**
+     * The shared name for the `SparseTensorsMap` created by this op.
+     * If blank, the new Operation's unique name is used.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new AddManySparseToTensorsMap(op), op, Arrays.asList("T", "container", "shared_name"));
+      int inputIndex = 0;
+      sparseIndices = (Operand<TInt64>) op.input(inputIndex++);
+      sparseValues = (Operand<? extends TType>) op.input(inputIndex++);
+      sparseShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java
index 32450a5d1d3..8a68e68e4ca 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -162,4 +166,48 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AddSparseToTensorsMap> {
+    /**
+     * 2-D.  The {@code indices} of the {@code SparseTensor}.
+     */
+    public final Operand<TInt64> sparseIndices;
+
+    /**
+     * 1-D.  The {@code values} of the {@code SparseTensor}.
+     */
+    public final Operand<? extends TType> sparseValues;
+
+    /**
+     * 1-D.  The {@code shape} of the {@code SparseTensor}.
+     */
+    public final Operand<TInt64> sparseShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The container name for the `SparseTensorsMap` created by this op.
+     */
+    public final String container;
+
+    /**
+     * The shared name for the `SparseTensorsMap` created by this op.
+     * If blank, the new Operation's unique name is used.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new AddSparseToTensorsMap(op), op, Arrays.asList("T", "container", "shared_name"));
+      int inputIndex = 0;
+      sparseIndices = (Operand<TInt64>) op.input(inputIndex++);
+      sparseValues = (Operand<? extends TType>) op.input(inputIndex++);
+      sparseShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java
index 20cc808c8a1..a83f853daac 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -168,4 +172,54 @@ public Options maxlength(Long maxlength) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<DenseCountSparseOutput<U>> {
+    /**
+     * Tensor containing data to count.
+     */
+    public final Operand<? extends TNumber> values;
+
+    /**
+     * A Tensor of the same shape as indices containing per-index weight values. May
+     * also be the empty tensor if no weights are used.
+     */
+    public final Operand<U> weights;
+
+    /**
+     * Dtype of the input values tensor.
+     */
+    public final DataType T;
+
+    /**
+     * Minimum value to count. Can be set to -1 for no minimum.
+     */
+    public final long minlength;
+
+    /**
+     * Maximum value to count. Can be set to -1 for no maximum.
+     */
+    public final long maxlength;
+
+    /**
+     * Whether to output the number of occurrences of each value or 1.
+     */
+    public final boolean binaryOutput;
+
+    /**
+     * Dtype of the output values tensor.
+     */
+    public final DataType outputType;
+
+    public Inputs(GraphOperation op) {
+      super(new DenseCountSparseOutput<>(op), op, Arrays.asList("T", "minlength", "maxlength", "binary_output", "output_type"));
+      int inputIndex = 0;
+      values = (Operand<? extends TNumber>) op.input(inputIndex++);
+      weights = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      minlength = op.attributes().getAttrInt("minlength");
+      maxlength = op.attributes().getAttrInt("maxlength");
+      binaryOutput = op.attributes().getAttrBool("binary_output");
+      outputType = op.attributes().getAttrType("output_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java
index 7ef4cdef3ba..ea896eac86f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -70,7 +74,7 @@ private DenseToDenseSetOperation(Operation operation) {
    * Dimension {@code n} contains values in a set, duplicates are allowed but ignored.
    * @param set2 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set1}.
    * Dimension {@code n} contains values in a set, duplicates are allowed but ignored.
-   * @param setOperation the value of the setOperation property
+   * @param setOperation The value of the setOperation attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DenseToDenseSetOperation} output and operands
    * @return a new instance of DenseToDenseSetOperation
@@ -153,4 +157,43 @@ public Options validateIndices(Boolean validateIndices) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DenseToDenseSetOperation<T>> {
+    /**
+     * {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set2}.
+     * Dimension {@code n} contains values in a set, duplicates are allowed but ignored.
+     */
+    public final Operand<T> set1;
+
+    /**
+     * {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set1}.
+     * Dimension {@code n} contains values in a set, duplicates are allowed but ignored.
+     */
+    public final Operand<T> set2;
+
+    /**
+     * The setOperation attribute
+     */
+    public final String setOperation;
+
+    /**
+     * The validateIndices attribute
+     */
+    public final boolean validateIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DenseToDenseSetOperation<>(op), op, Arrays.asList("set_operation", "validate_indices", "T"));
+      int inputIndex = 0;
+      set1 = (Operand<T>) op.input(inputIndex++);
+      set2 = (Operand<T>) op.input(inputIndex++);
+      setOperation = op.attributes().getAttrString("set_operation");
+      validateIndices = op.attributes().getAttrBool("validate_indices");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java
index 6afc0248772..6cf1c374394 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -81,7 +85,7 @@ private DenseToSparseSetOperation(Operation operation) {
    * @param set2Shape 1D {@code Tensor}, shape of a {@code SparseTensor}. {@code set2_shape[0...n-1]} must
    * be the same as the 1st {@code n-1} dimensions of {@code set1}, {@code result_shape[n]} is the
    * max set size across {@code n-1} dimensions.
-   * @param setOperation the value of the setOperation property
+   * @param setOperation The value of the setOperation attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code DenseToSparseSetOperation} output and operands
    * @return a new instance of DenseToSparseSetOperation
@@ -167,4 +171,58 @@ public Options validateIndices(Boolean validateIndices) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DenseToSparseSetOperation<T>> {
+    /**
+     * {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set2}.
+     * Dimension {@code n} contains values in a set, duplicates are allowed but ignored.
+     */
+    public final Operand<T> set1;
+
+    /**
+     * 2D {@code Tensor}, indices of a {@code SparseTensor}. Must be in row-major
+     * order.
+     */
+    public final Operand<TInt64> set2Indices;
+
+    /**
+     * 1D {@code Tensor}, values of a {@code SparseTensor}. Must be in row-major
+     * order.
+     */
+    public final Operand<T> set2Values;
+
+    /**
+     * 1D {@code Tensor}, shape of a {@code SparseTensor}. {@code set2_shape[0...n-1]} must
+     * be the same as the 1st {@code n-1} dimensions of {@code set1}, {@code result_shape[n]} is the
+     * max set size across {@code n-1} dimensions.
+     */
+    public final Operand<TInt64> set2Shape;
+
+    /**
+     * The setOperation attribute
+     */
+    public final String setOperation;
+
+    /**
+     * The validateIndices attribute
+     */
+    public final boolean validateIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new DenseToSparseSetOperation<>(op), op, Arrays.asList("set_operation", "validate_indices", "T"));
+      int inputIndex = 0;
+      set1 = (Operand<T>) op.input(inputIndex++);
+      set2Indices = (Operand<TInt64>) op.input(inputIndex++);
+      set2Values = (Operand<T>) op.input(inputIndex++);
+      set2Shape = (Operand<TInt64>) op.input(inputIndex++);
+      setOperation = op.attributes().getAttrString("set_operation");
+      validateIndices = op.attributes().getAttrBool("validate_indices");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java
index a57326729d1..837e8db112b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -143,4 +147,30 @@ public Output<U> sparseValues() {
   public Output<TInt64> sparseShape() {
     return sparseShape;
   }
+
+  public static class Inputs extends RawOpInputs<DeserializeSparse<?>> {
+    /**
+     * The serialized {@code SparseTensor} objects. The last dimension
+     * must have 3 columns.
+     */
+    public final Operand<? extends TType> serializedSparse;
+
+    /**
+     * The `dtype` of the serialized `SparseTensor` objects.
+     */
+    public final DataType dtype;
+
+    /**
+     * The Tserialized attribute
+     */
+    public final DataType Tserialized;
+
+    public Inputs(GraphOperation op) {
+      super(new DeserializeSparse<>(op), op, Arrays.asList("dtype", "Tserialized"));
+      int inputIndex = 0;
+      serializedSparse = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      Tserialized = op.attributes().getAttrType("Tserialized");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorApplyGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorApplyGradient.java
index 98d092850d7..8496ad6a614 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorApplyGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorApplyGradient.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -78,4 +82,58 @@ public static SparseAccumulatorApplyGradient create(Scope scope, Operand<TString
     opBuilder.setAttr("has_known_shape", hasKnownShape);
     return new SparseAccumulatorApplyGradient(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<SparseAccumulatorApplyGradient> {
+    /**
+     * The handle to a accumulator.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * The local_step value at which the sparse gradient was computed.
+     */
+    public final Operand<TInt64> localStep;
+
+    /**
+     * Indices of the sparse gradient to be accumulated. Must be a
+     * vector.
+     */
+    public final Operand<TInt64> gradientIndices;
+
+    /**
+     * Values are the non-zero slices of the gradient, and must have
+     * the same first dimension as indices, i.e., the nnz represented by indices and
+     * values must be consistent.
+     */
+    public final Operand<? extends TType> gradientValues;
+
+    /**
+     * Shape of the sparse gradient to be accumulated.
+     */
+    public final Operand<TInt64> gradientShape;
+
+    /**
+     * The data type of accumulated gradients. Needs to correspond to the type
+     * of the accumulator.
+     */
+    public final DataType dtype;
+
+    /**
+     * Boolean indicating whether gradient_shape is unknown, in which
+     * case the input is ignored during validation.
+     */
+    public final boolean hasKnownShape;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseAccumulatorApplyGradient(op), op, Arrays.asList("dtype", "has_known_shape"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      localStep = (Operand<TInt64>) op.input(inputIndex++);
+      gradientIndices = (Operand<TInt64>) op.input(inputIndex++);
+      gradientValues = (Operand<? extends TType>) op.input(inputIndex++);
+      gradientShape = (Operand<TInt64>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      hasKnownShape = op.attributes().getAttrBool("has_known_shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java
index 1e82f4bef9a..f1558dd83d4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -114,4 +118,30 @@ public Output<T> values() {
   public Output<TInt64> shape() {
     return shape;
   }
+
+  public static class Inputs extends RawOpInputs<SparseAccumulatorTakeGradient<?>> {
+    /**
+     * The handle to a SparseConditionalAccumulator.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * Number of gradients required before we return an aggregate.
+     */
+    public final Operand<TInt32> numRequired;
+
+    /**
+     * The data type of accumulated gradients. Needs to correspond to the type
+     * of the accumulator.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseAccumulatorTakeGradient<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      numRequired = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java
index 792e1101808..8e372cacf9b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -126,4 +130,66 @@ public Output<T> sumValues() {
   public Output<TInt64> sumShape() {
     return sumShape;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseAdd<T>> {
+    /**
+     * 2-D.  The {@code indices} of the first {@code SparseTensor}, size {@code [nnz, ndims]} Matrix.
+     */
+    public final Operand<TInt64> aIndices;
+
+    /**
+     * 1-D.  The {@code values} of the first {@code SparseTensor}, size {@code [nnz]} Vector.
+     */
+    public final Operand<T> aValues;
+
+    /**
+     * 1-D.  The {@code shape} of the first {@code SparseTensor}, size {@code [ndims]} Vector.
+     */
+    public final Operand<TInt64> aShape;
+
+    /**
+     * 2-D.  The {@code indices} of the second {@code SparseTensor}, size {@code [nnz, ndims]} Matrix.
+     */
+    public final Operand<TInt64> bIndices;
+
+    /**
+     * 1-D.  The {@code values} of the second {@code SparseTensor}, size {@code [nnz]} Vector.
+     */
+    public final Operand<T> bValues;
+
+    /**
+     * 1-D.  The {@code shape} of the second {@code SparseTensor}, size {@code [ndims]} Vector.
+     */
+    public final Operand<TInt64> bShape;
+
+    /**
+     * 0-D.  The magnitude threshold that determines if an output value/index
+     * pair takes space.
+     */
+    public final Operand<? extends TNumber> thresh;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Treal attribute
+     */
+    public final DataType Treal;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseAdd<>(op), op, Arrays.asList("T", "Treal"));
+      int inputIndex = 0;
+      aIndices = (Operand<TInt64>) op.input(inputIndex++);
+      aValues = (Operand<T>) op.input(inputIndex++);
+      aShape = (Operand<TInt64>) op.input(inputIndex++);
+      bIndices = (Operand<TInt64>) op.input(inputIndex++);
+      bValues = (Operand<T>) op.input(inputIndex++);
+      bShape = (Operand<TInt64>) op.input(inputIndex++);
+      thresh = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Treal = op.attributes().getAttrType("Treal");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java
index e88a90c5e92..c99dd5a7a08 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -102,4 +106,43 @@ public Output<T> aValGrad() {
   public Output<T> bValGrad() {
     return bValGrad;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseAddGrad<T>> {
+    /**
+     * 1-D with shape {@code [nnz(sum)]}.  The gradient with respect to
+     * the non-empty values of the sum.
+     */
+    public final Operand<T> backpropValGrad;
+
+    /**
+     * 2-D.  The {@code indices} of the {@code SparseTensor} A, size {@code [nnz(A), ndims]}.
+     */
+    public final Operand<TInt64> aIndices;
+
+    /**
+     * 2-D.  The {@code indices} of the {@code SparseTensor} B, size {@code [nnz(B), ndims]}.
+     */
+    public final Operand<TInt64> bIndices;
+
+    /**
+     * 2-D.  The {@code indices} of the sum {@code SparseTensor}, size
+     * {@code [nnz(sum), ndims]}.
+     */
+    public final Operand<TInt64> sumIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseAddGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      backpropValGrad = (Operand<T>) op.input(inputIndex++);
+      aIndices = (Operand<TInt64>) op.input(inputIndex++);
+      bIndices = (Operand<TInt64>) op.input(inputIndex++);
+      sumIndices = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java
index b13f2f043d3..6064e201455 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -139,4 +143,61 @@ public Options binaryOutput(Boolean binaryOutput) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TNumber> extends RawOpInputs<SparseBincount<U>> {
+    /**
+     * 2D int64 {@code Tensor}.
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * 1D int {@code Tensor}.
+     */
+    public final Operand<T> values;
+
+    /**
+     * 1D int64 {@code Tensor}.
+     */
+    public final Operand<TInt64> denseShape;
+
+    /**
+     * non-negative int scalar {@code Tensor}.
+     */
+    public final Operand<T> sizeOutput;
+
+    /**
+     * is an int32, int64, float32, or float64 {@code Tensor} with the same
+     * shape as {@code input}, or a length-0 {@code Tensor}, in which case it acts as all weights
+     * equal to 1.
+     */
+    public final Operand<U> weights;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * bool; Whether the kernel should count the appearance or number of occurrences.
+     */
+    public final boolean binaryOutput;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseBincount<>(op), op, Arrays.asList("Tidx", "T", "binary_output"));
+      int inputIndex = 0;
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<T>) op.input(inputIndex++);
+      denseShape = (Operand<TInt64>) op.input(inputIndex++);
+      sizeOutput = (Operand<T>) op.input(inputIndex++);
+      weights = (Operand<U>) op.input(inputIndex++);
+      Tidx = op.attributes().getAttrType("Tidx");
+      T = op.attributes().getAttrType("T");
+      binaryOutput = op.attributes().getAttrBool("binary_output");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java
index 4b4f2aad88e..d35c0837991 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -146,4 +150,48 @@ public Output<T> outputValues() {
   public Output<TInt64> outputShape() {
     return outputShape;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseConcat<T>> {
+    /**
+     * 2-D.  Indices of each input {@code SparseTensor}.
+     */
+    public final Iterable<Operand<TInt64>> indices;
+
+    /**
+     * 1-D.  Non-empty values of each {@code SparseTensor}.
+     */
+    public final Iterable<Operand<T>> values;
+
+    /**
+     * 1-D.  Shapes of each {@code SparseTensor}.
+     */
+    public final Iterable<Operand<TInt64>> shapes;
+
+    /**
+     * Dimension to concatenate along. Must be in range [-rank, rank),
+     * where rank is the number of dimensions in each input `SparseTensor`.
+     */
+    public final long concatDim;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseConcat<>(op), op, Arrays.asList("concat_dim", "T"));
+      int inputIndex = 0;
+      int indicesLength = op.inputListLength("indices");
+      indices = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, indicesLength));
+      inputIndex += indicesLength;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      int shapesLength = op.inputListLength("shapes");
+      shapes = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, shapesLength));
+      inputIndex += shapesLength;
+      concatDim = op.attributes().getAttrInt("concat_dim");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java
index 42b9e9795e9..7ddc90749d9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -184,4 +188,43 @@ public Options reductionType(String reductionType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SparseConditionalAccumulator> {
+    /**
+     * The type of the value being accumulated.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the values.
+     */
+    public final Shape shape;
+
+    /**
+     * If non-empty, this accumulator is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this accumulator will be shared under the given name
+     * across multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * The reductionType attribute
+     */
+    public final String reductionType;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseConditionalAccumulator(op), op, Arrays.asList("dtype", "shape", "container", "shared_name", "reduction_type"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      reductionType = op.attributes().getAttrString("reduction_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java
index f5a952335fa..bee78d51b23 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -172,4 +176,66 @@ public Options maxlength(Long maxlength) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TNumber> extends RawOpInputs<SparseCountSparseOutput<U>> {
+    /**
+     * Tensor containing the indices of the sparse tensor to count.
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * Tensor containing values of the sparse tensor to count.
+     */
+    public final Operand<? extends TNumber> values;
+
+    /**
+     * Tensor containing the dense shape of the sparse tensor to count.
+     */
+    public final Operand<TInt64> denseShape;
+
+    /**
+     * A Tensor of the same shape as indices containing per-index weight values.
+     * May also be the empty tensor if no weights are used.
+     */
+    public final Operand<U> weights;
+
+    /**
+     * Dtype of the input values tensor.
+     */
+    public final DataType T;
+
+    /**
+     * Minimum value to count. Can be set to -1 for no minimum.
+     */
+    public final long minlength;
+
+    /**
+     * Maximum value to count. Can be set to -1 for no maximum.
+     */
+    public final long maxlength;
+
+    /**
+     * Whether to output the number of occurrences of each value or 1.
+     */
+    public final boolean binaryOutput;
+
+    /**
+     * Dtype of the output values tensor.
+     */
+    public final DataType outputType;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseCountSparseOutput<>(op), op, Arrays.asList("T", "minlength", "maxlength", "binary_output", "output_type"));
+      int inputIndex = 0;
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<? extends TNumber>) op.input(inputIndex++);
+      denseShape = (Operand<TInt64>) op.input(inputIndex++);
+      weights = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      minlength = op.attributes().getAttrInt("minlength");
+      maxlength = op.attributes().getAttrInt("maxlength");
+      binaryOutput = op.attributes().getAttrBool("binary_output");
+      outputType = op.attributes().getAttrType("output_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCross.java
index 30fc19a5315..0208d01c554 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCross.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCross.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 
@@ -144,4 +148,61 @@ public Output<TString> outputValues() {
   public Output<TInt64> outputShape() {
     return outputShape;
   }
+
+  public static class Inputs extends RawOpInputs<SparseCross> {
+    /**
+     * 2-D.  Indices of each input {@code SparseTensor}.
+     */
+    public final Iterable<Operand<TInt64>> indices;
+
+    /**
+     * 1-D.   values of each {@code SparseTensor}.
+     */
+    public final Iterable<Operand<?>> values;
+
+    /**
+     * 1-D.   Shapes of each {@code SparseTensor}.
+     */
+    public final Iterable<Operand<TInt64>> shapes;
+
+    /**
+     * 2-D.    Columns represented by dense {@code Tensor}.
+     */
+    public final Iterable<Operand<?>> denseInputs;
+
+    /**
+     * string used when joining a list of string inputs, can be used as separator later.
+     */
+    public final Operand<TString> sep;
+
+    /**
+     * The sparseTypes attribute
+     */
+    public final DataType[] sparseTypes;
+
+    /**
+     * The denseTypes attribute
+     */
+    public final DataType[] denseTypes;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseCross(op), op, Arrays.asList("sparse_types", "dense_types"));
+      int inputIndex = 0;
+      int indicesLength = op.inputListLength("indices");
+      indices = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, indicesLength));
+      inputIndex += indicesLength;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      int shapesLength = op.inputListLength("shapes");
+      shapes = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, shapesLength));
+      inputIndex += shapesLength;
+      int denseInputsLength = op.inputListLength("dense_inputs");
+      denseInputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, denseInputsLength));
+      inputIndex += denseInputsLength;
+      sep = (Operand<TString>) op.input(inputIndex++);
+      sparseTypes = op.attributes().getAttrTypeList("sparse_types");
+      denseTypes = op.attributes().getAttrTypeList("dense_types");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCrossHashed.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCrossHashed.java
index 93e93fe4531..af73abe7e8d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCrossHashed.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCrossHashed.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 
@@ -150,4 +154,74 @@ public Output<TInt64> outputValues() {
   public Output<TInt64> outputShape() {
     return outputShape;
   }
+
+  public static class Inputs extends RawOpInputs<SparseCrossHashed> {
+    /**
+     * 2-D.  Indices of each input {@code SparseTensor}.
+     */
+    public final Iterable<Operand<TInt64>> indices;
+
+    /**
+     * 1-D.   values of each {@code SparseTensor}.
+     */
+    public final Iterable<Operand<?>> values;
+
+    /**
+     * 1-D.   Shapes of each {@code SparseTensor}.
+     */
+    public final Iterable<Operand<TInt64>> shapes;
+
+    /**
+     * 2-D.    Columns represented by dense {@code Tensor}.
+     */
+    public final Iterable<Operand<?>> denseInputs;
+
+    /**
+     * It is used if hashed_output is true.
+     * output = hashed_value%num_buckets if num_buckets &gt; 0 else hashed_value.
+     */
+    public final Operand<TInt64> numBuckets;
+
+    /**
+     * boolean, if true, siphash with salt will be used instead of farmhash.
+     */
+    public final Operand<TBool> strongHash;
+
+    /**
+     * Specify the salt that will be used by the siphash function.
+     */
+    public final Operand<TInt64> salt;
+
+    /**
+     * The sparseTypes attribute
+     */
+    public final DataType[] sparseTypes;
+
+    /**
+     * The denseTypes attribute
+     */
+    public final DataType[] denseTypes;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseCrossHashed(op), op, Arrays.asList("sparse_types", "dense_types"));
+      int inputIndex = 0;
+      int indicesLength = op.inputListLength("indices");
+      indices = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, indicesLength));
+      inputIndex += indicesLength;
+      int valuesLength = op.inputListLength("values");
+      values = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, valuesLength));
+      inputIndex += valuesLength;
+      int shapesLength = op.inputListLength("shapes");
+      shapes = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, shapesLength));
+      inputIndex += shapesLength;
+      int denseInputsLength = op.inputListLength("dense_inputs");
+      denseInputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, denseInputsLength));
+      inputIndex += denseInputsLength;
+      numBuckets = (Operand<TInt64>) op.input(inputIndex++);
+      strongHash = (Operand<TBool>) op.input(inputIndex++);
+      salt = (Operand<TInt64>) op.input(inputIndex++);
+      sparseTypes = op.attributes().getAttrTypeList("sparse_types");
+      denseTypes = op.attributes().getAttrTypeList("dense_types");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java
index 96911d81a5d..9f2e841c0a1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -95,4 +99,42 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseDenseCwiseAdd<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> spIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code sp_indices}.
+     */
+    public final Operand<T> spValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> spShape;
+
+    /**
+     * {@code R}-D.  The dense Tensor operand.
+     */
+    public final Operand<T> dense;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseDenseCwiseAdd<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      spIndices = (Operand<TInt64>) op.input(inputIndex++);
+      spValues = (Operand<T>) op.input(inputIndex++);
+      spShape = (Operand<TInt64>) op.input(inputIndex++);
+      dense = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java
index dabb95c94f4..9b519b392ca 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -90,4 +94,42 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseDenseCwiseDiv<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> spIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code sp_indices}.
+     */
+    public final Operand<T> spValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> spShape;
+
+    /**
+     * {@code R}-D.  The dense Tensor operand.
+     */
+    public final Operand<T> dense;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseDenseCwiseDiv<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      spIndices = (Operand<TInt64>) op.input(inputIndex++);
+      spValues = (Operand<T>) op.input(inputIndex++);
+      spShape = (Operand<TInt64>) op.input(inputIndex++);
+      dense = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java
index 046426ce0c4..f316405eb7f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -93,4 +97,42 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseDenseCwiseMul<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> spIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code sp_indices}.
+     */
+    public final Operand<T> spValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> spShape;
+
+    /**
+     * {@code R}-D.  The dense Tensor operand.
+     */
+    public final Operand<T> dense;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseDenseCwiseMul<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      spIndices = (Operand<TInt64>) op.input(inputIndex++);
+      spValues = (Operand<T>) op.input(inputIndex++);
+      spShape = (Operand<TInt64>) op.input(inputIndex++);
+      dense = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java
index 1f22702059e..6473358aad6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -157,4 +161,43 @@ public Output<TBool> emptyRowIndicator() {
   public Output<TInt64> reverseIndexMap() {
     return reverseIndexMap;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseFillEmptyRows<T>> {
+    /**
+     * 2-D. the indices of the sparse tensor.
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * 1-D. the values of the sparse tensor.
+     */
+    public final Operand<T> values;
+
+    /**
+     * 1-D. the shape of the sparse tensor.
+     */
+    public final Operand<TInt64> denseShape;
+
+    /**
+     * 0-D. default value to insert into location {@code [row, 0, ..., 0]}
+     * for rows missing from the input sparse tensor.
+     * output indices: 2-D. the indices of the filled sparse tensor.
+     */
+    public final Operand<T> defaultValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseFillEmptyRows<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<T>) op.input(inputIndex++);
+      denseShape = (Operand<TInt64>) op.input(inputIndex++);
+      defaultValue = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java
index bd262ebb278..94f5033d574 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -97,4 +101,29 @@ public Output<T> dValues() {
   public Output<T> dDefaultValue() {
     return dDefaultValue;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseFillEmptyRowsGrad<T>> {
+    /**
+     * 1-D.  The reverse index map from SparseFillEmptyRows.
+     */
+    public final Operand<TInt64> reverseIndexMap;
+
+    /**
+     * 1-D.  The gradients from backprop.
+     */
+    public final Operand<T> gradValues;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseFillEmptyRowsGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      reverseIndexMap = (Operand<TInt64>) op.input(inputIndex++);
+      gradValues = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java
index b913561a039..8c9388a0aaa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
 
@@ -60,8 +64,8 @@ private SparseMatMul(Operation operation) {
    * Factory method to create a class wrapping a new SparseMatMul operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param b the b value
+   * @param a The a value
+   * @param b The b value
    * @param options carries optional attribute values
    * @return a new instance of SparseMatMul
    */
@@ -205,4 +209,59 @@ public Options bIsSparse(Boolean bIsSparse) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SparseMatMul> {
+    /**
+     * The a input
+     */
+    public final Operand<? extends TNumber> a;
+
+    /**
+     * The b input
+     */
+    public final Operand<? extends TNumber> b;
+
+    /**
+     * The transposeA attribute
+     */
+    public final boolean transposeA;
+
+    /**
+     * The transposeB attribute
+     */
+    public final boolean transposeB;
+
+    /**
+     * The aIsSparse attribute
+     */
+    public final boolean aIsSparse;
+
+    /**
+     * The bIsSparse attribute
+     */
+    public final boolean bIsSparse;
+
+    /**
+     * The Ta attribute
+     */
+    public final DataType Ta;
+
+    /**
+     * The Tb attribute
+     */
+    public final DataType Tb;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseMatMul(op), op, Arrays.asList("transpose_a", "transpose_b", "a_is_sparse", "b_is_sparse", "Ta", "Tb"));
+      int inputIndex = 0;
+      a = (Operand<? extends TNumber>) op.input(inputIndex++);
+      b = (Operand<? extends TNumber>) op.input(inputIndex++);
+      transposeA = op.attributes().getAttrBool("transpose_a");
+      transposeB = op.attributes().getAttrBool("transpose_b");
+      aIsSparse = op.attributes().getAttrBool("a_is_sparse");
+      bIsSparse = op.attributes().getAttrBool("b_is_sparse");
+      Ta = op.attributes().getAttrType("Ta");
+      Tb = op.attributes().getAttrType("Tb");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java
index 534e256d548..989e3f5c48a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
@@ -139,4 +143,48 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseReduceMax<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> inputIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code input_indices}.
+     */
+    public final Operand<T> inputValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> inputShape;
+
+    /**
+     * 1-D.  Length-{@code K} vector containing the reduction axes.
+     */
+    public final Operand<TInt32> reductionAxes;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseReduceMax<>(op), op, Arrays.asList("keep_dims", "T"));
+      int inputIndex = 0;
+      inputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      inputValues = (Operand<T>) op.input(inputIndex++);
+      inputShape = (Operand<TInt64>) op.input(inputIndex++);
+      reductionAxes = (Operand<TInt32>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java
index 075937687d8..5ec12e79fa4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
@@ -158,4 +162,48 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseReduceMaxSparse<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> inputIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code input_indices}.
+     */
+    public final Operand<T> inputValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> inputShape;
+
+    /**
+     * 1-D.  Length-{@code K} vector containing the reduction axes.
+     */
+    public final Operand<TInt32> reductionAxes;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseReduceMaxSparse<>(op), op, Arrays.asList("keep_dims", "T"));
+      int inputIndex = 0;
+      inputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      inputValues = (Operand<T>) op.input(inputIndex++);
+      inputShape = (Operand<TInt64>) op.input(inputIndex++);
+      reductionAxes = (Operand<TInt32>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java
index b3e4e20e8c0..f81a5eff0cf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -139,4 +143,48 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseReduceSum<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> inputIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code input_indices}.
+     */
+    public final Operand<T> inputValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> inputShape;
+
+    /**
+     * 1-D.  Length-{@code K} vector containing the reduction axes.
+     */
+    public final Operand<TInt32> reductionAxes;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseReduceSum<>(op), op, Arrays.asList("keep_dims", "T"));
+      int inputIndex = 0;
+      inputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      inputValues = (Operand<T>) op.input(inputIndex++);
+      inputShape = (Operand<TInt64>) op.input(inputIndex++);
+      reductionAxes = (Operand<TInt32>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java
index 20e3887bffa..e97e512582a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -158,4 +162,48 @@ public Options keepDims(Boolean keepDims) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseReduceSumSparse<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> inputIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code input_indices}.
+     */
+    public final Operand<T> inputValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> inputShape;
+
+    /**
+     * 1-D.  Length-{@code K} vector containing the reduction axes.
+     */
+    public final Operand<TInt32> reductionAxes;
+
+    /**
+     * If true, retain reduced dimensions with length 1.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseReduceSumSparse<>(op), op, Arrays.asList("keep_dims", "T"));
+      int inputIndex = 0;
+      inputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      inputValues = (Operand<T>) op.input(inputIndex++);
+      inputShape = (Operand<TInt64>) op.input(inputIndex++);
+      reductionAxes = (Operand<TInt32>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java
index b1b836e6563..4f3ef7a762a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -100,4 +104,36 @@ public Output<TInt64> outputIndices() {
   public Output<T> outputValues() {
     return outputValues;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseReorder<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, possibly not in canonical ordering.
+     */
+    public final Operand<TInt64> inputIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code input_indices}.
+     */
+    public final Operand<T> inputValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> inputShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseReorder<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      inputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      inputValues = (Operand<T>) op.input(inputIndex++);
+      inputShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReshape.java
index 59eedfde460..5b569b8ea6c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReshape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReshape.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -104,4 +107,30 @@ public Output<TInt64> outputIndices() {
   public Output<TInt64> outputShape() {
     return outputShape;
   }
+
+  public static class Inputs extends RawOpInputs<SparseReshape> {
+    /**
+     * 2-D.  {@code N x R_in} matrix with the indices of non-empty values in a
+     * SparseTensor.
+     */
+    public final Operand<TInt64> inputIndices;
+
+    /**
+     * 1-D.  {@code R_in} vector with the input SparseTensor's dense shape.
+     */
+    public final Operand<TInt64> inputShape;
+
+    /**
+     * 1-D.  {@code R_out} vector with the requested new dense shape.
+     */
+    public final Operand<TInt64> newShape;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseReshape(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      inputShape = (Operand<TInt64>) op.input(inputIndex++);
+      newShape = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java
index cfa2fadbd74..af9f65b4551 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -56,7 +60,7 @@ private SparseSegmentMean(Operation operation) {
    * Factory method to create a class wrapping a new SparseSegmentMean operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param <T> data type for {@code SparseSegmentMean} output and operands
@@ -88,4 +92,47 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentMean<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor. Has same rank as {@code segment_ids}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A 1-D tensor. Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentMean<>(op), op, Arrays.asList("T", "Tidx", "Tsegmentids"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java
index 25245eb2db0..80c3acc5da1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -90,4 +94,53 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentMeanGrad<T>> {
+    /**
+     * gradient propagated to the SparseSegmentMean op.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * indices passed to the corresponding SparseSegmentMean op.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * segment_ids passed to the corresponding SparseSegmentMean op.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * dimension 0 of &quot;data&quot; passed to SparseSegmentMean op.
+     */
+    public final Operand<TInt32> outputDim0;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentMeanGrad<>(op), op, Arrays.asList("T", "Tidx", "Tsegmentids"));
+      int inputIndex = 0;
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      outputDim0 = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java
index ddc60bd6065..8fe4f039b62 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -58,7 +62,7 @@ private SparseSegmentMeanWithNumSegments(Operation operation) {
    * Factory method to create a class wrapping a new SparseSegmentMeanWithNumSegments operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param numSegments Should equal the number of distinct segment IDs.
@@ -93,4 +97,59 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentMeanWithNumSegments<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor. Has same rank as {@code segment_ids}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A 1-D tensor. Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * Should equal the number of distinct segment IDs.
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentMeanWithNumSegments<>(op), op, Arrays.asList("T", "Tidx", "Tnumsegments", "Tsegmentids"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java
index 7834485434d..f5b0a967137 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -55,7 +59,7 @@ private SparseSegmentSqrtN(Operation operation) {
    * Factory method to create a class wrapping a new SparseSegmentSqrtN operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param <T> data type for {@code SparseSegmentSqrtN} output and operands
@@ -87,4 +91,47 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentSqrtN<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor. Has same rank as {@code segment_ids}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A 1-D tensor. Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentSqrtN<>(op), op, Arrays.asList("T", "Tidx", "Tsegmentids"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java
index b6e5b54277a..2b5d8e00ae1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -90,4 +94,53 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentSqrtNGrad<T>> {
+    /**
+     * gradient propagated to the SparseSegmentSqrtN op.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * indices passed to the corresponding SparseSegmentSqrtN op.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * segment_ids passed to the corresponding SparseSegmentSqrtN op.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * dimension 0 of &quot;data&quot; passed to SparseSegmentSqrtN op.
+     */
+    public final Operand<TInt32> outputDim0;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentSqrtNGrad<>(op), op, Arrays.asList("T", "Tidx", "Tsegmentids"));
+      int inputIndex = 0;
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      outputDim0 = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java
index 6bd3339813e..090732ab6e2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -59,7 +63,7 @@ private SparseSegmentSqrtNWithNumSegments(Operation operation) {
    * Factory method to create a class wrapping a new SparseSegmentSqrtNWithNumSegments operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param numSegments Should equal the number of distinct segment IDs.
@@ -94,4 +98,59 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentSqrtNWithNumSegments<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor. Has same rank as {@code segment_ids}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A 1-D tensor. Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * Should equal the number of distinct segment IDs.
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentSqrtNWithNumSegments<>(op), op, Arrays.asList("T", "Tidx", "Tnumsegments", "Tsegmentids"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java
index 13f9842bbfa..7c78dfd8392 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -79,7 +83,7 @@ private SparseSegmentSum(Operation operation) {
    * Factory method to create a class wrapping a new SparseSegmentSum operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param <T> data type for {@code SparseSegmentSum} output and operands
@@ -111,4 +115,47 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentSum<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor. Has same rank as {@code segment_ids}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A 1-D tensor. Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentSum<>(op), op, Arrays.asList("T", "Tidx", "Tsegmentids"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java
index c82f3dbab2e..3689868f892 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -90,4 +94,53 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentSumGrad<T>> {
+    /**
+     * gradient propagated to the SparseSegmentSum op.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * indices passed to the corresponding SparseSegmentSum op.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * segment_ids passed to the corresponding SparseSegmentSum op.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * dimension 0 of &quot;data&quot; passed to SparseSegmentSum op.
+     */
+    public final Operand<TInt32> outputDim0;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentSumGrad<>(op), op, Arrays.asList("T", "Tidx", "Tsegmentids"));
+      int inputIndex = 0;
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      outputDim0 = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java
index d67e08a73e5..45c84027eec 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 
 /**
@@ -77,7 +81,7 @@ private SparseSegmentSumWithNumSegments(Operation operation) {
    * Factory method to create a class wrapping a new SparseSegmentSumWithNumSegments operation.
    *
    * @param scope current scope
-   * @param data the data value
+   * @param data The data value
    * @param indices A 1-D tensor. Has same rank as {@code segment_ids}.
    * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated.
    * @param numSegments Should equal the number of distinct segment IDs.
@@ -112,4 +116,59 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSegmentSumWithNumSegments<T>> {
+    /**
+     * The data input
+     */
+    public final Operand<T> data;
+
+    /**
+     * A 1-D tensor. Has same rank as {@code segment_ids}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * A 1-D tensor. Values should be sorted and can be repeated.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * Should equal the number of distinct segment IDs.
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tidx attribute
+     */
+    public final DataType Tidx;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    /**
+     * The Tsegmentids attribute
+     */
+    public final DataType Tsegmentids;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSegmentSumWithNumSegments<>(op), op, Arrays.asList("T", "Tidx", "Tnumsegments", "Tsegmentids"));
+      int inputIndex = 0;
+      data = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tidx = op.attributes().getAttrType("Tidx");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+      Tsegmentids = op.attributes().getAttrType("Tsegmentids");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java
index 3afe4ce5fa7..881d26ef94c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -128,4 +132,49 @@ public Output<T> outputValues() {
   public Output<TInt64> outputShape() {
     return outputShape;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseSlice<T>> {
+    /**
+     * 2-D tensor represents the indices of the sparse tensor.
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * 1-D tensor represents the values of the sparse tensor.
+     */
+    public final Operand<T> values;
+
+    /**
+     * 1-D. tensor represents the shape of the sparse tensor.
+     */
+    public final Operand<TInt64> shape;
+
+    /**
+     * 1-D. tensor represents the start of the slice.
+     */
+    public final Operand<TInt64> start;
+
+    /**
+     * 1-D. tensor represents the size of the slice.
+     * output indices: A list of 1-D tensors represents the indices of the output
+     * sparse tensors.
+     */
+    public final Operand<TInt64> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSlice<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<T>) op.input(inputIndex++);
+      shape = (Operand<TInt64>) op.input(inputIndex++);
+      start = (Operand<TInt64>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java
index 3e1fc4a3eae..0899e873513 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -91,4 +95,42 @@ public Output<T> valGrad() {
   public Output<T> asOutput() {
     return valGrad;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseSliceGrad<T>> {
+    /**
+     * 1-D. The gradient with respect to
+     * the non-empty values of the sliced {@code SparseTensor}.
+     */
+    public final Operand<T> backpropValGrad;
+
+    /**
+     * 2-D.  The {@code indices} of the input {@code SparseTensor}.
+     */
+    public final Operand<TInt64> inputIndices;
+
+    /**
+     * 1-D. tensor represents the start of the slice.
+     */
+    public final Operand<TInt64> inputStart;
+
+    /**
+     * 2-D.  The {@code indices} of the sliced {@code SparseTensor}.
+     */
+    public final Operand<TInt64> outputIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSliceGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      backpropValGrad = (Operand<T>) op.input(inputIndex++);
+      inputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      inputStart = (Operand<TInt64>) op.input(inputIndex++);
+      outputIndices = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java
index 5259cdc9127..0cc01eeee58 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -98,4 +102,36 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSoftmax<T>> {
+    /**
+     * 2-D.  {@code NNZ x R} matrix with the indices of non-empty values in a
+     * SparseTensor, in canonical ordering.
+     */
+    public final Operand<TInt64> spIndices;
+
+    /**
+     * 1-D.  {@code NNZ} non-empty values corresponding to {@code sp_indices}.
+     */
+    public final Operand<T> spValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> spShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSoftmax<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      spIndices = (Operand<TInt64>) op.input(inputIndex++);
+      spValues = (Operand<T>) op.input(inputIndex++);
+      spShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java
index 166ae8dc7f2..6a36379bd8d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 
@@ -101,4 +105,54 @@ public Output<TInt64> outputIndices() {
   public Output<T> outputValues() {
     return outputValues;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<SparseSparseMaximum<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, in the canonical lexicographic ordering.
+     */
+    public final Operand<TInt64> aIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code a_indices}.
+     */
+    public final Operand<T> aValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> aShape;
+
+    /**
+     * counterpart to {@code a_indices} for the other operand.
+     */
+    public final Operand<TInt64> bIndices;
+
+    /**
+     * counterpart to {@code a_values} for the other operand; must be of the same dtype.
+     */
+    public final Operand<T> bValues;
+
+    /**
+     * counterpart to {@code a_shape} for the other operand; the two shapes must be equal.
+     */
+    public final Operand<TInt64> bShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSparseMaximum<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      aIndices = (Operand<TInt64>) op.input(inputIndex++);
+      aValues = (Operand<T>) op.input(inputIndex++);
+      aShape = (Operand<TInt64>) op.input(inputIndex++);
+      bIndices = (Operand<TInt64>) op.input(inputIndex++);
+      bValues = (Operand<T>) op.input(inputIndex++);
+      bShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java
index 01a9ceb7431..6a32e085cee 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -101,4 +105,54 @@ public Output<TInt64> outputIndices() {
   public Output<T> outputValues() {
     return outputValues;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseSparseMinimum<T>> {
+    /**
+     * 2-D.  {@code N x R} matrix with the indices of non-empty values in a
+     * SparseTensor, in the canonical lexicographic ordering.
+     */
+    public final Operand<TInt64> aIndices;
+
+    /**
+     * 1-D.  {@code N} non-empty values corresponding to {@code a_indices}.
+     */
+    public final Operand<T> aValues;
+
+    /**
+     * 1-D.  Shape of the input SparseTensor.
+     */
+    public final Operand<TInt64> aShape;
+
+    /**
+     * counterpart to {@code a_indices} for the other operand.
+     */
+    public final Operand<TInt64> bIndices;
+
+    /**
+     * counterpart to {@code a_values} for the other operand; must be of the same dtype.
+     */
+    public final Operand<T> bValues;
+
+    /**
+     * counterpart to {@code a_shape} for the other operand; the two shapes must be equal.
+     */
+    public final Operand<TInt64> bShape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSparseMinimum<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      aIndices = (Operand<TInt64>) op.input(inputIndex++);
+      aValues = (Operand<T>) op.input(inputIndex++);
+      aShape = (Operand<TInt64>) op.input(inputIndex++);
+      bIndices = (Operand<TInt64>) op.input(inputIndex++);
+      bValues = (Operand<T>) op.input(inputIndex++);
+      bShape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java
index 9154c405640..0b830e4441f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -140,4 +143,44 @@ public List<Output<T>> outputValues() {
   public List<Output<TInt64>> outputShape() {
     return outputShape;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseSplit<T>> {
+    /**
+     * 0-D.  The dimension along which to split.  Must be in the range
+     * {@code [0, rank(shape))}.
+     */
+    public final Operand<TInt64> splitDim;
+
+    /**
+     * 2-D tensor represents the indices of the sparse tensor.
+     */
+    public final Operand<TInt64> indices;
+
+    /**
+     * 1-D tensor represents the values of the sparse tensor.
+     */
+    public final Operand<T> values;
+
+    /**
+     * 1-D. tensor represents the shape of the sparse tensor.
+     * output indices: A list of 1-D tensors represents the indices of the output
+     * sparse tensors.
+     */
+    public final Operand<TInt64> shape;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseSplit<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      splitDim = (Operand<TInt64>) op.input(inputIndex++);
+      indices = (Operand<TInt64>) op.input(inputIndex++);
+      values = (Operand<T>) op.input(inputIndex++);
+      shape = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java
index d181580983d..e828e6476fb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -89,4 +93,47 @@ public Output<U> output() {
   public Output<U> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber, U extends TType> extends RawOpInputs<SparseTensorDenseAdd<U>> {
+    /**
+     * 2-D.  The {@code indices} of the {@code SparseTensor}, with shape {@code [nnz, ndims]}.
+     */
+    public final Operand<T> aIndices;
+
+    /**
+     * 1-D.  The {@code values} of the {@code SparseTensor}, with shape {@code [nnz]}.
+     */
+    public final Operand<U> aValues;
+
+    /**
+     * 1-D.  The {@code shape} of the {@code SparseTensor}, with shape {@code [ndims]}.
+     */
+    public final Operand<T> aShape;
+
+    /**
+     * {@code ndims}-D Tensor.  With shape {@code a_shape}.
+     */
+    public final Operand<U> b;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseTensorDenseAdd<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      aIndices = (Operand<T>) op.input(inputIndex++);
+      aValues = (Operand<U>) op.input(inputIndex++);
+      aShape = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java
index 346b2917327..559b82d90c5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -166,4 +170,61 @@ public Options adjointB(Boolean adjointB) {
       return this;
     }
   }
+
+  public static class Inputs<U extends TType> extends RawOpInputs<SparseTensorDenseMatMul<U>> {
+    /**
+     * 2-D.  The {@code indices} of the {@code SparseTensor}, size {@code [nnz, 2]} Matrix.
+     */
+    public final Operand<? extends TNumber> aIndices;
+
+    /**
+     * 1-D.  The {@code values} of the {@code SparseTensor}, size {@code [nnz]} Vector.
+     */
+    public final Operand<U> aValues;
+
+    /**
+     * 1-D.  The {@code shape} of the {@code SparseTensor}, size {@code [2]} Vector.
+     */
+    public final Operand<TInt64> aShape;
+
+    /**
+     * 2-D.  A dense Matrix.
+     */
+    public final Operand<U> b;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * Use the adjoint of A in the matrix multiply.  If A is complex, this
+     * is transpose(conj(A)).  Otherwise it's transpose(A).
+     */
+    public final boolean adjointA;
+
+    /**
+     * Use the adjoint of B in the matrix multiply.  If B is complex, this
+     * is transpose(conj(B)).  Otherwise it's transpose(B).
+     */
+    public final boolean adjointB;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseTensorDenseMatMul<>(op), op, Arrays.asList("T", "Tindices", "adjoint_a", "adjoint_b"));
+      int inputIndex = 0;
+      aIndices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      aValues = (Operand<U>) op.input(inputIndex++);
+      aShape = (Operand<TInt64>) op.input(inputIndex++);
+      b = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      adjointA = op.attributes().getAttrBool("adjoint_a");
+      adjointB = op.attributes().getAttrBool("adjoint_b");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java
index 63fed696d31..dac1f7569b9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -149,4 +153,57 @@ public Options validateIndices(Boolean validateIndices) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber, U extends TType> extends RawOpInputs<SparseToDense<U>> {
+    /**
+     * 0-D, 1-D, or 2-D.  {@code sparse_indices[i]} contains the complete
+     * index where {@code sparse_values[i]} will be placed.
+     */
+    public final Operand<T> sparseIndices;
+
+    /**
+     * 1-D.  Shape of the dense output tensor.
+     */
+    public final Operand<T> outputShape;
+
+    /**
+     * 1-D.  Values corresponding to each row of {@code sparse_indices},
+     * or a scalar value to be used for all sparse indices.
+     */
+    public final Operand<U> sparseValues;
+
+    /**
+     * Scalar value to set for indices not specified in
+     * {@code sparse_indices}.
+     */
+    public final Operand<U> defaultValue;
+
+    /**
+     * If true, indices are checked to make sure they are sorted in
+     * lexicographic order and that there are no repeats.
+     */
+    public final boolean validateIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseToDense<>(op), op, Arrays.asList("validate_indices", "T", "Tindices"));
+      int inputIndex = 0;
+      sparseIndices = (Operand<T>) op.input(inputIndex++);
+      outputShape = (Operand<T>) op.input(inputIndex++);
+      sparseValues = (Operand<U>) op.input(inputIndex++);
+      defaultValue = (Operand<U>) op.input(inputIndex++);
+      validateIndices = op.attributes().getAttrBool("validate_indices");
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java
index 1877c8cbed5..1d4ea083ad6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -92,7 +96,7 @@ private SparseToSparseSetOperation(Operation operation) {
    * @param set2Shape 1D {@code Tensor}, shape of a {@code SparseTensor}. {@code set2_shape[0...n-1]} must
    * be the same as {@code set1_shape[0...n-1]}, {@code set2_shape[n]} is the
    * max set size across {@code 0...n-1} dimensions.
-   * @param setOperation the value of the setOperation property
+   * @param setOperation The value of the setOperation attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code SparseToSparseSetOperation} output and operands
    * @return a new instance of SparseToSparseSetOperation
@@ -181,4 +185,73 @@ public Options validateIndices(Boolean validateIndices) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseToSparseSetOperation<T>> {
+    /**
+     * 2D {@code Tensor}, indices of a {@code SparseTensor}. Must be in row-major
+     * order.
+     */
+    public final Operand<TInt64> set1Indices;
+
+    /**
+     * 1D {@code Tensor}, values of a {@code SparseTensor}. Must be in row-major
+     * order.
+     */
+    public final Operand<T> set1Values;
+
+    /**
+     * 1D {@code Tensor}, shape of a {@code SparseTensor}. {@code set1_shape[0...n-1]} must
+     * be the same as {@code set2_shape[0...n-1]}, {@code set1_shape[n]} is the
+     * max set size across {@code 0...n-1} dimensions.
+     */
+    public final Operand<TInt64> set1Shape;
+
+    /**
+     * 2D {@code Tensor}, indices of a {@code SparseTensor}. Must be in row-major
+     * order.
+     */
+    public final Operand<TInt64> set2Indices;
+
+    /**
+     * 1D {@code Tensor}, values of a {@code SparseTensor}. Must be in row-major
+     * order.
+     */
+    public final Operand<T> set2Values;
+
+    /**
+     * 1D {@code Tensor}, shape of a {@code SparseTensor}. {@code set2_shape[0...n-1]} must
+     * be the same as {@code set1_shape[0...n-1]}, {@code set2_shape[n]} is the
+     * max set size across {@code 0...n-1} dimensions.
+     */
+    public final Operand<TInt64> set2Shape;
+
+    /**
+     * The setOperation attribute
+     */
+    public final String setOperation;
+
+    /**
+     * The validateIndices attribute
+     */
+    public final boolean validateIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseToSparseSetOperation<>(op), op, Arrays.asList("set_operation", "validate_indices", "T"));
+      int inputIndex = 0;
+      set1Indices = (Operand<TInt64>) op.input(inputIndex++);
+      set1Values = (Operand<T>) op.input(inputIndex++);
+      set1Shape = (Operand<TInt64>) op.input(inputIndex++);
+      set2Indices = (Operand<TInt64>) op.input(inputIndex++);
+      set2Values = (Operand<T>) op.input(inputIndex++);
+      set2Shape = (Operand<TInt64>) op.input(inputIndex++);
+      setOperation = op.attributes().getAttrString("set_operation");
+      validateIndices = op.attributes().getAttrBool("validate_indices");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java
index 0f0e504a484..eaec58d9901 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.sparse;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -214,4 +218,39 @@ public Options sharedName(String sharedName) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TakeManySparseFromTensorsMap<?>> {
+    /**
+     * 1-D, The {@code N} serialized {@code SparseTensor} objects.
+     * Shape: {@code [N]}.
+     */
+    public final Operand<TInt64> sparseHandles;
+
+    /**
+     * The `dtype` of the `SparseTensor` objects stored in the
+     * `SparseTensorsMap`.
+     */
+    public final DataType dtype;
+
+    /**
+     * The container name for the `SparseTensorsMap` read by this op.
+     */
+    public final String container;
+
+    /**
+     * The shared name for the `SparseTensorsMap` read by this op.
+     * It should not be blank; rather the `shared_name` or unique Operation name
+     * of the Op that created the original `SparseTensorsMap` should be used.
+     */
+    public final String sharedName;
+
+    public Inputs(GraphOperation op) {
+      super(new TakeManySparseFromTensorsMap<>(op), op, Arrays.asList("dtype", "container", "shared_name"));
+      int inputIndex = 0;
+      sparseHandles = (Operand<TInt64>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Join.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Join.java
index 0edb7c882ce..6985e0283c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Join.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Join.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -129,4 +132,27 @@ public Options separator(String separator) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Join> {
+    /**
+     * A list of string tensors.  The tensors must all have the same shape,
+     * or be scalars.  Scalars may be mixed in; these will be broadcast to the shape
+     * of non-scalar inputs.
+     */
+    public final Iterable<Operand<TString>> inputs;
+
+    /**
+     * string, an optional join separator.
+     */
+    public final String separator;
+
+    public Inputs(GraphOperation op) {
+      super(new Join(op), op, Arrays.asList("separator"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<TString>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      separator = op.attributes().getAttrString("separator");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java
index 61b4a5664e6..83f55b3ef0f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -126,4 +129,24 @@ public Options encoding(String encoding) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Lower> {
+    /**
+     * The input to be lower-cased.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * Character encoding of `input`. Allowed values are '' and 'utf-8'.
+     * Value '' is interpreted as ASCII.
+     */
+    public final String encoding;
+
+    public Inputs(GraphOperation op) {
+      super(new Lower(op), op, Arrays.asList("encoding"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      encoding = op.attributes().getAttrString("encoding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java
index 4e914486e2a..2e9e709d68c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -169,4 +172,37 @@ public Options separator(String separator) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ReduceJoin> {
+    /**
+     * The input to be joined.  All reduced indices must have non-zero size.
+     */
+    public final Operand<TString> inputs;
+
+    /**
+     * The dimensions to reduce over.  Dimensions are reduced in the
+     * order specified.  Omitting {@code reduction_indices} is equivalent to passing
+     * {@code [n-1, n-2, ..., 0]}.  Negative indices from {@code -n} to {@code -1} are supported.
+     */
+    public final Operand<TInt32> reductionIndices;
+
+    /**
+     * If `True`, retain reduced dimensions with length `1`.
+     */
+    public final boolean keepDims;
+
+    /**
+     * The separator to use when joining.
+     */
+    public final String separator;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceJoin(op), op, Arrays.asList("keep_dims", "separator"));
+      int inputIndex = 0;
+      inputs = (Operand<TString>) op.input(inputIndex++);
+      reductionIndices = (Operand<TInt32>) op.input(inputIndex++);
+      keepDims = op.attributes().getAttrBool("keep_dims");
+      separator = op.attributes().getAttrString("separator");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexFullMatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexFullMatch.java
index 17fd9dddcc7..31157d96864 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexFullMatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexFullMatch.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -96,4 +99,23 @@ public Output<TBool> output() {
   public Output<TBool> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<RegexFullMatch> {
+    /**
+     * A string tensor of the text to be processed.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * A scalar string tensor containing the regular expression to match the input.
+     */
+    public final Operand<TString> pattern;
+
+    public Inputs(GraphOperation op) {
+      super(new RegexFullMatch(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      pattern = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java
index 535d46e9897..ca767d27f1e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -127,4 +130,38 @@ public Options replaceGlobal(Boolean replaceGlobal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RegexReplace> {
+    /**
+     * The text to be processed.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * The regular expression to be matched in the {@code input} strings.
+     */
+    public final Operand<TString> pattern;
+
+    /**
+     * The rewrite string to be substituted for the {@code pattern} expression where it is
+     * matched in the {@code input} strings.
+     */
+    public final Operand<TString> rewrite;
+
+    /**
+     * If True, the replacement is global (that is, all matches of the `pattern` regular
+     * expression in each input string are rewritten), otherwise the `rewrite`
+     * substitution is only made for the first `pattern` match.
+     */
+    public final boolean replaceGlobal;
+
+    public Inputs(GraphOperation op) {
+      super(new RegexReplace(op), op, Arrays.asList("replace_global"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      pattern = (Operand<TString>) op.input(inputIndex++);
+      rewrite = (Operand<TString>) op.input(inputIndex++);
+      replaceGlobal = op.attributes().getAttrBool("replace_global");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexFullMatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexFullMatch.java
index 1eba6e9c223..d101be0d46a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexFullMatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexFullMatch.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TBool;
@@ -80,4 +83,23 @@ public Output<TBool> output() {
   public Output<TBool> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<StaticRegexFullMatch> {
+    /**
+     * A string tensor of the text to be processed.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * The regular expression to match the input.
+     */
+    public final String pattern;
+
+    public Inputs(GraphOperation op) {
+      super(new StaticRegexFullMatch(op), op, Arrays.asList("pattern"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      pattern = op.attributes().getAttrString("pattern");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexReplace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexReplace.java
index 565437356c0..fdbb0c3e4da 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexReplace.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StaticRegexReplace.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -119,4 +122,36 @@ public Options replaceGlobal(Boolean replaceGlobal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StaticRegexReplace> {
+    /**
+     * The text to be processed.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * The regular expression to match the input.
+     */
+    public final String pattern;
+
+    /**
+     * The rewrite to be applied to the matched expression.
+     */
+    public final String rewrite;
+
+    /**
+     * If True, the replacement is global, otherwise the replacement
+     * is done only on the first match.
+     */
+    public final boolean replaceGlobal;
+
+    public Inputs(GraphOperation op) {
+      super(new StaticRegexReplace(op), op, Arrays.asList("pattern", "rewrite", "replace_global"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      pattern = op.attributes().getAttrString("pattern");
+      rewrite = op.attributes().getAttrString("rewrite");
+      replaceGlobal = op.attributes().getAttrBool("replace_global");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringFormat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringFormat.java
index 73e13bc795a..a7becde73ec 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringFormat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringFormat.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 
 /**
@@ -169,4 +173,43 @@ public Options summarize(Long summarize) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StringFormat> {
+    /**
+     * The list of tensors to format into the placeholder string.
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    /**
+     * A string, the template to format tensor summaries into.
+     */
+    public final String template;
+
+    /**
+     * A string, at each placeholder in the template a subsequent tensor summary will be inserted.
+     */
+    public final String placeholder;
+
+    /**
+     * When formatting the tensor summaries print the first and last summarize entries of each tensor dimension.
+     */
+    public final long summarize;
+
+    public Inputs(GraphOperation op) {
+      super(new StringFormat(op), op, Arrays.asList("T", "template", "placeholder", "summarize"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrTypeList("T");
+      template = op.attributes().getAttrString("template");
+      placeholder = op.attributes().getAttrString("placeholder");
+      summarize = op.attributes().getAttrInt("summarize");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java
index cab105ec8ee..98aa6dbec32 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -137,4 +140,27 @@ public Options unit(String unit) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StringLength> {
+    /**
+     * The strings for which to compute the length for each element.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * The unit that is counted to compute string length.  One of: `"BYTE"` (for
+     * the number of bytes in each string) or `"UTF8_CHAR"` (for the number of UTF-8
+     * encoded Unicode code points in each string).  Results are undefined
+     * if `unit=UTF8_CHAR` and the `input` strings do not contain structurally
+     * valid UTF-8.
+     */
+    public final String unit;
+
+    public Inputs(GraphOperation op) {
+      super(new StringLength(op), op, Arrays.asList("unit"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      unit = op.attributes().getAttrString("unit");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java
index c768a8cd421..49d00162650 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -74,7 +78,7 @@ private StringNGrams(Operation operation) {
    * sequence. Note that padding will never be greater than 'ngram_widths'-1
    * regardless of this value. If {@code pad_width=-1}, then add {@code max(ngram_widths)-1}
    * elements.
-   * @param preserveShortSequences the value of the preserveShortSequences property
+   * @param preserveShortSequences The value of the preserveShortSequences attribute
    * @param <T> data type for {@code StringNGrams} output and operands
    * @return a new instance of StringNGrams
    */
@@ -117,4 +121,71 @@ public Output<TString> ngrams() {
   public Output<T> ngramsSplits() {
     return ngramsSplits;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<StringNGrams<T>> {
+    /**
+     * The values tensor of the ragged string tensor to make ngrams out of. Must be a
+     * 1D string tensor.
+     */
+    public final Operand<TString> data;
+
+    /**
+     * The splits tensor of the ragged string tensor to make ngrams out of.
+     */
+    public final Operand<T> dataSplits;
+
+    /**
+     * The string to append between elements of the token. Use "" for no separator.
+     */
+    public final String separator;
+
+    /**
+     * The sizes of the ngrams to create.
+     */
+    public final long[] ngramWidths;
+
+    /**
+     * The string to use to pad the left side of the ngram sequence. Only used if
+     * pad_width != 0.
+     */
+    public final String leftPad;
+
+    /**
+     * The string to use to pad the right side of the ngram sequence. Only used if
+     * pad_width != 0.
+     */
+    public final String rightPad;
+
+    /**
+     * The number of padding elements to add to each side of each
+     * sequence. Note that padding will never be greater than 'ngram_widths'-1
+     * regardless of this value. If `pad_width=-1`, then add `max(ngram_widths)-1`
+     * elements.
+     */
+    public final long padWidth;
+
+    /**
+     * The preserveShortSequences attribute
+     */
+    public final boolean preserveShortSequences;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new StringNGrams<>(op), op, Arrays.asList("separator", "ngram_widths", "left_pad", "right_pad", "pad_width", "preserve_short_sequences", "Tsplits"));
+      int inputIndex = 0;
+      data = (Operand<TString>) op.input(inputIndex++);
+      dataSplits = (Operand<T>) op.input(inputIndex++);
+      separator = op.attributes().getAttrString("separator");
+      ngramWidths = op.attributes().getAttrIntList("ngram_widths");
+      leftPad = op.attributes().getAttrString("left_pad");
+      rightPad = op.attributes().getAttrString("right_pad");
+      padWidth = op.attributes().getAttrInt("pad_width");
+      preserveShortSequences = op.attributes().getAttrBool("preserve_short_sequences");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringSplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringSplit.java
index 51a137ca33b..499cc5269c0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringSplit.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringSplit.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -159,4 +162,29 @@ public Options maxsplit(Long maxsplit) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<StringSplit> {
+    /**
+     * {@code 1-D} string {@code Tensor}, the strings to split.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * {@code 0-D} string {@code Tensor}, the delimiter character.
+     */
+    public final Operand<TString> sep;
+
+    /**
+     * An `int`. If `maxsplit > 0`, limit of the split of the result.
+     */
+    public final long maxsplit;
+
+    public Inputs(GraphOperation op) {
+      super(new StringSplit(op), op, Arrays.asList("maxsplit"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      sep = (Operand<TString>) op.input(inputIndex++);
+      maxsplit = op.attributes().getAttrInt("maxsplit");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Strip.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Strip.java
index afd03047152..b5aefbb65ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Strip.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Strip.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -85,4 +88,17 @@ public Output<TString> output() {
   public Output<TString> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Strip> {
+    /**
+     * A string {@code Tensor} of any shape.
+     */
+    public final Operand<TString> input;
+
+    public Inputs(GraphOperation op) {
+      super(new Strip(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java
index fae4b2a26ec..acfebc4fe95 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -197,4 +201,45 @@ public Options unit(String unit) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<Substr> {
+    /**
+     * Tensor of strings
+     */
+    public final Operand<TString> input;
+
+    /**
+     * Scalar defining the position of first character in each substring
+     */
+    public final Operand<T> pos;
+
+    /**
+     * Scalar defining the number of characters to include in each substring
+     */
+    public final Operand<T> len;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The unit that is used to create the substring.  One of: `"BYTE"` (for
+     * defining position and length by bytes) or `"UTF8_CHAR"` (for the UTF-8
+     * encoded Unicode code points).  The default is `"BYTE"`. Results are undefined if
+     * `unit=UTF8_CHAR` and the `input` strings do not contain structurally valid
+     * UTF-8.
+     */
+    public final String unit;
+
+    public Inputs(GraphOperation op) {
+      super(new Substr(op), op, Arrays.asList("T", "unit"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      pos = (Operand<T>) op.input(inputIndex++);
+      len = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      unit = op.attributes().getAttrString("unit");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucket.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucket.java
index 17e4f6946d3..f801507c1ad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucket.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucket.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -57,7 +60,7 @@ private ToHashBucket(Operation operation) {
    * Factory method to create a class wrapping a new StringToHashBucket operation.
    *
    * @param scope current scope
-   * @param stringTensor the stringTensor value
+   * @param stringTensor The stringTensor value
    * @param numBuckets The number of buckets.
    * @return a new instance of ToHashBucket
    */
@@ -84,4 +87,23 @@ public Output<TInt64> output() {
   public Output<TInt64> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ToHashBucket> {
+    /**
+     * The stringTensor input
+     */
+    public final Operand<TString> stringTensor;
+
+    /**
+     * The number of buckets.
+     */
+    public final long numBuckets;
+
+    public Inputs(GraphOperation op) {
+      super(new ToHashBucket(op), op, Arrays.asList("num_buckets"));
+      int inputIndex = 0;
+      stringTensor = (Operand<TString>) op.input(inputIndex++);
+      numBuckets = op.attributes().getAttrInt("num_buckets");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketFast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketFast.java
index 5e85fc085a7..39cdf8a5405 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketFast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketFast.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -94,4 +97,23 @@ public Output<TInt64> output() {
   public Output<TInt64> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ToHashBucketFast> {
+    /**
+     * The strings to assign a hash bucket.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * The number of buckets.
+     */
+    public final long numBuckets;
+
+    public Inputs(GraphOperation op) {
+      super(new ToHashBucketFast(op), op, Arrays.asList("num_buckets"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      numBuckets = op.attributes().getAttrInt("num_buckets");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketStrong.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketStrong.java
index 9cf389be380..f9ca9b8115f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketStrong.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToHashBucketStrong.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -108,4 +111,30 @@ public Output<TInt64> output() {
   public Output<TInt64> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ToHashBucketStrong> {
+    /**
+     * The strings to assign a hash bucket.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * The number of buckets.
+     */
+    public final long numBuckets;
+
+    /**
+     * The key used to seed the hash function, passed as a list of two uint64
+     * elements.
+     */
+    public final long[] key;
+
+    public Inputs(GraphOperation op) {
+      super(new ToHashBucketStrong(op), op, Arrays.asList("num_buckets", "key"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      numBuckets = op.attributes().getAttrInt("num_buckets");
+      key = op.attributes().getAttrIntList("key");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java
index 733233bdba9..f8f325282fc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
@@ -68,7 +72,7 @@ private ToNumber(Operation operation) {
    * Factory method to create a class wrapping a new StringToNumber operation.
    *
    * @param scope current scope
-   * @param stringTensor the stringTensor value
+   * @param stringTensor The stringTensor value
    * @param outType The numeric type to interpret each string in {@code string_tensor} as.
    * @param <T> data type for {@code StringToNumber} output and operands
    * @return a new instance of ToNumber
@@ -88,7 +92,7 @@ public static <T extends TNumber> ToNumber<T> create(Scope scope, Operand<TStrin
    * Factory method to create a class wrapping a new StringToNumber operation, with the default output types.
    *
    * @param scope current scope
-   * @param stringTensor the stringTensor value
+   * @param stringTensor The stringTensor value
    * @return a new instance of ToNumber, with default output types
    */
   @Endpoint(
@@ -111,4 +115,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<ToNumber<?>> {
+    /**
+     * The stringTensor input
+     */
+    public final Operand<TString> stringTensor;
+
+    /**
+     * The numeric type to interpret each string in `string_tensor` as.
+     */
+    public final DataType outType;
+
+    public Inputs(GraphOperation op) {
+      super(new ToNumber<>(op), op, Arrays.asList("out_type"));
+      int inputIndex = 0;
+      stringTensor = (Operand<TString>) op.input(inputIndex++);
+      outType = op.attributes().getAttrType("out_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java
index 9640d30b1c1..a130514dc54 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -73,7 +77,7 @@ private UnicodeDecode(Operation operation) {
    * to a vector of char values.
    * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported
    * by ICU ucnv algorithmic converters. Examples: {@code "UTF-16", "US ASCII", "UTF-8"}.
-   * @param Tsplits the value of the Tsplits property
+   * @param Tsplits The value of the Tsplits attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code UnicodeDecode} output and operands
    * @return a new instance of UnicodeDecode
@@ -236,4 +240,59 @@ public Options replaceControlCharacters(Boolean replaceControlCharacters) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<UnicodeDecode<?>> {
+    /**
+     * The text to be decoded. Can have any shape. Note that the output is flattened
+     * to a vector of char values.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * Text encoding of the input strings. This is any of the encodings supported
+     * by ICU ucnv algorithmic converters. Examples: `"UTF-16", "US ASCII", "UTF-8"`.
+     */
+    public final String inputEncoding;
+
+    /**
+     * Error handling policy when there is invalid formatting found in the input.
+     * The value of 'strict' will cause the operation to produce a InvalidArgument
+     * error on any invalid input formatting. A value of 'replace' (the default) will
+     * cause the operation to replace any invalid formatting in the input with the
+     * `replacement_char` codepoint. A value of 'ignore' will cause the operation to
+     * skip any invalid formatting in the input and produce no corresponding output
+     * character.
+     */
+    public final String errors;
+
+    /**
+     * The replacement character codepoint to be used in place of any invalid
+     * formatting in the input when `errors='replace'`. Any valid unicode codepoint may
+     * be used. The default value is the default unicode replacement character is
+     * 0xFFFD or U+65533.)
+     */
+    public final long replacementChar;
+
+    /**
+     * Whether to replace the C0 control characters (00-1F) with the
+     * `replacement_char`. Default is false.
+     */
+    public final boolean replaceControlCharacters;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new UnicodeDecode<>(op), op, Arrays.asList("input_encoding", "errors", "replacement_char", "replace_control_characters", "Tsplits"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      inputEncoding = op.attributes().getAttrString("input_encoding");
+      errors = op.attributes().getAttrString("errors");
+      replacementChar = op.attributes().getAttrInt("replacement_char");
+      replaceControlCharacters = op.attributes().getAttrBool("replace_control_characters");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java
index 0cb5419064a..c3467e760b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -80,7 +84,7 @@ private UnicodeDecodeWithOffsets(Operation operation) {
    * to a vector of char values.
    * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported
    * by ICU ucnv algorithmic converters. Examples: {@code "UTF-16", "US ASCII", "UTF-8"}.
-   * @param Tsplits the value of the Tsplits property
+   * @param Tsplits The value of the Tsplits attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code UnicodeDecodeWithOffsets} output and operands
    * @return a new instance of UnicodeDecodeWithOffsets
@@ -253,4 +257,59 @@ public Options replaceControlCharacters(Boolean replaceControlCharacters) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<UnicodeDecodeWithOffsets<?>> {
+    /**
+     * The text to be decoded. Can have any shape. Note that the output is flattened
+     * to a vector of char values.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * Text encoding of the input strings. This is any of the encodings supported
+     * by ICU ucnv algorithmic converters. Examples: `"UTF-16", "US ASCII", "UTF-8"`.
+     */
+    public final String inputEncoding;
+
+    /**
+     * Error handling policy when there is invalid formatting found in the input.
+     * The value of 'strict' will cause the operation to produce a InvalidArgument
+     * error on any invalid input formatting. A value of 'replace' (the default) will
+     * cause the operation to replace any invalid formatting in the input with the
+     * `replacement_char` codepoint. A value of 'ignore' will cause the operation to
+     * skip any invalid formatting in the input and produce no corresponding output
+     * character.
+     */
+    public final String errors;
+
+    /**
+     * The replacement character codepoint to be used in place of any invalid
+     * formatting in the input when `errors='replace'`. Any valid unicode codepoint may
+     * be used. The default value is the default unicode replacement character is
+     * 0xFFFD or U+65533.)
+     */
+    public final long replacementChar;
+
+    /**
+     * Whether to replace the C0 control characters (00-1F) with the
+     * `replacement_char`. Default is false.
+     */
+    public final boolean replaceControlCharacters;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new UnicodeDecodeWithOffsets<>(op), op, Arrays.asList("input_encoding", "errors", "replacement_char", "replace_control_characters", "Tsplits"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      inputEncoding = op.attributes().getAttrString("input_encoding");
+      errors = op.attributes().getAttrString("errors");
+      replacementChar = op.attributes().getAttrInt("replacement_char");
+      replaceControlCharacters = op.attributes().getAttrBool("replace_control_characters");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java
index 31270365f6b..ffa29a2ddb4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
@@ -176,4 +180,59 @@ public Options replacementChar(Long replacementChar) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<UnicodeEncode> {
+    /**
+     * A 1D tensor containing the unicode codepoints that should be encoded.
+     */
+    public final Operand<TInt32> inputValues;
+
+    /**
+     * A 1D tensor specifying how the unicode codepoints should be split into strings.
+     * In particular, {@code output[i]} is constructed by encoding the codepoints in the
+     * slice {@code input_values[input_splits[i]:input_splits[i+1]]}.
+     */
+    public final Operand<? extends TNumber> inputSplits;
+
+    /**
+     * Error handling policy when there is invalid formatting found in the input.
+     * The value of 'strict' will cause the operation to produce a InvalidArgument
+     * error on any invalid input formatting. A value of 'replace' (the default) will
+     * cause the operation to replace any invalid formatting in the input with the
+     * `replacement_char` codepoint. A value of 'ignore' will cause the operation to
+     * skip any invalid formatting in the input and produce no corresponding output
+     * character.
+     */
+    public final String errors;
+
+    /**
+     * Unicode encoding of the output strings. Valid encodings are: `"UTF-8",
+     * "UTF-16-BE", and "UTF-32-BE"`.
+     */
+    public final String outputEncoding;
+
+    /**
+     * The replacement character codepoint to be used in place of any invalid
+     * formatting in the input when `errors='replace'`. Any valid unicode codepoint may
+     * be used. The default value is the default unicode replacement character is
+     * 0xFFFD (U+65533).
+     */
+    public final long replacementChar;
+
+    /**
+     * The Tsplits attribute
+     */
+    public final DataType Tsplits;
+
+    public Inputs(GraphOperation op) {
+      super(new UnicodeEncode(op), op, Arrays.asList("errors", "output_encoding", "replacement_char", "Tsplits"));
+      int inputIndex = 0;
+      inputValues = (Operand<TInt32>) op.input(inputIndex++);
+      inputSplits = (Operand<? extends TNumber>) op.input(inputIndex++);
+      errors = op.attributes().getAttrString("errors");
+      outputEncoding = op.attributes().getAttrString("output_encoding");
+      replacementChar = op.attributes().getAttrInt("replacement_char");
+      Tsplits = op.attributes().getAttrType("Tsplits");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeScript.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeScript.java
index ea638c3aad7..ce046508f36 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeScript.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeScript.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -95,4 +98,17 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<UnicodeScript> {
+    /**
+     * A Tensor of int32 Unicode code points.
+     */
+    public final Operand<TInt32> input;
+
+    public Inputs(GraphOperation op) {
+      super(new UnicodeScript(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TInt32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java
index b200bf64022..90194f8b23a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -237,4 +240,64 @@ public Options replaceControlCharacters(Boolean replaceControlCharacters) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<UnicodeTranscode> {
+    /**
+     * The text to be processed. Can have any shape.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * Text encoding of the input strings. This is any of the encodings supported
+     * by ICU ucnv algorithmic converters. Examples: `"UTF-16", "US ASCII", "UTF-8"`.
+     */
+    public final String inputEncoding;
+
+    /**
+     * The unicode encoding to use in the output. Must be one of
+     * `"UTF-8", "UTF-16-BE", "UTF-32-BE"`. Multi-byte encodings will be big-endian.
+     */
+    public final String outputEncoding;
+
+    /**
+     * Error handling policy when there is invalid formatting found in the input.
+     * The value of 'strict' will cause the operation to produce a InvalidArgument
+     * error on any invalid input formatting. A value of 'replace' (the default) will
+     * cause the operation to replace any invalid formatting in the input with the
+     * `replacement_char` codepoint. A value of 'ignore' will cause the operation to
+     * skip any invalid formatting in the input and produce no corresponding output
+     * character.
+     */
+    public final String errors;
+
+    /**
+     * The replacement character codepoint to be used in place of any invalid
+     * formatting in the input when `errors='replace'`. Any valid unicode codepoint may
+     * be used. The default value is the default unicode replacement character is
+     * 0xFFFD or U+65533.)
+     *
+     * Note that for UTF-8, passing a replacement character expressible in 1 byte, such
+     * as ' ', will preserve string alignment to the source since invalid bytes will be
+     * replaced with a 1-byte replacement. For UTF-16-BE and UTF-16-LE, any 1 or 2 byte
+     * replacement character will preserve byte alignment to the source.
+     */
+    public final long replacementChar;
+
+    /**
+     * Whether to replace the C0 control characters (00-1F) with the
+     * `replacement_char`. Default is false.
+     */
+    public final boolean replaceControlCharacters;
+
+    public Inputs(GraphOperation op) {
+      super(new UnicodeTranscode(op), op, Arrays.asList("input_encoding", "output_encoding", "errors", "replacement_char", "replace_control_characters"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      inputEncoding = op.attributes().getAttrString("input_encoding");
+      outputEncoding = op.attributes().getAttrString("output_encoding");
+      errors = op.attributes().getAttrString("errors");
+      replacementChar = op.attributes().getAttrInt("replacement_char");
+      replaceControlCharacters = op.attributes().getAttrBool("replace_control_characters");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java
index cbd8c518994..58b1eb8ac3b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -147,4 +151,48 @@ public Options separator(String separator) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<UnsortedSegmentJoin> {
+    /**
+     * The input to be joined.
+     */
+    public final Operand<TString> inputs;
+
+    /**
+     * A tensor whose shape is a prefix of data.shape.  Negative segment ids are not
+     * supported.
+     */
+    public final Operand<? extends TNumber> segmentIds;
+
+    /**
+     * A scalar.
+     */
+    public final Operand<? extends TNumber> numSegments;
+
+    /**
+     * The separator to use when joining.
+     */
+    public final String separator;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * The Tnumsegments attribute
+     */
+    public final DataType Tnumsegments;
+
+    public Inputs(GraphOperation op) {
+      super(new UnsortedSegmentJoin(op), op, Arrays.asList("separator", "Tindices", "Tnumsegments"));
+      int inputIndex = 0;
+      inputs = (Operand<TString>) op.input(inputIndex++);
+      segmentIds = (Operand<? extends TNumber>) op.input(inputIndex++);
+      numSegments = (Operand<? extends TNumber>) op.input(inputIndex++);
+      separator = op.attributes().getAttrString("separator");
+      Tindices = op.attributes().getAttrType("Tindices");
+      Tnumsegments = op.attributes().getAttrType("Tnumsegments");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java
index 8e8b0c06ff9..7ba066da30c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.strings;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -126,4 +129,24 @@ public Options encoding(String encoding) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Upper> {
+    /**
+     * The input to be upper-cased.
+     */
+    public final Operand<TString> input;
+
+    /**
+     * Character encoding of `input`. Allowed values are '' and 'utf-8'.
+     * Value '' is interpreted as ASCII.
+     */
+    public final String encoding;
+
+    public Inputs(GraphOperation op) {
+      super(new Upper(op), op, Arrays.asList("encoding"));
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+      encoding = op.attributes().getAttrString("encoding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/AudioSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/AudioSummary.java
index a971795dd2d..9a78e8b1bfc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/AudioSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/AudioSummary.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -131,4 +134,35 @@ public Options maxOutputs(Long maxOutputs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<AudioSummary> {
+    /**
+     * Scalar. Used to build the {@code tag} attribute of the summary values.
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * 2-D of shape {@code [batch_size, frames]}.
+     */
+    public final Operand<TFloat32> tensor;
+
+    /**
+     * The sample rate of the signal in hertz.
+     */
+    public final Operand<TFloat32> sampleRate;
+
+    /**
+     * Max number of batch elements to generate audio for.
+     */
+    public final long maxOutputs;
+
+    public Inputs(GraphOperation op) {
+      super(new AudioSummary(op), op, Arrays.asList("max_outputs"));
+      int inputIndex = 0;
+      tag = (Operand<TString>) op.input(inputIndex++);
+      tensor = (Operand<TFloat32>) op.input(inputIndex++);
+      sampleRate = (Operand<TFloat32>) op.input(inputIndex++);
+      maxOutputs = op.attributes().getAttrInt("max_outputs");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CloseSummaryWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CloseSummaryWriter.java
index c7bb55643da..58b8dcef495 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CloseSummaryWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CloseSummaryWriter.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -42,7 +45,7 @@ private CloseSummaryWriter(Operation operation) {
    * Factory method to create a class wrapping a new CloseSummaryWriter operation.
    *
    * @param scope current scope
-   * @param writer the writer value
+   * @param writer The writer value
    * @return a new instance of CloseSummaryWriter
    */
   @Endpoint(
@@ -53,4 +56,17 @@ public static CloseSummaryWriter create(Scope scope, Operand<? extends TType> wr
     opBuilder.addInput(writer.asOutput());
     return new CloseSummaryWriter(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<CloseSummaryWriter> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    public Inputs(GraphOperation op) {
+      super(new CloseSummaryWriter(op), op, Arrays.asList());
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryDbWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryDbWriter.java
index c7dc8ec117f..8af194417b1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryDbWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryDbWriter.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -43,11 +46,11 @@ private CreateSummaryDbWriter(Operation operation) {
    * Factory method to create a class wrapping a new CreateSummaryDbWriter operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param dbUri the dbUri value
-   * @param experimentName the experimentName value
-   * @param runName the runName value
-   * @param userName the userName value
+   * @param writer The writer value
+   * @param dbUri The dbUri value
+   * @param experimentName The experimentName value
+   * @param runName The runName value
+   * @param userName The userName value
    * @return a new instance of CreateSummaryDbWriter
    */
   @Endpoint(
@@ -64,4 +67,41 @@ public static CreateSummaryDbWriter create(Scope scope, Operand<? extends TType>
     opBuilder.addInput(userName.asOutput());
     return new CreateSummaryDbWriter(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<CreateSummaryDbWriter> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The dbUri input
+     */
+    public final Operand<TString> dbUri;
+
+    /**
+     * The experimentName input
+     */
+    public final Operand<TString> experimentName;
+
+    /**
+     * The runName input
+     */
+    public final Operand<TString> runName;
+
+    /**
+     * The userName input
+     */
+    public final Operand<TString> userName;
+
+    public Inputs(GraphOperation op) {
+      super(new CreateSummaryDbWriter(op), op, Arrays.asList());
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      dbUri = (Operand<TString>) op.input(inputIndex++);
+      experimentName = (Operand<TString>) op.input(inputIndex++);
+      runName = (Operand<TString>) op.input(inputIndex++);
+      userName = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryFileWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryFileWriter.java
index cc448613793..aecb55a68f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryFileWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/CreateSummaryFileWriter.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -44,11 +47,11 @@ private CreateSummaryFileWriter(Operation operation) {
    * Factory method to create a class wrapping a new CreateSummaryFileWriter operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param logdir the logdir value
-   * @param maxQueue the maxQueue value
-   * @param flushMillis the flushMillis value
-   * @param filenameSuffix the filenameSuffix value
+   * @param writer The writer value
+   * @param logdir The logdir value
+   * @param maxQueue The maxQueue value
+   * @param flushMillis The flushMillis value
+   * @param filenameSuffix The filenameSuffix value
    * @return a new instance of CreateSummaryFileWriter
    */
   @Endpoint(
@@ -65,4 +68,41 @@ public static CreateSummaryFileWriter create(Scope scope, Operand<? extends TTyp
     opBuilder.addInput(filenameSuffix.asOutput());
     return new CreateSummaryFileWriter(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<CreateSummaryFileWriter> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The logdir input
+     */
+    public final Operand<TString> logdir;
+
+    /**
+     * The maxQueue input
+     */
+    public final Operand<TInt32> maxQueue;
+
+    /**
+     * The flushMillis input
+     */
+    public final Operand<TInt32> flushMillis;
+
+    /**
+     * The filenameSuffix input
+     */
+    public final Operand<TString> filenameSuffix;
+
+    public Inputs(GraphOperation op) {
+      super(new CreateSummaryFileWriter(op), op, Arrays.asList());
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      logdir = (Operand<TString>) op.input(inputIndex++);
+      maxQueue = (Operand<TInt32>) op.input(inputIndex++);
+      flushMillis = (Operand<TInt32>) op.input(inputIndex++);
+      filenameSuffix = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/FlushSummaryWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/FlushSummaryWriter.java
index e2756661a48..44f22343c23 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/FlushSummaryWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/FlushSummaryWriter.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -42,7 +45,7 @@ private FlushSummaryWriter(Operation operation) {
    * Factory method to create a class wrapping a new FlushSummaryWriter operation.
    *
    * @param scope current scope
-   * @param writer the writer value
+   * @param writer The writer value
    * @return a new instance of FlushSummaryWriter
    */
   @Endpoint(
@@ -53,4 +56,17 @@ public static FlushSummaryWriter create(Scope scope, Operand<? extends TType> wr
     opBuilder.addInput(writer.asOutput());
     return new FlushSummaryWriter(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<FlushSummaryWriter> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    public Inputs(GraphOperation op) {
+      super(new FlushSummaryWriter(op), op, Arrays.asList());
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java
index 0c5ab5b5eec..6e05d278830 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -84,4 +88,29 @@ public Output<TString> summary() {
   public Output<TString> asOutput() {
     return summary;
   }
+
+  public static class Inputs extends RawOpInputs<HistogramSummary> {
+    /**
+     * Scalar.  Tag to use for the {@code Summary.Value}.
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * Any shape. Values to use to build the histogram.
+     */
+    public final Operand<? extends TNumber> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new HistogramSummary(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      tag = (Operand<TString>) op.input(inputIndex++);
+      values = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java
index f9685d3e7ce..ff83df181ad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.Tensor;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -182,4 +186,42 @@ public Options badColor(Tensor badColor) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ImageSummary> {
+    /**
+     * Scalar. Used to build the {@code tag} attribute of the summary values.
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * 4-D of shape {@code [batch_size, height, width, channels]} where
+     * {@code channels} is 1, 3, or 4.
+     */
+    public final Operand<? extends TNumber> tensor;
+
+    /**
+     * Max number of batch elements to generate images for.
+     */
+    public final long maxImages;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Color to use for pixels with non-finite values.
+     */
+    public final Tensor badColor;
+
+    public Inputs(GraphOperation op) {
+      super(new ImageSummary(op), op, Arrays.asList("max_images", "T", "bad_color"));
+      int inputIndex = 0;
+      tag = (Operand<TString>) op.input(inputIndex++);
+      tensor = (Operand<? extends TNumber>) op.input(inputIndex++);
+      maxImages = op.attributes().getAttrInt("max_images");
+      T = op.attributes().getAttrType("T");
+      badColor = op.attributes().getAttrTensor("bad_color");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImportEvent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImportEvent.java
index 4eb68fbc68d..0150201909b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImportEvent.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImportEvent.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -43,8 +46,8 @@ private ImportEvent(Operation operation) {
    * Factory method to create a class wrapping a new ImportEvent operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param event the event value
+   * @param writer The writer value
+   * @param event The event value
    * @return a new instance of ImportEvent
    */
   @Endpoint(
@@ -57,4 +60,23 @@ public static ImportEvent create(Scope scope, Operand<? extends TType> writer,
     opBuilder.addInput(event.asOutput());
     return new ImportEvent(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ImportEvent> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The event input
+     */
+    public final Operand<TString> event;
+
+    public Inputs(GraphOperation op) {
+      super(new ImportEvent(op), op, Arrays.asList());
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      event = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/MergeSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/MergeSummary.java
index c52ddaac7a4..643d36d2894 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/MergeSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/MergeSummary.java
@@ -17,12 +17,15 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -84,4 +87,20 @@ public Output<TString> summary() {
   public Output<TString> asOutput() {
     return summary;
   }
+
+  public static class Inputs extends RawOpInputs<MergeSummary> {
+    /**
+     * Can be of any shape.  Each must contain serialized {@code Summary} protocol
+     * buffers.
+     */
+    public final Iterable<Operand<TString>> inputs;
+
+    public Inputs(GraphOperation op) {
+      super(new MergeSummary(op), op, Arrays.asList());
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<TString>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java
index a41165f3327..c459ba8413a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -82,4 +86,29 @@ public Output<TString> summary() {
   public Output<TString> asOutput() {
     return summary;
   }
+
+  public static class Inputs extends RawOpInputs<ScalarSummary> {
+    /**
+     * Tags for the summary.
+     */
+    public final Operand<TString> tags;
+
+    /**
+     * Same shape as `tags.  Values for the summary.
+     */
+    public final Operand<? extends TNumber> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ScalarSummary(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      tags = (Operand<TString>) op.input(inputIndex++);
+      values = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/StatsAggregatorSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/StatsAggregatorSummary.java
index 8c6ce2b25d2..d1eeb17ac2f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/StatsAggregatorSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/StatsAggregatorSummary.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -48,7 +51,7 @@ private StatsAggregatorSummary(Operation operation) {
    * Factory method to create a class wrapping a new StatsAggregatorSummary operation.
    *
    * @param scope current scope
-   * @param iterator the iterator value
+   * @param iterator The iterator value
    * @return a new instance of StatsAggregatorSummary
    */
   @Endpoint(
@@ -73,4 +76,17 @@ public Output<TString> summary() {
   public Output<TString> asOutput() {
     return summary;
   }
+
+  public static class Inputs extends RawOpInputs<StatsAggregatorSummary> {
+    /**
+     * The iterator input
+     */
+    public final Operand<? extends TType> iterator;
+
+    public Inputs(GraphOperation op) {
+      super(new StatsAggregatorSummary(op), op, Arrays.asList());
+      int inputIndex = 0;
+      iterator = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/SummaryWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/SummaryWriter.java
index 3183ca16a90..c3a9d913d76 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/SummaryWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/SummaryWriter.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -137,4 +140,23 @@ public Options container(String container) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SummaryWriter> {
+    /**
+     * The sharedName attribute
+     */
+    public final String sharedName;
+
+    /**
+     * The container attribute
+     */
+    public final String container;
+
+    public Inputs(GraphOperation op) {
+      super(new SummaryWriter(op), op, Arrays.asList("shared_name", "container"));
+      int inputIndex = 0;
+      sharedName = op.attributes().getAttrString("shared_name");
+      container = op.attributes().getAttrString("container");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/TensorSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/TensorSummary.java
index 573a9961992..ccd1dcb3c67 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/TensorSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/TensorSummary.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -83,4 +87,36 @@ public Output<TString> summary() {
   public Output<TString> asOutput() {
     return summary;
   }
+
+  public static class Inputs extends RawOpInputs<TensorSummary> {
+    /**
+     * A string attached to this summary. Used for organization in TensorBoard.
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * A tensor to serialize.
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * A serialized SummaryMetadata proto. Contains plugin
+     * data.
+     */
+    public final Operand<TString> serializedSummaryMetadata;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TensorSummary(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      tag = (Operand<TString>) op.input(inputIndex++);
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      serializedSummaryMetadata = (Operand<TString>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteAudioSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteAudioSummary.java
index 2163effbc50..03c11c27c74 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteAudioSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteAudioSummary.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -47,11 +50,11 @@ private WriteAudioSummary(Operation operation) {
    * Factory method to create a class wrapping a new WriteAudioSummary operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param step the step value
-   * @param tag the tag value
-   * @param tensor the tensor value
-   * @param sampleRate the sampleRate value
+   * @param writer The writer value
+   * @param step The step value
+   * @param tag The tag value
+   * @param tensor The tensor value
+   * @param sampleRate The sampleRate value
    * @param options carries optional attribute values
    * @return a new instance of WriteAudioSummary
    */
@@ -107,4 +110,47 @@ public Options maxOutputs(Long maxOutputs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<WriteAudioSummary> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The step input
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<TFloat32> tensor;
+
+    /**
+     * The sampleRate input
+     */
+    public final Operand<TFloat32> sampleRate;
+
+    /**
+     * The maxOutputs attribute
+     */
+    public final long maxOutputs;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteAudioSummary(op), op, Arrays.asList("max_outputs"));
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      tensor = (Operand<TFloat32>) op.input(inputIndex++);
+      sampleRate = (Operand<TFloat32>) op.input(inputIndex++);
+      maxOutputs = op.attributes().getAttrInt("max_outputs");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteGraphSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteGraphSummary.java
index 725f481eab9..791f2e53025 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteGraphSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteGraphSummary.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -45,9 +48,9 @@ private WriteGraphSummary(Operation operation) {
    * Factory method to create a class wrapping a new WriteGraphSummary operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param step the step value
-   * @param tensor the tensor value
+   * @param writer The writer value
+   * @param step The step value
+   * @param tensor The tensor value
    * @return a new instance of WriteGraphSummary
    */
   @Endpoint(
@@ -61,4 +64,29 @@ public static WriteGraphSummary create(Scope scope, Operand<? extends TType> wri
     opBuilder.addInput(tensor.asOutput());
     return new WriteGraphSummary(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<WriteGraphSummary> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The step input
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<TString> tensor;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteGraphSummary(op), op, Arrays.asList());
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      tensor = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java
index b82701d2fec..93f3c00c93e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -45,10 +49,10 @@ private WriteHistogramSummary(Operation operation) {
    * Factory method to create a class wrapping a new WriteHistogramSummary operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param step the step value
-   * @param tag the tag value
-   * @param values the values value
+   * @param writer The writer value
+   * @param step The step value
+   * @param tag The tag value
+   * @param values The values value
    * @return a new instance of WriteHistogramSummary
    */
   @Endpoint(
@@ -63,4 +67,41 @@ public static WriteHistogramSummary create(Scope scope, Operand<? extends TType>
     opBuilder.addInput(values.asOutput());
     return new WriteHistogramSummary(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<WriteHistogramSummary> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The step input
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The values input
+     */
+    public final Operand<? extends TType> values;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteHistogramSummary(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      values = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java
index 374525fd3c0..9b1b64ae148 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.TUint8;
@@ -48,11 +52,11 @@ private WriteImageSummary(Operation operation) {
    * Factory method to create a class wrapping a new WriteImageSummary operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param step the step value
-   * @param tag the tag value
-   * @param tensor the tensor value
-   * @param badColor the badColor value
+   * @param writer The writer value
+   * @param step The step value
+   * @param tag The tag value
+   * @param tensor The tensor value
+   * @param badColor The badColor value
    * @param options carries optional attribute values
    * @return a new instance of WriteImageSummary
    */
@@ -108,4 +112,53 @@ public Options maxImages(Long maxImages) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<WriteImageSummary> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The step input
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TNumber> tensor;
+
+    /**
+     * The badColor input
+     */
+    public final Operand<TUint8> badColor;
+
+    /**
+     * The maxImages attribute
+     */
+    public final long maxImages;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteImageSummary(op), op, Arrays.asList("max_images", "T"));
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      tensor = (Operand<? extends TNumber>) op.input(inputIndex++);
+      badColor = (Operand<TUint8>) op.input(inputIndex++);
+      maxImages = op.attributes().getAttrInt("max_images");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteRawProtoSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteRawProtoSummary.java
index 47ab6026a7f..66b92490f04 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteRawProtoSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteRawProtoSummary.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -45,9 +48,9 @@ private WriteRawProtoSummary(Operation operation) {
    * Factory method to create a class wrapping a new WriteRawProtoSummary operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param step the step value
-   * @param tensor the tensor value
+   * @param writer The writer value
+   * @param step The step value
+   * @param tensor The tensor value
    * @return a new instance of WriteRawProtoSummary
    */
   @Endpoint(
@@ -61,4 +64,29 @@ public static WriteRawProtoSummary create(Scope scope, Operand<? extends TType>
     opBuilder.addInput(tensor.asOutput());
     return new WriteRawProtoSummary(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<WriteRawProtoSummary> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The step input
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<TString> tensor;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteRawProtoSummary(op), op, Arrays.asList());
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      tensor = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java
index 9313cff199e..3edd2898fd6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
@@ -46,10 +50,10 @@ private WriteScalarSummary(Operation operation) {
    * Factory method to create a class wrapping a new WriteScalarSummary operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param step the step value
-   * @param tag the tag value
-   * @param value the value value
+   * @param writer The writer value
+   * @param step The step value
+   * @param tag The tag value
+   * @param value The value value
    * @return a new instance of WriteScalarSummary
    */
   @Endpoint(
@@ -64,4 +68,41 @@ public static WriteScalarSummary create(Scope scope, Operand<? extends TType> wr
     opBuilder.addInput(value.asOutput());
     return new WriteScalarSummary(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<WriteScalarSummary> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The step input
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The value input
+     */
+    public final Operand<? extends TNumber> value;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteScalarSummary(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      value = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteSummary.java
index 2783d80ea64..0c1f7822242 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteSummary.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.summary;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -45,11 +49,11 @@ private WriteSummary(Operation operation) {
    * Factory method to create a class wrapping a new WriteSummary operation.
    *
    * @param scope current scope
-   * @param writer the writer value
-   * @param step the step value
-   * @param tensor the tensor value
-   * @param tag the tag value
-   * @param summaryMetadata the summaryMetadata value
+   * @param writer The writer value
+   * @param step The step value
+   * @param tensor The tensor value
+   * @param tag The tag value
+   * @param summaryMetadata The summaryMetadata value
    * @return a new instance of WriteSummary
    */
   @Endpoint(
@@ -66,4 +70,47 @@ public static WriteSummary create(Scope scope, Operand<? extends TType> writer,
     opBuilder.addInput(summaryMetadata.asOutput());
     return new WriteSummary(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<WriteSummary> {
+    /**
+     * The writer input
+     */
+    public final Operand<? extends TType> writer;
+
+    /**
+     * The step input
+     */
+    public final Operand<TInt64> step;
+
+    /**
+     * The tensor input
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The tag input
+     */
+    public final Operand<TString> tag;
+
+    /**
+     * The summaryMetadata input
+     */
+    public final Operand<TString> summaryMetadata;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new WriteSummary(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      writer = (Operand<? extends TType>) op.input(inputIndex++);
+      step = (Operand<TInt64>) op.input(inputIndex++);
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      tag = (Operand<TString>) op.input(inputIndex++);
+      summaryMetadata = (Operand<TString>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java
index 34599cbbbda..f5cf0420941 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -101,4 +105,50 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<AllToAll<T>> {
+    /**
+     * The local input to the sum.
+     */
+    public final Operand<T> input;
+
+    /**
+     * An int32 tensor with shape
+     * [num_groups, num_replicas_per_group]. {@code group_assignment[i]} represents the
+     * replica ids in the ith subgroup.
+     */
+    public final Operand<TInt32> groupAssignment;
+
+    /**
+     * The type of elements to be exchanged.
+     */
+    public final DataType T;
+
+    /**
+     * The dimension number to concatenate.
+     */
+    public final long concatDimension;
+
+    /**
+     * The dimension number to split.
+     */
+    public final long splitDimension;
+
+    /**
+     * The number of splits, this number must equal to the sub-group
+     * size(group_assignment.get_shape()[1])
+     */
+    public final long splitCount;
+
+    public Inputs(GraphOperation op) {
+      super(new AllToAll<>(op), op, Arrays.asList("T", "concat_dimension", "split_dimension", "split_count"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      groupAssignment = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      concatDimension = op.attributes().getAttrInt("concat_dimension");
+      splitDimension = op.attributes().getAttrInt("split_dimension");
+      splitCount = op.attributes().getAttrInt("split_count");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CollectivePermute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CollectivePermute.java
index 3083821cf79..0741956dcc7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CollectivePermute.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CollectivePermute.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -84,4 +88,30 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<CollectivePermute<T>> {
+    /**
+     * The local input to be permuted. Currently only supports float and
+     * bfloat16.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A tensor with shape [num_pairs, 2].
+     */
+    public final Operand<TInt32> sourceTargetPairs;
+
+    /**
+     * The type of elements to be exchanged.
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new CollectivePermute<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      sourceTargetPairs = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompilationResult.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompilationResult.java
index 7811ec35db4..450c390d6e2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompilationResult.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompilationResult.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -73,4 +76,11 @@ public Output<TString> output() {
   public Output<TString> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<CompilationResult> {
+    public Inputs(GraphOperation op) {
+      super(new CompilationResult(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Compile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Compile.java
index 7442a387d67..ecf0ae4cc3f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Compile.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Compile.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
@@ -82,11 +85,11 @@ private Compile(Operation operation) {
    * Factory method to create a class wrapping a new TPUCompile operation.
    *
    * @param scope current scope
-   * @param dynamicShapes the dynamicShapes value
-   * @param guaranteedConstants the guaranteedConstants value
-   * @param numComputations the value of the numComputations property
-   * @param function the value of the function property
-   * @param metadata the value of the metadata property
+   * @param dynamicShapes The dynamicShapes value
+   * @param guaranteedConstants The guaranteedConstants value
+   * @param numComputations The value of the numComputations attribute
+   * @param function The value of the function attribute
+   * @param metadata The value of the metadata attribute
    * @return a new instance of Compile
    */
   @Endpoint(
@@ -130,4 +133,39 @@ public List<Output<TString>> program() {
   public List<Output<TBool>> mayModifyVariables() {
     return mayModifyVariables;
   }
+
+  public static class Inputs extends RawOpInputs<Compile> {
+    /**
+     * The dynamicShapes input
+     */
+    public final Iterable<Operand<TInt64>> dynamicShapes;
+
+    /**
+     * The guaranteedConstants input
+     */
+    public final Iterable<Operand<?>> guaranteedConstants;
+
+    /**
+     * The metadata attribute
+     */
+    public final String metadata;
+
+    /**
+     * The TguaranteedConstants attribute
+     */
+    public final DataType[] TguaranteedConstants;
+
+    public Inputs(GraphOperation op) {
+      super(new Compile(op), op, Arrays.asList("metadata", "Tguaranteed_constants"));
+      int inputIndex = 0;
+      int dynamicShapesLength = op.inputListLength("dynamic_shapes");
+      dynamicShapes = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, dynamicShapesLength));
+      inputIndex += dynamicShapesLength;
+      int guaranteedConstantsLength = op.inputListLength("guaranteed_constants");
+      guaranteedConstants = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, guaranteedConstantsLength));
+      inputIndex += guaranteedConstantsLength;
+      metadata = op.attributes().getAttrString("metadata");
+      TguaranteedConstants = op.attributes().getAttrTypeList("Tguaranteed_constants");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompileSucceededAssert.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompileSucceededAssert.java
index 31e5550bdb8..d4a2b599e91 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompileSucceededAssert.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CompileSucceededAssert.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -49,7 +52,7 @@ private CompileSucceededAssert(Operation operation) {
    * Factory method to create a class wrapping a new TPUCompileSucceededAssert operation.
    *
    * @param scope current scope
-   * @param compilationStatus the compilationStatus value
+   * @param compilationStatus The compilationStatus value
    * @return a new instance of CompileSucceededAssert
    */
   @Endpoint(
@@ -60,4 +63,17 @@ public static CompileSucceededAssert create(Scope scope, Operand<TString> compil
     opBuilder.addInput(compilationStatus.asOutput());
     return new CompileSucceededAssert(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<CompileSucceededAssert> {
+    /**
+     * The compilationStatus input
+     */
+    public final Operand<TString> compilationStatus;
+
+    public Inputs(GraphOperation op) {
+      super(new CompileSucceededAssert(op), op, Arrays.asList());
+      int inputIndex = 0;
+      compilationStatus = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureDistributedTPU.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureDistributedTPU.java
index bfbed670d1e..8c951410670 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureDistributedTPU.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureDistributedTPU.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -216,4 +219,42 @@ public Options compilationFailureClosesChips(Boolean compilationFailureClosesChi
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ConfigureDistributedTPU> {
+    /**
+     * Reserved. Do not use.
+     */
+    public final String embeddingConfig;
+
+    /**
+     * Serialized tensorflow.tpu.TPUEmbeddingConfiguration that
+     * describes the embedding lookups of the program.
+     */
+    public final String tpuEmbeddingConfig;
+
+    /**
+     * Reserved. Do not use.
+     */
+    public final boolean isGlobalInit;
+
+    /**
+     * The enableWholeMeshCompilations attribute
+     */
+    public final boolean enableWholeMeshCompilations;
+
+    /**
+     * The compilationFailureClosesChips attribute
+     */
+    public final boolean compilationFailureClosesChips;
+
+    public Inputs(GraphOperation op) {
+      super(new ConfigureDistributedTPU(op), op, Arrays.asList("embedding_config", "tpu_embedding_config", "is_global_init", "enable_whole_mesh_compilations", "compilation_failure_closes_chips"));
+      int inputIndex = 0;
+      embeddingConfig = op.attributes().getAttrString("embedding_config");
+      tpuEmbeddingConfig = op.attributes().getAttrString("tpu_embedding_config");
+      isGlobalInit = op.attributes().getAttrBool("is_global_init");
+      enableWholeMeshCompilations = op.attributes().getAttrBool("enable_whole_mesh_compilations");
+      compilationFailureClosesChips = op.attributes().getAttrBool("compilation_failure_closes_chips");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureTPUEmbedding.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureTPUEmbedding.java
index 0a9aa88e9a5..029bcc9974a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureTPUEmbedding.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ConfigureTPUEmbedding.java
@@ -17,9 +17,12 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 
@@ -52,4 +55,18 @@ public static ConfigureTPUEmbedding create(Scope scope, String config) {
     opBuilder.setAttr("config", config);
     return new ConfigureTPUEmbedding(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ConfigureTPUEmbedding> {
+    /**
+     * Serialized tensorflow.tpu.TPUEmbeddingConfiguration that
+     * describes the embedding lookups of the program.
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new ConfigureTPUEmbedding(op), op, Arrays.asList("config"));
+      int inputIndex = 0;
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java
index c1267521173..52c9e9a4bf0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
 
@@ -86,4 +90,31 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TNumber> extends RawOpInputs<CrossReplicaSum<T>> {
+    /**
+     * The local input to the sum.
+     */
+    public final Operand<T> input;
+
+    /**
+     * An int32 tensor with shape
+     * [num_groups, num_replicas_per_group]. {@code group_assignment[i]} represents the
+     * replica ids in the ith subgroup.
+     */
+    public final Operand<TInt32> groupAssignment;
+
+    /**
+     * The type of elements to be summed.
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new CrossReplicaSum<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      groupAssignment = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EmbeddingActivations.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EmbeddingActivations.java
index 0c98c598a4c..16e93996681 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EmbeddingActivations.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EmbeddingActivations.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -86,4 +89,37 @@ public Output<TFloat32> output() {
   public Output<TFloat32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<EmbeddingActivations> {
+    /**
+     * A trainable variable, enabling optimizers to find this op.
+     */
+    public final Operand<TFloat32> embeddingVariable;
+
+    /**
+     * The embedding activations Tensor to return.
+     */
+    public final Operand<TFloat32> slicedActivations;
+
+    /**
+     * The id of the table in the embedding layer configuration from which
+     * these activations were computed.
+     */
+    public final long tableId;
+
+    /**
+     * Identifier of the set of embedding indices which produced these
+     * activations.
+     */
+    public final long lookupId;
+
+    public Inputs(GraphOperation op) {
+      super(new EmbeddingActivations(op), op, Arrays.asList("table_id", "lookup_id"));
+      int inputIndex = 0;
+      embeddingVariable = (Operand<TFloat32>) op.input(inputIndex++);
+      slicedActivations = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      lookupId = op.attributes().getAttrInt("lookup_id");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java
index d80625786c5..dc6902258ab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -103,4 +106,36 @@ public Options deviceOrdinal(Long deviceOrdinal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EnqueueTPUEmbeddingIntegerBatch> {
+    /**
+     * A list of 1D tensors, one for each embedding table, containing the
+     * indices into the tables.
+     */
+    public final Iterable<Operand<TInt32>> batch;
+
+    /**
+     * A string input that overrides the mode specified in the
+     * TPUEmbeddingConfiguration. Supported values are {'unspecified', 'inference',
+     * 'training', 'backward_pass_only'}. When set to 'unspecified', the mode set
+     * in TPUEmbeddingConfiguration is used, otherwise mode_override is used.
+     */
+    public final Operand<TString> modeOverride;
+
+    /**
+     * The TPU device to use. Should be >= 0 and less than the number
+     * of TPU cores in the task on which the node is placed.
+     */
+    public final long deviceOrdinal;
+
+    public Inputs(GraphOperation op) {
+      super(new EnqueueTPUEmbeddingIntegerBatch(op), op, Arrays.asList("device_ordinal"));
+      int inputIndex = 0;
+      int batchLength = op.inputListLength("batch");
+      batch = Arrays.asList((Operand<TInt32>[]) op.inputList(inputIndex, batchLength));
+      inputIndex += batchLength;
+      modeOverride = (Operand<TString>) op.input(inputIndex++);
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java
index e63d8e5e7c1..8128d89956f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -161,7 +164,7 @@ public static Options combiners(List<String> combiners) {
    * all tables.
    * @return this Options instance.
    */
-  public static Options combiners(String[] combiners) {
+  public static Options combiners(String... combiners) {
     return new Options().combiners(combiners);
   }
 
@@ -181,7 +184,7 @@ public static Options maxSequenceLengths(List<Long> maxSequenceLengths) {
    * @param maxSequenceLengths the maxSequenceLengths option
    * @return this Options instance.
    */
-  public static Options maxSequenceLengths(Long[] maxSequenceLengths) {
+  public static Options maxSequenceLengths(Long... maxSequenceLengths) {
     return new Options().maxSequenceLengths(maxSequenceLengths);
   }
 
@@ -201,7 +204,7 @@ public static Options numFeatures(List<Long> numFeatures) {
    * @param numFeatures the numFeatures option
    * @return this Options instance.
    */
-  public static Options numFeatures(Long[] numFeatures) {
+  public static Options numFeatures(Long... numFeatures) {
     return new Options().numFeatures(numFeatures);
   }
 
@@ -308,4 +311,109 @@ public Options numFeatures(Long... numFeatures) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EnqueueTPUEmbeddingRaggedTensorBatch> {
+    /**
+     * A list of rank 1 Tensors specifying the break points for splitting
+     * embedding_indices and aggregation_weights into rows.
+     * It corresponds to ids.row_splits in embedding_lookup(), when ids is a
+     * RaggedTensor.
+     */
+    public final Iterable<Operand<? extends TNumber>> sampleSplits;
+
+    /**
+     * A list of rank 1 Tensors, indices into the embedding tables.
+     * It corresponds to ids.values in embedding_lookup(), when ids is a RaggedTensor.
+     */
+    public final Iterable<Operand<? extends TNumber>> embeddingIndices;
+
+    /**
+     * A list of rank 1 Tensors containing per training example
+     * aggregation weights. It corresponds to the values field of a RaggedTensor
+     * with the same row_splits as ids in embedding_lookup(), when ids is a
+     * RaggedTensor.
+     */
+    public final Iterable<Operand<? extends TNumber>> aggregationWeights;
+
+    /**
+     * A string input that overrides the mode specified in the
+     * TPUEmbeddingConfiguration. Supported values are {'unspecified', 'inference',
+     * 'training', 'backward_pass_only'}. When set to 'unspecified', the mode set
+     * in TPUEmbeddingConfiguration is used, otherwise mode_override is used.
+     */
+    public final Operand<TString> modeOverride;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The T3 attribute
+     */
+    public final DataType T3;
+
+    /**
+     * The TPU device to use. Should be >= 0 and less than the number
+     * of TPU cores in the task on which the node is placed.
+     */
+    public final long deviceOrdinal;
+
+    /**
+     * A list of string scalars, one for each embedding table that specify
+     * how to normalize the embedding activations after weighted summation.
+     * Supported combiners are 'mean', 'sum', or 'sqrtn'. It is invalid to have
+     * the sum of the weights be 0 for 'mean' or the sum of the squared weights be
+     * 0 for 'sqrtn'. If combiners isn't passed, the default is to use 'sum' for
+     * all tables.
+     */
+    public final String[] combiners;
+
+    /**
+     * A list of integers specifying the identifier of the embedding table
+     * (offset of TableDescriptor in the TPUEmbeddingConfiguration) to lookup the
+     * corresponding input. The ith input is looked up using table_ids[i]. The size
+     * of the table_ids list must be equal to that of sample_indices,
+     * embedding_indices and aggregation_weights.
+     */
+    public final long[] tableIds;
+
+    /**
+     * The maxSequenceLengths attribute
+     */
+    public final long[] maxSequenceLengths;
+
+    /**
+     * The numFeatures attribute
+     */
+    public final long[] numFeatures;
+
+    public Inputs(GraphOperation op) {
+      super(new EnqueueTPUEmbeddingRaggedTensorBatch(op), op, Arrays.asList("T1", "T2", "T3", "device_ordinal", "combiners", "table_ids", "max_sequence_lengths", "num_features"));
+      int inputIndex = 0;
+      int sampleSplitsLength = op.inputListLength("sample_splits");
+      sampleSplits = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, sampleSplitsLength));
+      inputIndex += sampleSplitsLength;
+      int embeddingIndicesLength = op.inputListLength("embedding_indices");
+      embeddingIndices = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, embeddingIndicesLength));
+      inputIndex += embeddingIndicesLength;
+      int aggregationWeightsLength = op.inputListLength("aggregation_weights");
+      aggregationWeights = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, aggregationWeightsLength));
+      inputIndex += aggregationWeightsLength;
+      modeOverride = (Operand<TString>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      T3 = op.attributes().getAttrType("T3");
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+      combiners = op.attributes().getAttrStringList("combiners");
+      tableIds = op.attributes().getAttrIntList("table_ids");
+      maxSequenceLengths = op.attributes().getAttrIntList("max_sequence_lengths");
+      numFeatures = op.attributes().getAttrIntList("num_features");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java
index af6164c23e5..b94730af5f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -136,7 +139,7 @@ public static Options combiners(List<String> combiners) {
    * all tables.
    * @return this Options instance.
    */
-  public static Options combiners(String[] combiners) {
+  public static Options combiners(String... combiners) {
     return new Options().combiners(combiners);
   }
 
@@ -195,4 +198,85 @@ public Options combiners(String... combiners) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EnqueueTPUEmbeddingSparseBatch> {
+    /**
+     * A list of rank 1 Tensors specifying the training example and
+     * feature to which the corresponding embedding_indices and aggregation_weights
+     * values belong. sample_indices[i] must equal b * nf + f, where nf is the
+     * number of features from the corresponding table, f is in [0, nf), and
+     * b is in [0, batch size).
+     */
+    public final Iterable<Operand<? extends TNumber>> sampleIndices;
+
+    /**
+     * A list of rank 1 Tensors, indices into the embedding tables.
+     */
+    public final Iterable<Operand<? extends TNumber>> embeddingIndices;
+
+    /**
+     * A list of rank 1 Tensors containing per sample -- i.e. per
+     * (training example, feature) -- aggregation weights.
+     */
+    public final Iterable<Operand<? extends TNumber>> aggregationWeights;
+
+    /**
+     * A string input that overrides the mode specified in the
+     * TPUEmbeddingConfiguration. Supported values are {'unspecified', 'inference',
+     * 'training', 'backward_pass_only'}. When set to 'unspecified', the mode set
+     * in TPUEmbeddingConfiguration is used, otherwise mode_override is used.
+     */
+    public final Operand<TString> modeOverride;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The T3 attribute
+     */
+    public final DataType T3;
+
+    /**
+     * The TPU device to use. Should be >= 0 and less than the number
+     * of TPU cores in the task on which the node is placed.
+     */
+    public final long deviceOrdinal;
+
+    /**
+     * A list of string scalars, one for each embedding table that specify
+     * how to normalize the embedding activations after weighted summation.
+     * Supported combiners are 'mean', 'sum', or 'sqrtn'. It is invalid to have
+     * the sum of the weights be 0 for 'mean' or the sum of the squared weights be
+     * 0 for 'sqrtn'. If combiners isn't passed, the default is to use 'sum' for
+     * all tables.
+     */
+    public final String[] combiners;
+
+    public Inputs(GraphOperation op) {
+      super(new EnqueueTPUEmbeddingSparseBatch(op), op, Arrays.asList("T1", "T2", "T3", "device_ordinal", "combiners"));
+      int inputIndex = 0;
+      int sampleIndicesLength = op.inputListLength("sample_indices");
+      sampleIndices = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, sampleIndicesLength));
+      inputIndex += sampleIndicesLength;
+      int embeddingIndicesLength = op.inputListLength("embedding_indices");
+      embeddingIndices = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, embeddingIndicesLength));
+      inputIndex += embeddingIndicesLength;
+      int aggregationWeightsLength = op.inputListLength("aggregation_weights");
+      aggregationWeights = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, aggregationWeightsLength));
+      inputIndex += aggregationWeightsLength;
+      modeOverride = (Operand<TString>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      T3 = op.attributes().getAttrType("T3");
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+      combiners = op.attributes().getAttrStringList("combiners");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java
index a153a5c005e..d431aec3598 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
 
@@ -159,7 +162,7 @@ public static Options combiners(List<String> combiners) {
    * all tables.
    * @return this Options instance.
    */
-  public static Options combiners(String[] combiners) {
+  public static Options combiners(String... combiners) {
     return new Options().combiners(combiners);
   }
 
@@ -179,7 +182,7 @@ public static Options maxSequenceLengths(List<Long> maxSequenceLengths) {
    * @param maxSequenceLengths the maxSequenceLengths option
    * @return this Options instance.
    */
-  public static Options maxSequenceLengths(Long[] maxSequenceLengths) {
+  public static Options maxSequenceLengths(Long... maxSequenceLengths) {
     return new Options().maxSequenceLengths(maxSequenceLengths);
   }
 
@@ -199,7 +202,7 @@ public static Options numFeatures(List<Long> numFeatures) {
    * @param numFeatures the numFeatures option
    * @return this Options instance.
    */
-  public static Options numFeatures(Long[] numFeatures) {
+  public static Options numFeatures(Long... numFeatures) {
     return new Options().numFeatures(numFeatures);
   }
 
@@ -306,4 +309,107 @@ public Options numFeatures(Long... numFeatures) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<EnqueueTPUEmbeddingSparseTensorBatch> {
+    /**
+     * A list of rank 1 Tensors specifying the training example to
+     * which the corresponding embedding_indices and aggregation_weights values
+     * belong. It corresponds to sp_ids.indices[:,0] in  embedding_lookup_sparse().
+     */
+    public final Iterable<Operand<? extends TNumber>> sampleIndices;
+
+    /**
+     * A list of rank 1 Tensors, indices into the embedding tables.
+     * It corresponds to sp_ids.values in embedding_lookup_sparse().
+     */
+    public final Iterable<Operand<? extends TNumber>> embeddingIndices;
+
+    /**
+     * A list of rank 1 Tensors containing per training example
+     * aggregation weights. It corresponds to sp_weights.values in
+     * embedding_lookup_sparse().
+     */
+    public final Iterable<Operand<? extends TNumber>> aggregationWeights;
+
+    /**
+     * A string input that overrides the mode specified in the
+     * TPUEmbeddingConfiguration. Supported values are {'unspecified', 'inference',
+     * 'training', 'backward_pass_only'}. When set to 'unspecified', the mode set
+     * in TPUEmbeddingConfiguration is used, otherwise mode_override is used.
+     */
+    public final Operand<TString> modeOverride;
+
+    /**
+     * The T1 attribute
+     */
+    public final DataType T1;
+
+    /**
+     * The T2 attribute
+     */
+    public final DataType T2;
+
+    /**
+     * The T3 attribute
+     */
+    public final DataType T3;
+
+    /**
+     * The TPU device to use. Should be >= 0 and less than the number
+     * of TPU cores in the task on which the node is placed.
+     */
+    public final long deviceOrdinal;
+
+    /**
+     * A list of string scalars, one for each embedding table that specify
+     * how to normalize the embedding activations after weighted summation.
+     * Supported combiners are 'mean', 'sum', or 'sqrtn'. It is invalid to have
+     * the sum of the weights be 0 for 'mean' or the sum of the squared weights be
+     * 0 for 'sqrtn'. If combiners isn't passed, the default is to use 'sum' for
+     * all tables.
+     */
+    public final String[] combiners;
+
+    /**
+     * A list of integers specifying the identifier of the embedding table
+     * (offset of TableDescriptor in the TPUEmbeddingConfiguration) to lookup the
+     * corresponding input. The ith input is looked up using table_ids[i]. The size
+     * of the table_ids list must be equal to that of sample_indices,
+     * embedding_indices and aggregation_weights.
+     */
+    public final long[] tableIds;
+
+    /**
+     * The maxSequenceLengths attribute
+     */
+    public final long[] maxSequenceLengths;
+
+    /**
+     * The numFeatures attribute
+     */
+    public final long[] numFeatures;
+
+    public Inputs(GraphOperation op) {
+      super(new EnqueueTPUEmbeddingSparseTensorBatch(op), op, Arrays.asList("T1", "T2", "T3", "device_ordinal", "combiners", "table_ids", "max_sequence_lengths", "num_features"));
+      int inputIndex = 0;
+      int sampleIndicesLength = op.inputListLength("sample_indices");
+      sampleIndices = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, sampleIndicesLength));
+      inputIndex += sampleIndicesLength;
+      int embeddingIndicesLength = op.inputListLength("embedding_indices");
+      embeddingIndices = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, embeddingIndicesLength));
+      inputIndex += embeddingIndicesLength;
+      int aggregationWeightsLength = op.inputListLength("aggregation_weights");
+      aggregationWeights = Arrays.asList((Operand<? extends TNumber>[]) op.inputList(inputIndex, aggregationWeightsLength));
+      inputIndex += aggregationWeightsLength;
+      modeOverride = (Operand<TString>) op.input(inputIndex++);
+      T1 = op.attributes().getAttrType("T1");
+      T2 = op.attributes().getAttrType("T2");
+      T3 = op.attributes().getAttrType("T3");
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+      combiners = op.attributes().getAttrStringList("combiners");
+      tableIds = op.attributes().getAttrIntList("table_ids");
+      maxSequenceLengths = op.attributes().getAttrIntList("max_sequence_lengths");
+      numFeatures = op.attributes().getAttrIntList("num_features");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Execute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Execute.java
index d525ac67f35..14c939ac6f9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Execute.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Execute.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -60,9 +63,9 @@ private Execute(Operation operation) {
    * Factory method to create a class wrapping a new TPUExecute operation.
    *
    * @param scope current scope
-   * @param args the args value
-   * @param key the key value
-   * @param Tresults the value of the Tresults property
+   * @param args The args value
+   * @param key The key value
+   * @param Tresults The value of the Tresults attribute
    * @return a new instance of Execute
    */
   @Endpoint(
@@ -91,4 +94,37 @@ public List<Output<?>> results() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) results.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<Execute> {
+    /**
+     * The args input
+     */
+    public final Iterable<Operand<?>> args;
+
+    /**
+     * The key input
+     */
+    public final Operand<TString> key;
+
+    /**
+     * The Targs attribute
+     */
+    public final DataType[] Targs;
+
+    /**
+     * The Tresults attribute
+     */
+    public final DataType[] Tresults;
+
+    public Inputs(GraphOperation op) {
+      super(new Execute(op), op, Arrays.asList("Targs", "Tresults"));
+      int inputIndex = 0;
+      int argsLength = op.inputListLength("args");
+      args = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argsLength));
+      inputIndex += argsLength;
+      key = (Operand<TString>) op.input(inputIndex++);
+      Targs = op.attributes().getAttrTypeList("Targs");
+      Tresults = op.attributes().getAttrTypeList("Tresults");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ExecuteAndUpdateVariables.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ExecuteAndUpdateVariables.java
index 9b3cbe0100e..260af4b758a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ExecuteAndUpdateVariables.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ExecuteAndUpdateVariables.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -66,11 +69,11 @@ private ExecuteAndUpdateVariables(Operation operation) {
    * Factory method to create a class wrapping a new TPUExecuteAndUpdateVariables operation.
    *
    * @param scope current scope
-   * @param args the args value
-   * @param key the key value
-   * @param Tresults the value of the Tresults property
-   * @param deviceVarReadsIndices the value of the deviceVarReadsIndices property
-   * @param deviceVarUpdatesIndices the value of the deviceVarUpdatesIndices property
+   * @param args The args value
+   * @param key The key value
+   * @param Tresults The value of the Tresults attribute
+   * @param deviceVarReadsIndices The value of the deviceVarReadsIndices attribute
+   * @param deviceVarUpdatesIndices The value of the deviceVarUpdatesIndices attribute
    * @return a new instance of ExecuteAndUpdateVariables
    */
   @Endpoint(
@@ -110,4 +113,49 @@ public List<Output<?>> results() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) results.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<ExecuteAndUpdateVariables> {
+    /**
+     * The args input
+     */
+    public final Iterable<Operand<?>> args;
+
+    /**
+     * The key input
+     */
+    public final Operand<TString> key;
+
+    /**
+     * The Targs attribute
+     */
+    public final DataType[] Targs;
+
+    /**
+     * The Tresults attribute
+     */
+    public final DataType[] Tresults;
+
+    /**
+     * The deviceVarReadsIndices attribute
+     */
+    public final long[] deviceVarReadsIndices;
+
+    /**
+     * The deviceVarUpdatesIndices attribute
+     */
+    public final long[] deviceVarUpdatesIndices;
+
+    public Inputs(GraphOperation op) {
+      super(new ExecuteAndUpdateVariables(op), op, Arrays.asList("Targs", "Tresults", "device_var_reads_indices", "device_var_updates_indices"));
+      int inputIndex = 0;
+      int argsLength = op.inputListLength("args");
+      args = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argsLength));
+      inputIndex += argsLength;
+      key = (Operand<TString>) op.input(inputIndex++);
+      Targs = op.attributes().getAttrTypeList("Targs");
+      Tresults = op.attributes().getAttrTypeList("Tresults");
+      deviceVarReadsIndices = op.attributes().getAttrIntList("device_var_reads_indices");
+      deviceVarUpdatesIndices = op.attributes().getAttrIntList("device_var_updates_indices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java
index 9133d876829..4f5e1a1dd73 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,8 +26,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -80,4 +84,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<InfeedDequeue<?>> {
+    /**
+     * The type of elements in the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the tensor.
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new InfeedDequeue<>(op), op, Arrays.asList("dtype", "shape"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java
index 25c5bb5f3d2..5dd69faeae1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -88,4 +91,23 @@ public List<Output<?>> outputs() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<InfeedDequeueTuple> {
+    /**
+     * The element types of each element in `outputs`.
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The shapes of each tensor in `outputs`.
+     */
+    public final Shape[] shapes;
+
+    public Inputs(GraphOperation op) {
+      super(new InfeedDequeueTuple(op), op, Arrays.asList("dtypes", "shapes"));
+      int inputIndex = 0;
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      shapes = op.attributes().getAttrShapeList("shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java
index 54c1c436dae..07d0f827355 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java
@@ -19,13 +19,16 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -106,7 +109,7 @@ public static Options layout(List<Long> layout) {
    * be computed by the infeed operation.
    * @return this Options instance.
    */
-  public static Options layout(Long[] layout) {
+  public static Options layout(Long... layout) {
     return new Options().layout(layout);
   }
 
@@ -185,4 +188,45 @@ public Options deviceOrdinal(Long deviceOrdinal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<InfeedEnqueue> {
+    /**
+     * A tensor that will be provided using the infeed mechanism.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The type of elements in the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the tensor.
+     */
+    public final Shape shape;
+
+    /**
+     * A vector holding the requested layout in minor-to-major sequence.
+     * If a layout attribute is passed, but its values are all -1, the layout will
+     * be computed by the infeed operation.
+     */
+    public final long[] layout;
+
+    /**
+     * The TPU device to use. This should be -1 when the Op
+     * is running on a TPU device, and >= 0 when the Op is running on the CPU
+     * device.
+     */
+    public final long deviceOrdinal;
+
+    public Inputs(GraphOperation op) {
+      super(new InfeedEnqueue(op), op, Arrays.asList("dtype", "shape", "layout", "device_ordinal"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      layout = op.attributes().getAttrIntList("layout");
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueuePrelinearizedBuffer.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueuePrelinearizedBuffer.java
index e2e31f1e1a4..09c8647caf7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueuePrelinearizedBuffer.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueuePrelinearizedBuffer.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.family.TType;
@@ -95,4 +98,24 @@ public Options deviceOrdinal(Long deviceOrdinal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<InfeedEnqueuePrelinearizedBuffer> {
+    /**
+     * A variant tensor representing linearized output.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The TPU device to use. This should be -1 when the Op is running on a TPU device
+     * and = 0 when the Op is running on the CPU device.
+     */
+    public final long deviceOrdinal;
+
+    public Inputs(GraphOperation op) {
+      super(new InfeedEnqueuePrelinearizedBuffer(op), op, Arrays.asList("device_ordinal"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java
index 1e4e5275ab9..1704d634091 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * Feeds multiple Tensor values into the computation as an XLA tuple.
@@ -101,7 +104,7 @@ public static Options layouts(List<Long> layouts) {
    * corresponding layout will be computed by the infeed operation.
    * @return this Options instance.
    */
-  public static Options layouts(Long[] layouts) {
+  public static Options layouts(Long... layouts) {
     return new Options().layouts(layouts);
   }
 
@@ -169,4 +172,48 @@ public Options deviceOrdinal(Long deviceOrdinal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<InfeedEnqueueTuple> {
+    /**
+     * A list of tensors that will be provided using the infeed mechanism.
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The element types of each element in `inputs`.
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The shapes of each tensor in `inputs`.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * A vector holding the requested layout in minor-to-major sequence for
+     * all the tuple shapes, in the order the shapes appear in the "shapes" input.
+     * The layout elements for a sub-shape can be set to -1, in which case the
+     * corresponding layout will be computed by the infeed operation.
+     */
+    public final long[] layouts;
+
+    /**
+     * The TPU device to use. This should be -1 when the Op
+     * is running on a TPU device, and >= 0 when the Op is running on the CPU
+     * device.
+     */
+    public final long deviceOrdinal;
+
+    public Inputs(GraphOperation op) {
+      super(new InfeedEnqueueTuple(op), op, Arrays.asList("dtypes", "shapes", "layouts", "device_ordinal"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      layouts = op.attributes().getAttrIntList("layouts");
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParameters.java
index 9fbc8ce5bb3..fa607e3d65f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -50,8 +53,8 @@ private LoadTPUEmbeddingADAMParameters(Operation operation) {
    * @param parameters Value of parameters used in the ADAM optimization algorithm.
    * @param momenta Value of momenta used in the ADAM optimization algorithm.
    * @param velocities Value of velocities used in the ADAM optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingADAMParameters
    */
@@ -159,4 +162,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingADAMParameters> {
+    /**
+     * Value of parameters used in the ADAM optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of momenta used in the ADAM optimization algorithm.
+     */
+    public final Operand<TFloat32> momenta;
+
+    /**
+     * Value of velocities used in the ADAM optimization algorithm.
+     */
+    public final Operand<TFloat32> velocities;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingADAMParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      momenta = (Operand<TFloat32>) op.input(inputIndex++);
+      velocities = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParametersGradAccumDebug.java
index e6a19adf6b8..3689a78b02f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private LoadTPUEmbeddingADAMParametersGradAccumDebug(Operation operation) {
    * @param momenta Value of momenta used in the ADAM optimization algorithm.
    * @param velocities Value of velocities used in the ADAM optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the ADAM optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingADAMParametersGradAccumDebug
    */
@@ -161,4 +164,65 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingADAMParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the ADAM optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of momenta used in the ADAM optimization algorithm.
+     */
+    public final Operand<TFloat32> momenta;
+
+    /**
+     * Value of velocities used in the ADAM optimization algorithm.
+     */
+    public final Operand<TFloat32> velocities;
+
+    /**
+     * Value of gradient_accumulators used in the ADAM optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingADAMParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      momenta = (Operand<TFloat32>) op.input(inputIndex++);
+      velocities = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParameters.java
index 9ef74ac8b76..bc573e662ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -50,8 +53,8 @@ private LoadTPUEmbeddingAdadeltaParameters(Operation operation) {
    * @param parameters Value of parameters used in the Adadelta optimization algorithm.
    * @param accumulators Value of accumulators used in the Adadelta optimization algorithm.
    * @param updates Value of updates used in the Adadelta optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingAdadeltaParameters
    */
@@ -159,4 +162,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingAdadeltaParameters> {
+    /**
+     * Value of parameters used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * Value of updates used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> updates;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingAdadeltaParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      updates = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.java
index 6a8bb70e0aa..55c53423e92 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private LoadTPUEmbeddingAdadeltaParametersGradAccumDebug(Operation operation) {
    * @param accumulators Value of accumulators used in the Adadelta optimization algorithm.
    * @param updates Value of updates used in the Adadelta optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the Adadelta optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingAdadeltaParametersGradAccumDebug
    */
@@ -161,4 +164,65 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingAdadeltaParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * Value of updates used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> updates;
+
+    /**
+     * Value of gradient_accumulators used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingAdadeltaParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      updates = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParameters.java
index ec3eb041f92..4932fcb0f30 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -49,8 +52,8 @@ private LoadTPUEmbeddingAdagradParameters(Operation operation) {
    * @param scope current scope
    * @param parameters Value of parameters used in the Adagrad optimization algorithm.
    * @param accumulators Value of accumulators used in the Adagrad optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingAdagradParameters
    */
@@ -156,4 +159,53 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingAdagradParameters> {
+    /**
+     * Value of parameters used in the Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingAdagradParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParametersGradAccumDebug.java
index 79df9ecd358..6c6982d38b9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingAdagradParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -50,8 +53,8 @@ private LoadTPUEmbeddingAdagradParametersGradAccumDebug(Operation operation) {
    * @param parameters Value of parameters used in the Adagrad optimization algorithm.
    * @param accumulators Value of accumulators used in the Adagrad optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the Adagrad optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingAdagradParametersGradAccumDebug
    */
@@ -159,4 +162,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingAdagradParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * Value of gradient_accumulators used in the Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingAdagradParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingCenteredRMSPropParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingCenteredRMSPropParameters.java
index 9d5f01cf52f..5aa18411600 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingCenteredRMSPropParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingCenteredRMSPropParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private LoadTPUEmbeddingCenteredRMSPropParameters(Operation operation) {
    * @param ms Value of ms used in the centered RMSProp optimization algorithm.
    * @param mom Value of mom used in the centered RMSProp optimization algorithm.
    * @param mg Value of mg used in the centered RMSProp optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingCenteredRMSPropParameters
    */
@@ -161,4 +164,65 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingCenteredRMSPropParameters> {
+    /**
+     * Value of parameters used in the centered RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of ms used in the centered RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> ms;
+
+    /**
+     * Value of mom used in the centered RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> mom;
+
+    /**
+     * Value of mg used in the centered RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> mg;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingCenteredRMSPropParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      ms = (Operand<TFloat32>) op.input(inputIndex++);
+      mom = (Operand<TFloat32>) op.input(inputIndex++);
+      mg = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParameters.java
index 9b31d9975fc..77c88b54456 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -50,8 +53,8 @@ private LoadTPUEmbeddingFTRLParameters(Operation operation) {
    * @param parameters Value of parameters used in the FTRL optimization algorithm.
    * @param accumulators Value of accumulators used in the FTRL optimization algorithm.
    * @param linears Value of linears used in the FTRL optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingFTRLParameters
    */
@@ -159,4 +162,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingFTRLParameters> {
+    /**
+     * Value of parameters used in the FTRL optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the FTRL optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * Value of linears used in the FTRL optimization algorithm.
+     */
+    public final Operand<TFloat32> linears;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingFTRLParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      linears = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParametersGradAccumDebug.java
index 422515c24a3..78438e9fec9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private LoadTPUEmbeddingFTRLParametersGradAccumDebug(Operation operation) {
    * @param accumulators Value of accumulators used in the FTRL optimization algorithm.
    * @param linears Value of linears used in the FTRL optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the FTRL optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingFTRLParametersGradAccumDebug
    */
@@ -161,4 +164,65 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingFTRLParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the FTRL optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the FTRL optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * Value of linears used in the FTRL optimization algorithm.
+     */
+    public final Operand<TFloat32> linears;
+
+    /**
+     * Value of gradient_accumulators used in the FTRL optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingFTRLParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      linears = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMDLAdagradLightParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMDLAdagradLightParameters.java
index 328d83e2c87..111f9c8541b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMDLAdagradLightParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMDLAdagradLightParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private LoadTPUEmbeddingMDLAdagradLightParameters(Operation operation) {
    * @param accumulators Value of accumulators used in the MDL Adagrad Light optimization algorithm.
    * @param weights Value of weights used in the MDL Adagrad Light optimization algorithm.
    * @param benefits Value of benefits used in the MDL Adagrad Light optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingMDLAdagradLightParameters
    */
@@ -161,4 +164,65 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingMDLAdagradLightParameters> {
+    /**
+     * Value of parameters used in the MDL Adagrad Light optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the MDL Adagrad Light optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * Value of weights used in the MDL Adagrad Light optimization algorithm.
+     */
+    public final Operand<TFloat32> weights;
+
+    /**
+     * Value of benefits used in the MDL Adagrad Light optimization algorithm.
+     */
+    public final Operand<TFloat32> benefits;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingMDLAdagradLightParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      weights = (Operand<TFloat32>) op.input(inputIndex++);
+      benefits = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParameters.java
index 2b448ef111d..1abf0471457 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -49,8 +52,8 @@ private LoadTPUEmbeddingMomentumParameters(Operation operation) {
    * @param scope current scope
    * @param parameters Value of parameters used in the Momentum optimization algorithm.
    * @param momenta Value of momenta used in the Momentum optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingMomentumParameters
    */
@@ -156,4 +159,53 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingMomentumParameters> {
+    /**
+     * Value of parameters used in the Momentum optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of momenta used in the Momentum optimization algorithm.
+     */
+    public final Operand<TFloat32> momenta;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingMomentumParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      momenta = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParametersGradAccumDebug.java
index 8bfd0dc74eb..ba22bbb8363 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingMomentumParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -50,8 +53,8 @@ private LoadTPUEmbeddingMomentumParametersGradAccumDebug(Operation operation) {
    * @param parameters Value of parameters used in the Momentum optimization algorithm.
    * @param momenta Value of momenta used in the Momentum optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the Momentum optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingMomentumParametersGradAccumDebug
    */
@@ -159,4 +162,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingMomentumParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the Momentum optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of momenta used in the Momentum optimization algorithm.
+     */
+    public final Operand<TFloat32> momenta;
+
+    /**
+     * Value of gradient_accumulators used in the Momentum optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingMomentumParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      momenta = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParameters.java
index 90bd696b108..9306ca0d29f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -49,8 +52,8 @@ private LoadTPUEmbeddingProximalAdagradParameters(Operation operation) {
    * @param scope current scope
    * @param parameters Value of parameters used in the proximal Adagrad optimization algorithm.
    * @param accumulators Value of accumulators used in the proximal Adagrad optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingProximalAdagradParameters
    */
@@ -157,4 +160,53 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingProximalAdagradParameters> {
+    /**
+     * Value of parameters used in the proximal Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the proximal Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingProximalAdagradParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.java
index 7fa88cc5273..8f1a7957da3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -50,8 +53,8 @@ private LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug(Operation operat
    * @param parameters Value of parameters used in the proximal Adagrad optimization algorithm.
    * @param accumulators Value of accumulators used in the proximal Adagrad optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the proximal Adagrad optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug
    */
@@ -159,4 +162,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the proximal Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of accumulators used in the proximal Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> accumulators;
+
+    /**
+     * Value of gradient_accumulators used in the proximal Adagrad optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      accumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParameters.java
index c722394cb64..424542eadb2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -42,11 +45,11 @@ private LoadTPUEmbeddingProximalYogiParameters(Operation operation) {
    * Factory method to create a class wrapping a new LoadTPUEmbeddingProximalYogiParameters operation.
    *
    * @param scope current scope
-   * @param parameters the parameters value
-   * @param v the v value
-   * @param m the m value
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param parameters The parameters value
+   * @param v The v value
+   * @param m The m value
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingProximalYogiParameters
    */
@@ -154,4 +157,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingProximalYogiParameters> {
+    /**
+     * The parameters input
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * The v input
+     */
+    public final Operand<TFloat32> v;
+
+    /**
+     * The m input
+     */
+    public final Operand<TFloat32> m;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingProximalYogiParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      v = (Operand<TFloat32>) op.input(inputIndex++);
+      m = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.java
index 139a4b7928d..4c3dfed12dc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -42,12 +45,12 @@ private LoadTPUEmbeddingProximalYogiParametersGradAccumDebug(Operation operation
    * Factory method to create a class wrapping a new LoadTPUEmbeddingProximalYogiParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param parameters the parameters value
-   * @param v the v value
-   * @param m the m value
-   * @param gradientAccumulators the gradientAccumulators value
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param parameters The parameters value
+   * @param v The v value
+   * @param m The m value
+   * @param gradientAccumulators The gradientAccumulators value
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingProximalYogiParametersGradAccumDebug
    */
@@ -156,4 +159,65 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingProximalYogiParametersGradAccumDebug> {
+    /**
+     * The parameters input
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * The v input
+     */
+    public final Operand<TFloat32> v;
+
+    /**
+     * The m input
+     */
+    public final Operand<TFloat32> m;
+
+    /**
+     * The gradientAccumulators input
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingProximalYogiParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      v = (Operand<TFloat32>) op.input(inputIndex++);
+      m = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParameters.java
index 855cd064132..69e422ee802 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -50,8 +53,8 @@ private LoadTPUEmbeddingRMSPropParameters(Operation operation) {
    * @param parameters Value of parameters used in the RMSProp optimization algorithm.
    * @param ms Value of ms used in the RMSProp optimization algorithm.
    * @param mom Value of mom used in the RMSProp optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingRMSPropParameters
    */
@@ -159,4 +162,59 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingRMSPropParameters> {
+    /**
+     * Value of parameters used in the RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of ms used in the RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> ms;
+
+    /**
+     * Value of mom used in the RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> mom;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingRMSPropParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      ms = (Operand<TFloat32>) op.input(inputIndex++);
+      mom = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParametersGradAccumDebug.java
index 3831217f2c9..3f987e4beac 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private LoadTPUEmbeddingRMSPropParametersGradAccumDebug(Operation operation) {
    * @param ms Value of ms used in the RMSProp optimization algorithm.
    * @param mom Value of mom used in the RMSProp optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the RMSProp optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingRMSPropParametersGradAccumDebug
    */
@@ -161,4 +164,65 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingRMSPropParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of ms used in the RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> ms;
+
+    /**
+     * Value of mom used in the RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> mom;
+
+    /**
+     * Value of gradient_accumulators used in the RMSProp optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingRMSPropParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      ms = (Operand<TFloat32>) op.input(inputIndex++);
+      mom = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParameters.java
index c263af2f921..62e73a01c52 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -48,8 +51,8 @@ private LoadTPUEmbeddingStochasticGradientDescentParameters(Operation operation)
    *
    * @param scope current scope
    * @param parameters Value of parameters used in the stochastic gradient descent optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingStochasticGradientDescentParameters
    */
@@ -154,4 +157,47 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingStochasticGradientDescentParameters> {
+    /**
+     * Value of parameters used in the stochastic gradient descent optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingStochasticGradientDescentParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java
index 2b8c8979f43..dd5fd61bc44 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -49,8 +52,8 @@ private LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug(Operat
    * @param scope current scope
    * @param parameters Value of parameters used in the stochastic gradient descent optimization algorithm.
    * @param gradientAccumulators Value of gradient_accumulators used in the Adadelta optimization algorithm.
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
    */
@@ -157,4 +160,53 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug> {
+    /**
+     * Value of parameters used in the stochastic gradient descent optimization algorithm.
+     */
+    public final Operand<TFloat32> parameters;
+
+    /**
+     * Value of gradient_accumulators used in the Adadelta optimization algorithm.
+     */
+    public final Operand<TFloat32> gradientAccumulators;
+
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      parameters = (Operand<TFloat32>) op.input(inputIndex++);
+      gradientAccumulators = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OrdinalSelector.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OrdinalSelector.java
index 27ac214d707..c026d5f55a4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OrdinalSelector.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OrdinalSelector.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -73,4 +76,11 @@ public Output<TInt32> deviceOrdinals() {
   public Output<TInt32> asOutput() {
     return deviceOrdinals;
   }
+
+  public static class Inputs extends RawOpInputs<OrdinalSelector> {
+    public Inputs(GraphOperation op) {
+      super(new OrdinalSelector(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java
index c86acd651b9..b2cd4412cae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,8 +26,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -124,4 +128,31 @@ public Options deviceOrdinal(Long deviceOrdinal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OutfeedDequeue<?>> {
+    /**
+     * The type of elements in the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the tensor.
+     */
+    public final Shape shape;
+
+    /**
+     * The TPU device to use. This should be -1 when the Op
+     * is running on a TPU device, and >= 0 when the Op is running on the CPU
+     * device.
+     */
+    public final long deviceOrdinal;
+
+    public Inputs(GraphOperation op) {
+      super(new OutfeedDequeue<>(op), op, Arrays.asList("dtype", "shape", "device_ordinal"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java
index 317b8c9fe94..c667cf7a4ed 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -133,4 +136,31 @@ public Options deviceOrdinal(Long deviceOrdinal) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<OutfeedDequeueTuple> {
+    /**
+     * The element types of each element in `outputs`.
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The shapes of each tensor in `outputs`.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * The TPU device to use. This should be -1 when the Op
+     * is running on a TPU device, and >= 0 when the Op is running on the CPU
+     * device.
+     */
+    public final long deviceOrdinal;
+
+    public Inputs(GraphOperation op) {
+      super(new OutfeedDequeueTuple(op), op, Arrays.asList("dtypes", "shapes", "device_ordinal"));
+      int inputIndex = 0;
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      deviceOrdinal = op.attributes().getAttrInt("device_ordinal");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java
index d76cb039bcf..328e3a7da5f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java
@@ -20,6 +20,7 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -27,8 +28,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -96,4 +99,31 @@ public List<Output<?>> outputs() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<OutfeedDequeueTupleV2> {
+    /**
+     * An int scalar tensor, representing the TPU device to use. This should be -1 when
+     * the Op is running on a TPU device, and &gt;= 0 when the Op is running on the CPU
+     * device.
+     */
+    public final Operand<TInt32> deviceOrdinal;
+
+    /**
+     * The element types of each element in `outputs`.
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The shapes of each tensor in `outputs`.
+     */
+    public final Shape[] shapes;
+
+    public Inputs(GraphOperation op) {
+      super(new OutfeedDequeueTupleV2(op), op, Arrays.asList("dtypes", "shapes"));
+      int inputIndex = 0;
+      deviceOrdinal = (Operand<TInt32>) op.input(inputIndex++);
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      shapes = op.attributes().getAttrShapeList("shapes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java
index 52c59042db0..bdd0a7f4157 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,8 +26,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -87,4 +91,31 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<OutfeedDequeueV2<?>> {
+    /**
+     * An int scalar tensor, representing the TPU device to use. This should be -1 when
+     * the Op is running on a TPU device, and &gt;= 0 when the Op is running on the CPU
+     * device.
+     */
+    public final Operand<TInt32> deviceOrdinal;
+
+    /**
+     * The type of elements in the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the tensor.
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new OutfeedDequeueV2<>(op), op, Arrays.asList("dtype", "shape"));
+      int inputIndex = 0;
+      deviceOrdinal = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueue.java
index 91b06a891c3..effdad173b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueue.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,4 +57,23 @@ public static OutfeedEnqueue create(Scope scope, Operand<? extends TType> input)
     opBuilder.addInput(input.asOutput());
     return new OutfeedEnqueue(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<OutfeedEnqueue> {
+    /**
+     * A tensor that will be inserted into the outfeed queue.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The dtype attribute
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new OutfeedEnqueue(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueueTuple.java
index 14b280a0e91..5e915899fd6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueueTuple.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueueTuple.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * Enqueue multiple Tensor values on the computation outfeed.
@@ -54,4 +58,26 @@ public static OutfeedEnqueueTuple create(Scope scope, Iterable<Operand<?>> input
     opBuilder.addInputList(Operands.asOutputs(inputs));
     return new OutfeedEnqueueTuple(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<OutfeedEnqueueTuple> {
+    /**
+     * A list of tensors that will be inserted into the outfeed queue as an
+     * XLA tuple.
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    public Inputs(GraphOperation op) {
+      super(new OutfeedEnqueueTuple(op), op, Arrays.asList("dtypes"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedCall.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedCall.java
index 72ea7263328..a85442af958 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedCall.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedCall.java
@@ -21,14 +21,17 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -129,4 +132,43 @@ public Options autotunerThresh(Long autotunerThresh) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<PartitionedCall> {
+    /**
+     * The arguments to the function.
+     */
+    public final Iterable<Operand<?>> args;
+
+    /**
+     * The TPU device ordinal to run the function on.
+     */
+    public final Operand<TInt32> deviceOrdinal;
+
+    /**
+     * The types of the arguments to the function.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * The types of the outputs of the function.
+     */
+    public final DataType[] Tout;
+
+    /**
+     * The autotunerThresh attribute
+     */
+    public final long autotunerThresh;
+
+    public Inputs(GraphOperation op) {
+      super(new PartitionedCall(op), op, Arrays.asList("Tin", "Tout", "autotuner_thresh"));
+      int inputIndex = 0;
+      int argsLength = op.inputListLength("args");
+      args = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argsLength));
+      inputIndex += argsLength;
+      deviceOrdinal = (Operand<TInt32>) op.input(inputIndex++);
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+      autotunerThresh = op.attributes().getAttrInt("autotuner_thresh");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java
index 36808e6cf20..8e080b4fd05 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -122,4 +126,32 @@ public Options partitionDim(Long partitionDim) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<PartitionedInput<T>> {
+    /**
+     * A list of partitioned inputs which must have the same shape.
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * An integer describles which dimension is partitioned. -1 means
+     * those inputs are replicated.
+     */
+    public final long partitionDim;
+
+    public Inputs(GraphOperation op) {
+      super(new PartitionedInput<>(op), op, Arrays.asList("T", "partition_dim"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+      partitionDim = op.attributes().getAttrInt("partition_dim");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java
index 55df563614e..626610bad5e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java
@@ -20,14 +20,17 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -61,7 +64,7 @@ private PartitionedOutput(Operation operation) {
    *
    * @param scope current scope
    * @param inputs A tensor which represents the full shape of partitioned tensors.
-   * @param numSplits the value of the numSplits property
+   * @param numSplits The value of the numSplits attribute
    * @param options carries optional attribute values
    * @param <T> data type for {@code TPUPartitionedOutput} output and operands
    * @return a new instance of PartitionedOutput
@@ -129,4 +132,29 @@ public Options partitionDim(Long partitionDim) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<PartitionedOutput<T>> {
+    /**
+     * A tensor which represents the full shape of partitioned tensors.
+     */
+    public final Operand<T> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * An integer describles which dimension is partitioned.
+     */
+    public final long partitionDim;
+
+    public Inputs(GraphOperation op) {
+      super(new PartitionedOutput<>(op), op, Arrays.asList("T", "partition_dim"));
+      int inputIndex = 0;
+      inputs = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      partitionDim = op.attributes().getAttrInt("partition_dim");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Prelinearize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Prelinearize.java
index b88ba6f8fb6..ddb2f379660 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Prelinearize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/Prelinearize.java
@@ -19,14 +19,17 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -109,7 +112,7 @@ public static Options layout(List<Long> layout) {
    * the infeed operation.
    * @return this Options instance.
    */
-  public static Options layout(Long[] layout) {
+  public static Options layout(Long... layout) {
     return new Options().layout(layout);
   }
 
@@ -176,4 +179,37 @@ public Options layout(Long... layout) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<Prelinearize> {
+    /**
+     * A tensor that will be linearized.
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The type of elements in the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the tensor.
+     */
+    public final Shape shape;
+
+    /**
+     * A vector holding the requested layout in minor-to-major sequence. If a layout
+     * attribute is passed but its values are all -1 the layout will be computed by
+     * the infeed operation.
+     */
+    public final long[] layout;
+
+    public Inputs(GraphOperation op) {
+      super(new Prelinearize(op), op, Arrays.asList("dtype", "shape", "layout"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      layout = op.attributes().getAttrIntList("layout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java
index a7683d006e9..344cab1a66a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java
@@ -19,6 +19,7 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -26,8 +27,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -105,7 +108,7 @@ public static Options layouts(List<Long> layouts) {
    * will be computed by the infeed operation.
    * @return this Options instance.
    */
-  public static Options layouts(Long[] layouts) {
+  public static Options layouts(Long... layouts) {
     return new Options().layouts(layouts);
   }
 
@@ -161,4 +164,40 @@ public Options layouts(Long... layouts) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<PrelinearizeTuple> {
+    /**
+     * A list of tensors that will be provided using the infeed mechanism.
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The element types of each element in `inputs`.
+     */
+    public final DataType[] dtypes;
+
+    /**
+     * The shapes of each tensor in `inputs`.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * A vector holding the requested layout in minor-to-major sequence for all the
+     * tuple shapes in the order the shapes appear in the "shapes" input. The layout
+     * elements for a sub-shape can be set to -1 in which case the corresponding layout
+     * will be computed by the infeed operation.
+     */
+    public final long[] layouts;
+
+    public Inputs(GraphOperation op) {
+      super(new PrelinearizeTuple(op), op, Arrays.asList("dtypes", "shapes", "layouts"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      layouts = op.attributes().getAttrIntList("layouts");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RecvTPUEmbeddingActivations.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RecvTPUEmbeddingActivations.java
index bce36be28ce..4dc37a810c5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RecvTPUEmbeddingActivations.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RecvTPUEmbeddingActivations.java
@@ -20,11 +20,13 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -89,4 +91,17 @@ public List<Output<TFloat32>> outputs() {
   public Iterator<Operand<TFloat32>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<RecvTPUEmbeddingActivations> {
+    /**
+     * Serialized TPUEmbeddingConfiguration proto.
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RecvTPUEmbeddingActivations(op), op, Arrays.asList("config"));
+      int inputIndex = 0;
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java
index ea469e87a9f..8e12a13b887 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java
@@ -19,9 +19,11 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 
@@ -152,7 +154,7 @@ public static Options deviceAssignment(List<Long> deviceAssignment) {
    * @param deviceAssignment The assignment of devices for the computation.
    * @return this Options instance.
    */
-  public static Options deviceAssignment(Long[] deviceAssignment) {
+  public static Options deviceAssignment(Long... deviceAssignment) {
     return new Options().deviceAssignment(deviceAssignment);
   }
 
@@ -172,7 +174,7 @@ public static Options computationShape(List<Long> computationShape) {
    * @param computationShape DEPRECATED. Use num_cores_per_replica instead.
    * @return this Options instance.
    */
-  public static Options computationShape(Long[] computationShape) {
+  public static Options computationShape(Long... computationShape) {
     return new Options().computationShape(computationShape);
   }
 
@@ -192,7 +194,7 @@ public static Options hostComputeCore(List<String> hostComputeCore) {
    * @param hostComputeCore the hostComputeCore option
    * @return this Options instance.
    */
-  public static Options hostComputeCore(String[] hostComputeCore) {
+  public static Options hostComputeCore(String... hostComputeCore) {
     return new Options().hostComputeCore(hostComputeCore);
   }
 
@@ -212,7 +214,7 @@ public static Options paddingMap(List<String> paddingMap) {
    * @param paddingMap the paddingMap option
    * @return this Options instance.
    */
-  public static Options paddingMap(String[] paddingMap) {
+  public static Options paddingMap(String... paddingMap) {
     return new Options().paddingMap(paddingMap);
   }
 
@@ -427,4 +429,77 @@ public Options useSpmdForXlaPartitioning(Boolean useSpmdForXlaPartitioning) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ReplicateMetadata> {
+    /**
+     * Number of replicas of the computation
+     */
+    public final long numReplicas;
+
+    /**
+     * Number of cores per replica. Used for model parallelism.
+     */
+    public final long numCoresPerReplica;
+
+    /**
+     * TopologyProto indicating the topology of the TPU pod slice.
+     */
+    public final String topology;
+
+    /**
+     * Whether to place the computation on the TPU.
+     */
+    public final boolean useTpu;
+
+    /**
+     * The assignment of devices for the computation.
+     */
+    public final long[] deviceAssignment;
+
+    /**
+     * DEPRECATED. Use num_cores_per_replica instead.
+     */
+    public final long[] computationShape;
+
+    /**
+     * The hostComputeCore attribute
+     */
+    public final String[] hostComputeCore;
+
+    /**
+     * The paddingMap attribute
+     */
+    public final String[] paddingMap;
+
+    /**
+     * The stepMarkerLocation attribute
+     */
+    public final String stepMarkerLocation;
+
+    /**
+     * The allowSoftPlacement attribute
+     */
+    public final boolean allowSoftPlacement;
+
+    /**
+     * The useSpmdForXlaPartitioning attribute
+     */
+    public final boolean useSpmdForXlaPartitioning;
+
+    public Inputs(GraphOperation op) {
+      super(new ReplicateMetadata(op), op, Arrays.asList("num_replicas", "num_cores_per_replica", "topology", "use_tpu", "device_assignment", "computation_shape", "host_compute_core", "padding_map", "step_marker_location", "allow_soft_placement", "use_spmd_for_xla_partitioning"));
+      int inputIndex = 0;
+      numReplicas = op.attributes().getAttrInt("num_replicas");
+      numCoresPerReplica = op.attributes().getAttrInt("num_cores_per_replica");
+      topology = op.attributes().getAttrString("topology");
+      useTpu = op.attributes().getAttrBool("use_tpu");
+      deviceAssignment = op.attributes().getAttrIntList("device_assignment");
+      computationShape = op.attributes().getAttrIntList("computation_shape");
+      hostComputeCore = op.attributes().getAttrStringList("host_compute_core");
+      paddingMap = op.attributes().getAttrStringList("padding_map");
+      stepMarkerLocation = op.attributes().getAttrString("step_marker_location");
+      allowSoftPlacement = op.attributes().getAttrBool("allow_soft_placement");
+      useSpmdForXlaPartitioning = op.attributes().getAttrBool("use_spmd_for_xla_partitioning");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java
index 609ba0ffea6..1bfa9e59e25 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,7 +64,7 @@ private ReplicatedInput(Operation operation) {
    * Factory method to create a class wrapping a new TPUReplicatedInput operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
+   * @param inputs The inputs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code TPUReplicatedInput} output and operands
    * @return a new instance of ReplicatedInput
@@ -178,4 +182,43 @@ public Options isPacked(Boolean isPacked) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ReplicatedInput<T>> {
+    /**
+     * The inputs input
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The isMirroredVariable attribute
+     */
+    public final boolean isMirroredVariable;
+
+    /**
+     * The index attribute
+     */
+    public final long index;
+
+    /**
+     * The isPacked attribute
+     */
+    public final boolean isPacked;
+
+    public Inputs(GraphOperation op) {
+      super(new ReplicatedInput<>(op), op, Arrays.asList("T", "is_mirrored_variable", "index", "is_packed"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+      isMirroredVariable = op.attributes().getAttrBool("is_mirrored_variable");
+      index = op.attributes().getAttrInt("index");
+      isPacked = op.attributes().getAttrBool("is_packed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java
index 53c2f484f09..f644763c1e8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java
@@ -20,13 +20,16 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -63,8 +66,8 @@ private ReplicatedOutput(Operation operation) {
    * Factory method to create a class wrapping a new TPUReplicatedOutput operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param numReplicas the value of the numReplicas property
+   * @param input The input value
+   * @param numReplicas The value of the numReplicas attribute
    * @param <T> data type for {@code TPUReplicatedOutput} output and operands
    * @return a new instance of ReplicatedOutput
    */
@@ -93,4 +96,23 @@ public List<Output<T>> outputs() {
   public Iterator<Operand<T>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ReplicatedOutput<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ReplicatedOutput<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParameters.java
index 2d5b5a035b9..d05f62e2f3e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingADAMParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingADAMParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingADAMParameters
    */
@@ -188,4 +191,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingADAMParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingADAMParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParametersGradAccumDebug.java
index b35d58f4620..c08259b0d89 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -59,8 +62,8 @@ private RetrieveTPUEmbeddingADAMParametersGradAccumDebug(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingADAMParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingADAMParametersGradAccumDebug
    */
@@ -200,4 +203,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingADAMParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingADAMParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParameters.java
index bf5c12097f8..d7f5626f574 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingAdadeltaParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingAdadeltaParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingAdadeltaParameters
    */
@@ -188,4 +191,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingAdadeltaParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingAdadeltaParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.java
index 77eeff609e9..7740306b350 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -59,8 +62,8 @@ private RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug(Operation operation
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug
    */
@@ -200,4 +203,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParameters.java
index 259d7301875..64762a31449 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -53,8 +56,8 @@ private RetrieveTPUEmbeddingAdagradParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingAdagradParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingAdagradParameters
    */
@@ -176,4 +179,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingAdagradParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingAdagradParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.java
index d0c18009b22..78c29954df4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingAdagradParametersGradAccumDebug(Operation operation)
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingAdagradParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingAdagradParametersGradAccumDebug
    */
@@ -188,4 +191,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingAdagradParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingAdagradParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingCenteredRMSPropParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingCenteredRMSPropParameters.java
index 58c257c4a38..a4dd7ba910e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingCenteredRMSPropParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingCenteredRMSPropParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -59,8 +62,8 @@ private RetrieveTPUEmbeddingCenteredRMSPropParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingCenteredRMSPropParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingCenteredRMSPropParameters
    */
@@ -200,4 +203,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingCenteredRMSPropParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingCenteredRMSPropParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParameters.java
index 4f8cdfc578c..6e1ab7a50c0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingFTRLParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingFTRLParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingFTRLParameters
    */
@@ -188,4 +191,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingFTRLParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingFTRLParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.java
index b2100385e37..5dc9db5c737 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -59,8 +62,8 @@ private RetrieveTPUEmbeddingFTRLParametersGradAccumDebug(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingFTRLParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingFTRLParametersGradAccumDebug
    */
@@ -200,4 +203,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingFTRLParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingFTRLParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMDLAdagradLightParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMDLAdagradLightParameters.java
index 84f4b4a7da0..0b341ec67e7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMDLAdagradLightParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMDLAdagradLightParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -59,8 +62,8 @@ private RetrieveTPUEmbeddingMDLAdagradLightParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingMDLAdagradLightParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingMDLAdagradLightParameters
    */
@@ -200,4 +203,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingMDLAdagradLightParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingMDLAdagradLightParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParameters.java
index 14c67e9e170..360d345257c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -53,8 +56,8 @@ private RetrieveTPUEmbeddingMomentumParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingMomentumParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingMomentumParameters
    */
@@ -176,4 +179,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingMomentumParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingMomentumParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.java
index c374fb8ecc5..5ba59def58d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingMomentumParametersGradAccumDebug(Operation operation
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingMomentumParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingMomentumParametersGradAccumDebug
    */
@@ -188,4 +191,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingMomentumParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingMomentumParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParameters.java
index 5aea831a41b..5a351245ecb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -53,8 +56,8 @@ private RetrieveTPUEmbeddingProximalAdagradParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingProximalAdagradParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingProximalAdagradParameters
    */
@@ -176,4 +179,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingProximalAdagradParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingProximalAdagradParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.java
index 587d0dc3b1d..740410a1c49 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug(Operation op
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug
    */
@@ -188,4 +191,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParameters.java
index 26b6a4f0b65..3caff4629ad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -52,8 +55,8 @@ private RetrieveTPUEmbeddingProximalYogiParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingProximalYogiParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingProximalYogiParameters
    */
@@ -184,4 +187,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingProximalYogiParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingProximalYogiParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.java
index 6ff27ae7156..50fe386f14f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -55,8 +58,8 @@ private RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug(Operation opera
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug
    */
@@ -196,4 +199,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParameters.java
index beecf2f21ba..0db31288db7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParameters.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -56,8 +59,8 @@ private RetrieveTPUEmbeddingRMSPropParameters(Operation operation) {
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingRMSPropParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingRMSPropParameters
    */
@@ -188,4 +191,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingRMSPropParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingRMSPropParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.java
index 569044de7cc..3d32bd5d1f2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -59,8 +62,8 @@ private RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug(Operation operation)
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug
    */
@@ -200,4 +203,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParameters.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParameters.java
index f80a04cf0dc..7d8ab5ae954 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParameters.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParameters.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -51,8 +54,8 @@ private RetrieveTPUEmbeddingStochasticGradientDescentParameters(Operation operat
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingStochasticGradientDescentParameters operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingStochasticGradientDescentParameters
    */
@@ -170,4 +173,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingStochasticGradientDescentParameters> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingStochasticGradientDescentParameters(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java
index 95d897459b1..c199ce91f51 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -54,8 +57,8 @@ private RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug(
    * Factory method to create a class wrapping a new RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug operation.
    *
    * @param scope current scope
-   * @param numShards the value of the numShards property
-   * @param shardId the value of the shardId property
+   * @param numShards The value of the numShards attribute
+   * @param shardId The value of the shardId attribute
    * @param options carries optional attribute values
    * @return a new instance of RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
    */
@@ -177,4 +180,41 @@ public Options config(String config) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug> {
+    /**
+     * The tableId attribute
+     */
+    public final long tableId;
+
+    /**
+     * The tableName attribute
+     */
+    public final String tableName;
+
+    /**
+     * The numShards attribute
+     */
+    public final long numShards;
+
+    /**
+     * The shardId attribute
+     */
+    public final long shardId;
+
+    /**
+     * The config attribute
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug(op), op, Arrays.asList("table_id", "table_name", "num_shards", "shard_id", "config"));
+      int inputIndex = 0;
+      tableId = op.attributes().getAttrInt("table_id");
+      tableName = op.attributes().getAttrString("table_name");
+      numShards = op.attributes().getAttrInt("num_shards");
+      shardId = op.attributes().getAttrInt("shard_id");
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SendTPUEmbeddingGradients.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SendTPUEmbeddingGradients.java
index e9925b25235..0556e51c322 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SendTPUEmbeddingGradients.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SendTPUEmbeddingGradients.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -108,4 +111,43 @@ public Options NN(Long NN) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SendTPUEmbeddingGradients> {
+    /**
+     * A TensorList of gradients with which to update embedding tables.
+     * This argument has the same length and shapes as the return value of
+     * RecvTPUEmbeddingActivations, but contains gradients of the model's loss
+     * with respect to the embedding activations. The embedding tables are updated
+     * from these gradients via the optimizer specified in the TPU embedding
+     * configuration given to tpu.initialize_system.
+     */
+    public final Iterable<Operand<TFloat32>> inputs;
+
+    /**
+     * A TensorList of float32 scalars, one for each dynamic learning
+     * rate tag: see the comments in
+     * //third_party/tensorflow/core/protobuf/tpu/optimization_parameters.proto.
+     * Multiple tables can share the same dynamic learning rate tag as specified
+     * in the configuration. If the learning rates for all tables are constant,
+     * this list should be empty.
+     */
+    public final Iterable<Operand<TFloat32>> learningRates;
+
+    /**
+     * Serialized TPUEmbeddingConfiguration proto.
+     */
+    public final String config;
+
+    public Inputs(GraphOperation op) {
+      super(new SendTPUEmbeddingGradients(op), op, Arrays.asList("config"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      int learningRatesLength = op.inputListLength("learning_rates");
+      learningRates = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, learningRatesLength));
+      inputIndex += learningRatesLength;
+      config = op.attributes().getAttrString("config");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ShutdownDistributedTPU.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ShutdownDistributedTPU.java
index 75fb90a9caa..bfd80d334da 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ShutdownDistributedTPU.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ShutdownDistributedTPU.java
@@ -17,9 +17,12 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 
@@ -50,4 +53,11 @@ public static ShutdownDistributedTPU create(Scope scope) {
     OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "ShutdownDistributedTPU");
     return new ShutdownDistributedTPU(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ShutdownDistributedTPU> {
+    public Inputs(GraphOperation op) {
+      super(new ShutdownDistributedTPU(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUCompilationResult.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUCompilationResult.java
index 7ad97d0b7eb..7bc258d87f6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUCompilationResult.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUCompilationResult.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -76,4 +79,11 @@ public Output<TString> output() {
   public Output<TString> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<TPUCompilationResult> {
+    public Inputs(GraphOperation op) {
+      super(new TPUCompilationResult(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUEmbeddingActivations.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUEmbeddingActivations.java
index c97dd07cec4..360c11d3a5a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUEmbeddingActivations.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUEmbeddingActivations.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -89,4 +92,37 @@ public Output<TFloat32> output() {
   public Output<TFloat32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<TPUEmbeddingActivations> {
+    /**
+     * A trainable variable, enabling optimizers to find this op.
+     */
+    public final Operand<TFloat32> embeddingVariable;
+
+    /**
+     * The embedding activations Tensor to return.
+     */
+    public final Operand<TFloat32> slicedActivations;
+
+    /**
+     * The id of the table in the embedding layer configuration from which
+     * these activations were computed.
+     */
+    public final long tableId;
+
+    /**
+     * Identifier of the set of embedding indices which produced these
+     * activations.
+     */
+    public final long lookupId;
+
+    public Inputs(GraphOperation op) {
+      super(new TPUEmbeddingActivations(op), op, Arrays.asList("table_id", "lookup_id"));
+      int inputIndex = 0;
+      embeddingVariable = (Operand<TFloat32>) op.input(inputIndex++);
+      slicedActivations = (Operand<TFloat32>) op.input(inputIndex++);
+      tableId = op.attributes().getAttrInt("table_id");
+      lookupId = op.attributes().getAttrInt("lookup_id");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicateMetadata.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicateMetadata.java
index 4a291f3ae50..124bccfda5c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicateMetadata.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicateMetadata.java
@@ -19,9 +19,11 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 
@@ -155,7 +157,7 @@ public static Options deviceAssignment(List<Long> deviceAssignment) {
    * @param deviceAssignment The assignment of devices for the computation.
    * @return this Options instance.
    */
-  public static Options deviceAssignment(Long[] deviceAssignment) {
+  public static Options deviceAssignment(Long... deviceAssignment) {
     return new Options().deviceAssignment(deviceAssignment);
   }
 
@@ -175,7 +177,7 @@ public static Options computationShape(List<Long> computationShape) {
    * @param computationShape DEPRECATED. Use num_cores_per_replica instead.
    * @return this Options instance.
    */
-  public static Options computationShape(Long[] computationShape) {
+  public static Options computationShape(Long... computationShape) {
     return new Options().computationShape(computationShape);
   }
 
@@ -195,7 +197,7 @@ public static Options hostComputeCore(List<String> hostComputeCore) {
    * @param hostComputeCore the hostComputeCore option
    * @return this Options instance.
    */
-  public static Options hostComputeCore(String[] hostComputeCore) {
+  public static Options hostComputeCore(String... hostComputeCore) {
     return new Options().hostComputeCore(hostComputeCore);
   }
 
@@ -215,7 +217,7 @@ public static Options paddingMap(List<String> paddingMap) {
    * @param paddingMap the paddingMap option
    * @return this Options instance.
    */
-  public static Options paddingMap(String[] paddingMap) {
+  public static Options paddingMap(String... paddingMap) {
     return new Options().paddingMap(paddingMap);
   }
 
@@ -430,4 +432,77 @@ public Options useSpmdForXlaPartitioning(Boolean useSpmdForXlaPartitioning) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<TPUReplicateMetadata> {
+    /**
+     * Number of replicas of the computation
+     */
+    public final long numReplicas;
+
+    /**
+     * Number of cores per replica. Used for model parallelism.
+     */
+    public final long numCoresPerReplica;
+
+    /**
+     * TopologyProto indicating the topology of the TPU pod slice.
+     */
+    public final String topology;
+
+    /**
+     * Whether to place the computation on the TPU.
+     */
+    public final boolean useTpu;
+
+    /**
+     * The assignment of devices for the computation.
+     */
+    public final long[] deviceAssignment;
+
+    /**
+     * DEPRECATED. Use num_cores_per_replica instead.
+     */
+    public final long[] computationShape;
+
+    /**
+     * The hostComputeCore attribute
+     */
+    public final String[] hostComputeCore;
+
+    /**
+     * The paddingMap attribute
+     */
+    public final String[] paddingMap;
+
+    /**
+     * The stepMarkerLocation attribute
+     */
+    public final String stepMarkerLocation;
+
+    /**
+     * The allowSoftPlacement attribute
+     */
+    public final boolean allowSoftPlacement;
+
+    /**
+     * The useSpmdForXlaPartitioning attribute
+     */
+    public final boolean useSpmdForXlaPartitioning;
+
+    public Inputs(GraphOperation op) {
+      super(new TPUReplicateMetadata(op), op, Arrays.asList("num_replicas", "num_cores_per_replica", "topology", "use_tpu", "device_assignment", "computation_shape", "host_compute_core", "padding_map", "step_marker_location", "allow_soft_placement", "use_spmd_for_xla_partitioning"));
+      int inputIndex = 0;
+      numReplicas = op.attributes().getAttrInt("num_replicas");
+      numCoresPerReplica = op.attributes().getAttrInt("num_cores_per_replica");
+      topology = op.attributes().getAttrString("topology");
+      useTpu = op.attributes().getAttrBool("use_tpu");
+      deviceAssignment = op.attributes().getAttrIntList("device_assignment");
+      computationShape = op.attributes().getAttrIntList("computation_shape");
+      hostComputeCore = op.attributes().getAttrStringList("host_compute_core");
+      paddingMap = op.attributes().getAttrStringList("padding_map");
+      stepMarkerLocation = op.attributes().getAttrString("step_marker_location");
+      allowSoftPlacement = op.attributes().getAttrBool("allow_soft_placement");
+      useSpmdForXlaPartitioning = op.attributes().getAttrBool("use_spmd_for_xla_partitioning");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java
index de437abaf8e..bfb2ef52af0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -63,7 +67,7 @@ private TPUReplicatedInput(Operation operation) {
    * Factory method to create a class wrapping a new TPUReplicatedInput operation.
    *
    * @param scope current scope
-   * @param inputs the inputs value
+   * @param inputs The inputs value
    * @param options carries optional attribute values
    * @param <T> data type for {@code TPUReplicatedInput} output and operands
    * @return a new instance of TPUReplicatedInput
@@ -181,4 +185,43 @@ public Options isPacked(Boolean isPacked) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TPUReplicatedInput<T>> {
+    /**
+     * The inputs input
+     */
+    public final Iterable<Operand<T>> inputs;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The isMirroredVariable attribute
+     */
+    public final boolean isMirroredVariable;
+
+    /**
+     * The index attribute
+     */
+    public final long index;
+
+    /**
+     * The isPacked attribute
+     */
+    public final boolean isPacked;
+
+    public Inputs(GraphOperation op) {
+      super(new TPUReplicatedInput<>(op), op, Arrays.asList("T", "is_mirrored_variable", "index", "is_packed"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      T = op.attributes().getAttrType("T");
+      isMirroredVariable = op.attributes().getAttrBool("is_mirrored_variable");
+      index = op.attributes().getAttrInt("index");
+      isPacked = op.attributes().getAttrBool("is_packed");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java
index 33a23fd27e9..e20f5d1b4c6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java
@@ -20,13 +20,16 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -66,8 +69,8 @@ private TPUReplicatedOutput(Operation operation) {
    * Factory method to create a class wrapping a new TPUReplicatedOutput operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param numReplicas the value of the numReplicas property
+   * @param input The input value
+   * @param numReplicas The value of the numReplicas attribute
    * @param <T> data type for {@code TPUReplicatedOutput} output and operands
    * @return a new instance of TPUReplicatedOutput
    */
@@ -96,4 +99,23 @@ public List<Output<T>> outputs() {
   public Iterator<Operand<T>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TPUReplicatedOutput<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TPUReplicatedOutput<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReshardVariables.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReshardVariables.java
index 012917b3350..5308bcc3b37 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReshardVariables.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReshardVariables.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -49,9 +52,9 @@ private TPUReshardVariables(Operation operation) {
    * Factory method to create a class wrapping a new TPUReshardVariables operation.
    *
    * @param scope current scope
-   * @param vars the vars value
-   * @param newFormatKey the newFormatKey value
-   * @param formatStateVar the formatStateVar value
+   * @param vars The vars value
+   * @param newFormatKey The newFormatKey value
+   * @param formatStateVar The formatStateVar value
    * @return a new instance of TPUReshardVariables
    */
   @Endpoint(
@@ -65,4 +68,31 @@ public static TPUReshardVariables create(Scope scope, Iterable<Operand<? extends
     opBuilder.addInput(formatStateVar.asOutput());
     return new TPUReshardVariables(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<TPUReshardVariables> {
+    /**
+     * The vars input
+     */
+    public final Iterable<Operand<? extends TType>> vars;
+
+    /**
+     * The newFormatKey input
+     */
+    public final Operand<TString> newFormatKey;
+
+    /**
+     * The formatStateVar input
+     */
+    public final Operand<? extends TType> formatStateVar;
+
+    public Inputs(GraphOperation op) {
+      super(new TPUReshardVariables(op), op, Arrays.asList());
+      int inputIndex = 0;
+      int varsLength = op.inputListLength("vars");
+      vars = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, varsLength));
+      inputIndex += varsLength;
+      newFormatKey = (Operand<TString>) op.input(inputIndex++);
+      formatStateVar = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/WorkerHeartbeat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/WorkerHeartbeat.java
index 76185847723..cff0719e947 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/WorkerHeartbeat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/WorkerHeartbeat.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.tpu;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TString;
@@ -74,4 +77,17 @@ public Output<TString> response() {
   public Output<TString> asOutput() {
     return response;
   }
+
+  public static class Inputs extends RawOpInputs<WorkerHeartbeat> {
+    /**
+     * A string tensor containing a serialized WorkerHeartbeatRequest
+     */
+    public final Operand<TString> request;
+
+    public Inputs(GraphOperation op) {
+      super(new WorkerHeartbeat(op), op, Arrays.asList());
+      int inputIndex = 0;
+      request = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorApplyGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorApplyGradient.java
index 204dae5a267..64f16b73bab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorApplyGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorApplyGradient.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -65,4 +69,36 @@ public static AccumulatorApplyGradient create(Scope scope, Operand<TString> hand
     opBuilder.addInput(gradient.asOutput());
     return new AccumulatorApplyGradient(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<AccumulatorApplyGradient> {
+    /**
+     * The handle to a accumulator.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * The local_step value at which the gradient was computed.
+     */
+    public final Operand<TInt64> localStep;
+
+    /**
+     * A tensor of the gradient to be accumulated.
+     */
+    public final Operand<? extends TType> gradient;
+
+    /**
+     * The data type of accumulated gradients. Needs to correspond to the type
+     * of the accumulator.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new AccumulatorApplyGradient(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      localStep = (Operand<TInt64>) op.input(inputIndex++);
+      gradient = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorNumAccumulated.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorNumAccumulated.java
index 5b5b775ef9b..73199c30e4b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorNumAccumulated.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorNumAccumulated.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -77,4 +80,17 @@ public Output<TInt32> numAccumulated() {
   public Output<TInt32> asOutput() {
     return numAccumulated;
   }
+
+  public static class Inputs extends RawOpInputs<AccumulatorNumAccumulated> {
+    /**
+     * The handle to an accumulator.
+     */
+    public final Operand<TString> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new AccumulatorNumAccumulated(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorSetGlobalStep.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorSetGlobalStep.java
index cca774e5106..23092eb9759 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorSetGlobalStep.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorSetGlobalStep.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -63,4 +66,23 @@ public static AccumulatorSetGlobalStep create(Scope scope, Operand<TString> hand
     opBuilder.addInput(newGlobalStep.asOutput());
     return new AccumulatorSetGlobalStep(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<AccumulatorSetGlobalStep> {
+    /**
+     * The handle to an accumulator.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * The new global_step value to set.
+     */
+    public final Operand<TInt64> newGlobalStep;
+
+    public Inputs(GraphOperation op) {
+      super(new AccumulatorSetGlobalStep(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      newGlobalStep = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java
index e27b98bd50b..52d6bce2df3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
@@ -93,4 +97,30 @@ public Output<T> average() {
   public Output<T> asOutput() {
     return average;
   }
+
+  public static class Inputs extends RawOpInputs<AccumulatorTakeGradient<?>> {
+    /**
+     * The handle to an accumulator.
+     */
+    public final Operand<TString> handle;
+
+    /**
+     * Number of gradients required before we return an aggregate.
+     */
+    public final Operand<TInt32> numRequired;
+
+    /**
+     * The data type of accumulated gradients. Needs to correspond to the type
+     * of the accumulator.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new AccumulatorTakeGradient<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      handle = (Operand<TString>) op.input(inputIndex++);
+      numRequired = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java
index 433c44bb92e..84b1ccd7a52 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -139,4 +143,79 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyAdaMax<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> m;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> v;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta1Power;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta1;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta2;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, m, and v tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyAdaMax<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      m = (Operand<T>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      beta1Power = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      beta1 = (Operand<T>) op.input(inputIndex++);
+      beta2 = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java
index f71e57defbd..2d908547cfd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -138,4 +142,66 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyAdadelta<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accumUpdate;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay factor. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, updating of the var, accum and update_accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyAdadelta<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      accumUpdate = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java
index b26331a94c9..1296c191656 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -157,4 +161,55 @@ public Options updateSlots(Boolean updateSlots) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyAdagrad<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The updateSlots attribute
+     */
+    public final boolean updateSlots;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyAdagrad<>(op), op, Arrays.asList("T", "use_locking", "update_slots"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      updateSlots = op.attributes().getAttrBool("update_slots");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java
index 978c8db8202..a3f60e0471f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -137,4 +141,72 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyAdagradDa<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> gradientAccumulator;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> gradientSquaredAccumulator;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * Training step number. Must be a scalar.
+     */
+    public final Operand<TInt64> globalStep;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyAdagradDa<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      gradientAccumulator = (Operand<T>) op.input(inputIndex++);
+      gradientSquaredAccumulator = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      globalStep = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java
index 615802c3be0..f26f0ca7e82 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -155,4 +159,61 @@ public Options updateSlots(Boolean updateSlots) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyAdagradV2<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The updateSlots attribute
+     */
+    public final boolean updateSlots;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyAdagradV2<>(op), op, Arrays.asList("T", "use_locking", "update_slots"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      updateSlots = op.attributes().getAttrBool("update_slots");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java
index 5c47f6dbd56..ae419bd1640 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdam.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -172,4 +176,91 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyAdam<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> m;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> v;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta1Power;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta2Power;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta1;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta2;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, m, and v tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, uses the nesterov update.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyAdam<>(op), op, Arrays.asList("T", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      m = (Operand<T>) op.input(inputIndex++);
+      v = (Operand<T>) op.input(inputIndex++);
+      beta1Power = (Operand<T>) op.input(inputIndex++);
+      beta2Power = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      beta1 = (Operand<T>) op.input(inputIndex++);
+      beta2 = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java
index e0e014d9438..5eb80c556c3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -139,4 +143,67 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyAddSign<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> m;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> signDecay;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and m tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyAddSign<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      m = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      signDecay = (Operand<T>) op.input(inputIndex++);
+      beta = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java
index 015487e6b0f..5872ccce7b1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -154,4 +158,79 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyCenteredRmsProp<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> mg;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * Momentum Scale. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, mg, ms, and mom tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyCenteredRmsProp<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      mg = (Operand<T>) op.input(inputIndex++);
+      ms = (Operand<T>) op.input(inputIndex++);
+      mom = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java
index 2aa8c5146f0..af10fab7ed5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyFtrl.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -67,7 +71,7 @@ private ApplyFtrl(Operation operation) {
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code ApplyFtrlV2} output and operands
@@ -173,4 +177,85 @@ public Options multiplyLinearByLr(Boolean multiplyLinearByLr) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyFtrl<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> linear;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 shrinkage regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The l2Shrinkage input
+     */
+    public final Operand<T> l2Shrinkage;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lrPower;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The multiplyLinearByLr attribute
+     */
+    public final boolean multiplyLinearByLr;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyFtrl<>(op), op, Arrays.asList("T", "use_locking", "multiply_linear_by_lr"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      linear = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      l2Shrinkage = (Operand<T>) op.input(inputIndex++);
+      lrPower = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      multiplyLinearByLr = op.attributes().getAttrBool("multiply_linear_by_lr");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java
index 116c546494b..0e459aefa68 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -125,4 +129,42 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyGradientDescent<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * The change.
+     */
+    public final Operand<T> delta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyGradientDescent<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      delta = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java
index 51e5ac6da61..cf22b9bcbed 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyMomentum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -164,4 +168,63 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyMomentum<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * Momentum. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, the tensor passed to compute grad will be
+     * var - lr * momentum * accum, so in the end, the var you get is actually
+     * var - lr * momentum * accum.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyMomentum<>(op), op, Arrays.asList("T", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java
index 9990db09384..88fd9980c94 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -139,4 +143,67 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyPowerSign<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> m;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> logbase;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> signDecay;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and m tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyPowerSign<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      m = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      logbase = (Operand<T>) op.input(inputIndex++);
+      signDecay = (Operand<T>) op.input(inputIndex++);
+      beta = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java
index 713ed8cbdca..aa2dc292c1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -135,4 +139,60 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyProximalAdagrad<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyProximalAdagrad<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java
index 65cce9b1594..d1c6ab76cea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -132,4 +136,54 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyProximalGradientDescent<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The change.
+     */
+    public final Operand<T> delta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyProximalGradientDescent<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      delta = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java
index c64f1a76a37..3c9ad0c5087 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -66,7 +70,7 @@ private ApplyRmsProp(Operation operation) {
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param options carries optional attribute values
@@ -146,4 +150,73 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ApplyRmsProp<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * The momentum input
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, ms, and mom tensors is protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ApplyRmsProp<>(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      ms = (Operand<T>) op.input(inputIndex++);
+      mom = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java
index 0dbe8f569a1..2efb6c587ac 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -170,4 +174,53 @@ public Options adjY(Boolean adjY) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<BatchMatMul<?>> {
+    /**
+     * 2-D or higher with shape {@code [..., r_x, c_x]}.
+     */
+    public final Operand<? extends TType> x;
+
+    /**
+     * 2-D or higher with shape {@code [..., r_y, c_y]}.
+     */
+    public final Operand<? extends TType> y;
+
+    /**
+     * The Ta attribute
+     */
+    public final DataType Ta;
+
+    /**
+     * The Tb attribute
+     */
+    public final DataType Tb;
+
+    /**
+     * If not spcified, Tout is the same type to input type.
+     */
+    public final DataType Tout;
+
+    /**
+     * If `True`, adjoint the slices of `x`. Defaults to `False`.
+     */
+    public final boolean adjX;
+
+    /**
+     * If `True`, adjoint the slices of `y`. Defaults to `False`.
+     */
+    public final boolean adjY;
+
+    public Inputs(GraphOperation op) {
+      super(new BatchMatMul<>(op), op, Arrays.asList("Ta", "Tb", "Tout", "adj_x", "adj_y"));
+      int inputIndex = 0;
+      x = (Operand<? extends TType>) op.input(inputIndex++);
+      y = (Operand<? extends TType>) op.input(inputIndex++);
+      Ta = op.attributes().getAttrType("Ta");
+      Tb = op.attributes().getAttrType("Tb");
+      Tout = op.attributes().getAttrType("Tout");
+      adjX = op.attributes().getAttrBool("adj_x");
+      adjY = op.attributes().getAttrBool("adj_y");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ComputeBatchSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ComputeBatchSize.java
index 707132417e7..ef4a34b1a9a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ComputeBatchSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ComputeBatchSize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -48,7 +51,7 @@ private ComputeBatchSize(Operation operation) {
    * Factory method to create a class wrapping a new ComputeBatchSize operation.
    *
    * @param scope current scope
-   * @param inputDataset the inputDataset value
+   * @param inputDataset The inputDataset value
    * @return a new instance of ComputeBatchSize
    */
   @Endpoint(
@@ -73,4 +76,17 @@ public Output<TInt64> batchSize() {
   public Output<TInt64> asOutput() {
     return batchSize;
   }
+
+  public static class Inputs extends RawOpInputs<ComputeBatchSize> {
+    /**
+     * The inputDataset input
+     */
+    public final Operand<? extends TType> inputDataset;
+
+    public Inputs(GraphOperation op) {
+      super(new ComputeBatchSize(op), op, Arrays.asList());
+      int inputIndex = 0;
+      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java
index 96449ca58e3..ae58b09075e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -184,4 +188,43 @@ public Options reductionType(String reductionType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ConditionalAccumulator> {
+    /**
+     * The type of the value being accumulated.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the values, can be [], in which case shape is unknown.
+     */
+    public final Shape shape;
+
+    /**
+     * If non-empty, this accumulator is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this accumulator will be shared under the
+     * given name across multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * The reductionType attribute
+     */
+    public final String reductionType;
+
+    public Inputs(GraphOperation op) {
+      super(new ConditionalAccumulator(op), op, Arrays.asList("dtype", "shape", "container", "shared_name", "reduction_type"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      reductionType = op.attributes().getAttrString("reduction_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/GenerateVocabRemapping.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/GenerateVocabRemapping.java
index e6797a7111c..d5246b11201 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/GenerateVocabRemapping.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/GenerateVocabRemapping.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -159,4 +162,42 @@ public Options oldVocabSize(Long oldVocabSize) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<GenerateVocabRemapping> {
+    /**
+     * Path to the new vocab file.
+     */
+    public final Operand<TString> newVocabFile;
+
+    /**
+     * Path to the old vocab file.
+     */
+    public final Operand<TString> oldVocabFile;
+
+    /**
+     * How many entries into the new vocab file to start reading.
+     */
+    public final long newVocabOffset;
+
+    /**
+     * Number of entries in the new vocab file to remap.
+     */
+    public final long numNewVocab;
+
+    /**
+     * Number of entries in the old vocab file to consider.  If -1,
+     * use the entire old vocabulary.
+     */
+    public final long oldVocabSize;
+
+    public Inputs(GraphOperation op) {
+      super(new GenerateVocabRemapping(op), op, Arrays.asList("new_vocab_offset", "num_new_vocab", "old_vocab_size"));
+      int inputIndex = 0;
+      newVocabFile = (Operand<TString>) op.input(inputIndex++);
+      oldVocabFile = (Operand<TString>) op.input(inputIndex++);
+      newVocabOffset = op.attributes().getAttrInt("new_vocab_offset");
+      numNewVocab = op.attributes().getAttrInt("num_new_vocab");
+      oldVocabSize = op.attributes().getAttrInt("old_vocab_size");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/MergeV2Checkpoints.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/MergeV2Checkpoints.java
index 9172767def8..2d45a0379dc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/MergeV2Checkpoints.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/MergeV2Checkpoints.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -106,4 +109,30 @@ public Options deleteOldDirs(Boolean deleteOldDirs) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<MergeV2Checkpoints> {
+    /**
+     * prefixes of V2 checkpoints to merge.
+     */
+    public final Operand<TString> checkpointPrefixes;
+
+    /**
+     * scalar.  The desired final prefix.  Allowed to be the same
+     * as one of the checkpoint_prefixes.
+     */
+    public final Operand<TString> destinationPrefix;
+
+    /**
+     * see above.
+     */
+    public final boolean deleteOldDirs;
+
+    public Inputs(GraphOperation op) {
+      super(new MergeV2Checkpoints(op), op, Arrays.asList("delete_old_dirs"));
+      int inputIndex = 0;
+      checkpointPrefixes = (Operand<TString>) op.input(inputIndex++);
+      destinationPrefix = (Operand<TString>) op.input(inputIndex++);
+      deleteOldDirs = op.attributes().getAttrBool("delete_old_dirs");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/NegTrain.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/NegTrain.java
index d41712ac70c..491a6c2da92 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/NegTrain.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/NegTrain.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -52,7 +55,7 @@ private NegTrain(Operation operation) {
    * @param wOut output word embedding.
    * @param examples A vector of word ids.
    * @param labels A vector of word ids.
-   * @param lr the lr value
+   * @param lr The lr value
    * @param vocabCount Count of words in the vocabulary.
    * @param numNegativeSamples Number of negative samples per example.
    * @return a new instance of NegTrain
@@ -77,4 +80,53 @@ public static NegTrain create(Scope scope, Operand<TFloat32> wIn, Operand<TFloat
     opBuilder.setAttr("num_negative_samples", numNegativeSamples);
     return new NegTrain(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<NegTrain> {
+    /**
+     * input word embedding.
+     */
+    public final Operand<TFloat32> wIn;
+
+    /**
+     * output word embedding.
+     */
+    public final Operand<TFloat32> wOut;
+
+    /**
+     * A vector of word ids.
+     */
+    public final Operand<TInt32> examples;
+
+    /**
+     * A vector of word ids.
+     */
+    public final Operand<TInt32> labels;
+
+    /**
+     * The lr input
+     */
+    public final Operand<TFloat32> lr;
+
+    /**
+     * Count of words in the vocabulary.
+     */
+    public final long[] vocabCount;
+
+    /**
+     * Number of negative samples per example.
+     */
+    public final long numNegativeSamples;
+
+    public Inputs(GraphOperation op) {
+      super(new NegTrain(op), op, Arrays.asList("vocab_count", "num_negative_samples"));
+      int inputIndex = 0;
+      wIn = (Operand<TFloat32>) op.input(inputIndex++);
+      wOut = (Operand<TFloat32>) op.input(inputIndex++);
+      examples = (Operand<TInt32>) op.input(inputIndex++);
+      labels = (Operand<TInt32>) op.input(inputIndex++);
+      lr = (Operand<TFloat32>) op.input(inputIndex++);
+      vocabCount = op.attributes().getAttrIntList("vocab_count");
+      numNegativeSamples = op.attributes().getAttrInt("num_negative_samples");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java
index 68e248aa696..884fffc0487 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -127,4 +131,30 @@ public Options message(String message) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<PreventGradient<T>> {
+    /**
+     * any tensor.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * Will be printed in the error when anyone tries to differentiate
+     * this operation.
+     */
+    public final String message;
+
+    public Inputs(GraphOperation op) {
+      super(new PreventGradient<>(op), op, Arrays.asList("T", "message"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      message = op.attributes().getAttrString("message");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorApplyGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorApplyGradient.java
index 98f187541c9..db829374d76 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorApplyGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorApplyGradient.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -61,4 +65,36 @@ public static ResourceAccumulatorApplyGradient create(Scope scope,
     opBuilder.addInput(gradient.asOutput());
     return new ResourceAccumulatorApplyGradient(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceAccumulatorApplyGradient> {
+    /**
+     * The handle to a accumulator.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The local_step value at which the gradient was computed.
+     */
+    public final Operand<TInt64> localStep;
+
+    /**
+     * A tensor of the gradient to be accumulated.
+     */
+    public final Operand<? extends TType> gradient;
+
+    /**
+     * The data type of accumulated gradients. Needs to correspond to the type
+     * of the accumulator.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceAccumulatorApplyGradient(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      localStep = (Operand<TInt64>) op.input(inputIndex++);
+      gradient = (Operand<? extends TType>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorNumAccumulated.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorNumAccumulated.java
index 9041826e913..c9cc0a3c4a2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorNumAccumulated.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorNumAccumulated.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt32;
@@ -74,4 +77,17 @@ public Output<TInt32> numAccumulated() {
   public Output<TInt32> asOutput() {
     return numAccumulated;
   }
+
+  public static class Inputs extends RawOpInputs<ResourceAccumulatorNumAccumulated> {
+    /**
+     * The handle to an accumulator.
+     */
+    public final Operand<? extends TType> handle;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceAccumulatorNumAccumulated(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorSetGlobalStep.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorSetGlobalStep.java
index b634dca59b8..23141dd5d10 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorSetGlobalStep.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorSetGlobalStep.java
@@ -17,10 +17,13 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TInt64;
@@ -59,4 +62,23 @@ public static ResourceAccumulatorSetGlobalStep create(Scope scope,
     opBuilder.addInput(newGlobalStep.asOutput());
     return new ResourceAccumulatorSetGlobalStep(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<ResourceAccumulatorSetGlobalStep> {
+    /**
+     * The handle to an accumulator.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * The new global_step value to set.
+     */
+    public final Operand<TInt64> newGlobalStep;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceAccumulatorSetGlobalStep(op), op, Arrays.asList());
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      newGlobalStep = (Operand<TInt64>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java
index 867f0751001..1cfc15beb3c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -88,4 +92,30 @@ public Output<T> average() {
   public Output<T> asOutput() {
     return average;
   }
+
+  public static class Inputs extends RawOpInputs<ResourceAccumulatorTakeGradient<?>> {
+    /**
+     * The handle to an accumulator.
+     */
+    public final Operand<? extends TType> handle;
+
+    /**
+     * Number of gradients required before we return an aggregate.
+     */
+    public final Operand<TInt32> numRequired;
+
+    /**
+     * The data type of accumulated gradients. Needs to correspond to the type
+     * of the accumulator.
+     */
+    public final DataType dtype;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceAccumulatorTakeGradient<>(op), op, Arrays.asList("dtype"));
+      int inputIndex = 0;
+      handle = (Operand<? extends TType>) op.input(inputIndex++);
+      numRequired = (Operand<TInt32>) op.input(inputIndex++);
+      dtype = op.attributes().getAttrType("dtype");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java
index fb5947e5ab7..336031fd4ae 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -119,4 +123,79 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyAdaMax> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> m;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> v;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta1Power;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta1;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta2;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, m, and v tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyAdaMax(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      m = (Operand<? extends TType>) op.input(inputIndex++);
+      v = (Operand<? extends TType>) op.input(inputIndex++);
+      beta1Power = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      beta1 = (Operand<T>) op.input(inputIndex++);
+      beta2 = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdadelta.java
index f7f572719da..11c2202c18b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdadelta.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdadelta.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -118,4 +122,66 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyAdadelta> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accumUpdate;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay factor. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, updating of the var, accum and update_accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyAdadelta(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      accumUpdate = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagrad.java
index ca8682dc2b1..29042e8ccd3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagrad.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -135,4 +139,61 @@ public Options updateSlots(Boolean updateSlots) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyAdagrad> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The updateSlots attribute
+     */
+    public final boolean updateSlots;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyAdagrad(op), op, Arrays.asList("T", "use_locking", "update_slots"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      updateSlots = op.attributes().getAttrBool("update_slots");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagradDa.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagradDa.java
index 5062953430b..b153e0c2cf6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagradDa.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdagradDa.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
@@ -117,4 +121,72 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyAdagradDa> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> gradientAccumulator;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> gradientSquaredAccumulator;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * Training step number. Must be a scalar.
+     */
+    public final Operand<TInt64> globalStep;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyAdagradDa(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      gradientAccumulator = (Operand<? extends TType>) op.input(inputIndex++);
+      gradientSquaredAccumulator = (Operand<? extends TType>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      globalStep = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdam.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdam.java
index eb4d8d0ffd2..d58a5e916f1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdam.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdam.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -152,4 +156,91 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyAdam> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> m;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> v;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta1Power;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta2Power;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta1;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta2;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, m, and v tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, uses the nesterov update.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyAdam(op), op, Arrays.asList("T", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      m = (Operand<? extends TType>) op.input(inputIndex++);
+      v = (Operand<? extends TType>) op.input(inputIndex++);
+      beta1Power = (Operand<T>) op.input(inputIndex++);
+      beta2Power = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      beta1 = (Operand<T>) op.input(inputIndex++);
+      beta2 = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdamWithAmsgrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdamWithAmsgrad.java
index be9f35d16ea..38df623446b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdamWithAmsgrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdamWithAmsgrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -129,4 +133,91 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyAdamWithAmsgrad> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> m;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> v;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> vhat;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta1Power;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta2Power;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta1;
+
+    /**
+     * Momentum factor. Must be a scalar.
+     */
+    public final Operand<T> beta2;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, m, and v tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyAdamWithAmsgrad(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      m = (Operand<? extends TType>) op.input(inputIndex++);
+      v = (Operand<? extends TType>) op.input(inputIndex++);
+      vhat = (Operand<? extends TType>) op.input(inputIndex++);
+      beta1Power = (Operand<T>) op.input(inputIndex++);
+      beta2Power = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      beta1 = (Operand<T>) op.input(inputIndex++);
+      beta2 = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAddSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAddSign.java
index 5a5d2fd2520..d034cd3bf0d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAddSign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAddSign.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -118,4 +122,67 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyAddSign> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> m;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> signDecay;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and m tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyAddSign(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      m = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      signDecay = (Operand<T>) op.input(inputIndex++);
+      beta = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyCenteredRmsProp.java
index d10936d4253..55ce63a208c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyCenteredRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyCenteredRmsProp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -134,4 +138,79 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyCenteredRmsProp> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> mg;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * Momentum Scale. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, mg, ms, and mom tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyCenteredRmsProp(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      mg = (Operand<? extends TType>) op.input(inputIndex++);
+      ms = (Operand<? extends TType>) op.input(inputIndex++);
+      mom = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyFtrl.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyFtrl.java
index d082bbfc45d..8d3540eda02 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyFtrl.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyFtrl.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -60,7 +64,7 @@ private ResourceApplyFtrl(Operation operation) {
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code ResourceApplyFtrlV2} output and operands
@@ -153,4 +157,85 @@ public Options multiplyLinearByLr(Boolean multiplyLinearByLr) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyFtrl> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> linear;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 shrinkage regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The l2Shrinkage input
+     */
+    public final Operand<T> l2Shrinkage;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lrPower;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The multiplyLinearByLr attribute
+     */
+    public final boolean multiplyLinearByLr;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyFtrl(op), op, Arrays.asList("T", "use_locking", "multiply_linear_by_lr"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      linear = (Operand<? extends TType>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      l2Shrinkage = (Operand<T>) op.input(inputIndex++);
+      lrPower = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      multiplyLinearByLr = op.attributes().getAttrBool("multiply_linear_by_lr");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyGradientDescent.java
index f772d2c6361..f33601521df 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyGradientDescent.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyGradientDescent.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -104,4 +108,42 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyGradientDescent> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * The change.
+     */
+    public final Operand<T> delta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyGradientDescent(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      delta = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyKerasMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyKerasMomentum.java
index bb6a9f3169c..39edfec6216 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyKerasMomentum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyKerasMomentum.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -144,4 +148,63 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyKerasMomentum> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * Momentum. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, the tensor passed to compute grad will be
+     * var + momentum * accum, so in the end, the var you get is actually
+     * var + momentum * accum.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyKerasMomentum(op), op, Arrays.asList("T", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyMomentum.java
index f4a9058871a..6bb224aa4e4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyMomentum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyMomentum.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -144,4 +148,63 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyMomentum> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * Momentum. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, the tensor passed to compute grad will be
+     * var - lr * momentum * accum, so in the end, the var you get is actually
+     * var - lr * momentum * accum.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyMomentum(op), op, Arrays.asList("T", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyPowerSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyPowerSign.java
index 397de82bac3..3df2066af31 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyPowerSign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyPowerSign.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -118,4 +122,67 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyPowerSign> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> m;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> logbase;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> signDecay;
+
+    /**
+     * Must be a scalar.
+     */
+    public final Operand<T> beta;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var and m tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyPowerSign(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      m = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      logbase = (Operand<T>) op.input(inputIndex++);
+      signDecay = (Operand<T>) op.input(inputIndex++);
+      beta = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalAdagrad.java
index 177ee0b4ec7..5e251235af1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalAdagrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -114,4 +118,60 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyProximalAdagrad> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyProximalAdagrad(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalGradientDescent.java
index 4dd1fc9a361..1a3da62fbf4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalGradientDescent.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyProximalGradientDescent.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -111,4 +115,54 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyProximalGradientDescent> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The change.
+     */
+    public final Operand<T> delta;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If True, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyProximalGradientDescent(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      delta = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyRmsProp.java
index c6b569388ed..6d2fe91d598 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyRmsProp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,7 +63,7 @@ private ResourceApplyRmsProp(Operation operation) {
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param options carries optional attribute values
@@ -126,4 +130,73 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceApplyRmsProp> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * The momentum input
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * If `True`, updating of the var, ms, and mom tensors is protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceApplyRmsProp(op), op, Arrays.asList("T", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      ms = (Operand<? extends TType>) op.input(inputIndex++);
+      mom = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java
index 546a566f45a..4cc51c55289 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,8 +26,10 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -183,4 +187,43 @@ public Options reductionType(String reductionType) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<ResourceConditionalAccumulator> {
+    /**
+     * The type of the value being accumulated.
+     */
+    public final DataType dtype;
+
+    /**
+     * The shape of the values, can be [], in which case shape is unknown.
+     */
+    public final Shape shape;
+
+    /**
+     * If non-empty, this accumulator is placed in the given container.
+     * Otherwise, a default container is used.
+     */
+    public final String container;
+
+    /**
+     * If non-empty, this accumulator will be shared under the
+     * given name across multiple sessions.
+     */
+    public final String sharedName;
+
+    /**
+     * The reductionType attribute
+     */
+    public final String reductionType;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceConditionalAccumulator(op), op, Arrays.asList("dtype", "shape", "container", "shared_name", "reduction_type"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      shape = op.attributes().getAttrShape("shape");
+      container = op.attributes().getAttrString("container");
+      sharedName = op.attributes().getAttrString("shared_name");
+      reductionType = op.attributes().getAttrString("reduction_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdadelta.java
index 816e18737ca..01f0a739f36 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdadelta.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdadelta.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -47,7 +51,7 @@ private ResourceSparseApplyAdadelta(Operation operation) {
    * Factory method to create a class wrapping a new ResourceSparseApplyAdadelta operation.
    *
    * @param scope current scope
-   * @param var the var value
+   * @param var The var value
    * @param accum Should be from a Variable().
    * @param accumUpdate : Should be from a Variable().
    * @param lr Learning rate. Must be a scalar.
@@ -117,4 +121,78 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyAdadelta> {
+    /**
+     * The var input
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * : Should be from a Variable().
+     */
+    public final Operand<? extends TType> accumUpdate;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay factor. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyAdadelta(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      accumUpdate = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagrad.java
index 733fc1f3f6b..aaa5be414ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -141,4 +145,67 @@ public Options updateSlots(Boolean updateSlots) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyAdagrad> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The updateSlots attribute
+     */
+    public final boolean updateSlots;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyAdagrad(op), op, Arrays.asList("T", "Tindices", "use_locking", "update_slots"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      updateSlots = op.attributes().getAttrBool("update_slots");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradDa.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradDa.java
index d2c3ea597e8..6a410002f3a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradDa.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradDa.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -121,4 +125,84 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyAdagradDa> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> gradientAccumulator;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> gradientSquaredAccumulator;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * Training step number. Must be a scalar.
+     */
+    public final Operand<TInt64> globalStep;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyAdagradDa(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      gradientAccumulator = (Operand<? extends TType>) op.input(inputIndex++);
+      gradientSquaredAccumulator = (Operand<? extends TType>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      globalStep = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradV2.java
index a432cee80f3..423505a39b5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyAdagradV2.java
@@ -17,12 +17,16 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -139,4 +143,73 @@ public Options updateSlots(Boolean updateSlots) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyAdagradV2> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The updateSlots attribute
+     */
+    public final boolean updateSlots;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyAdagradV2(op), op, Arrays.asList("T", "Tindices", "use_locking", "update_slots"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      updateSlots = op.attributes().getAttrBool("update_slots");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyCenteredRmsProp.java
index 4a39342989e..2789f2fb191 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyCenteredRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyCenteredRmsProp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -66,7 +70,7 @@ private ResourceSparseApplyCenteredRmsProp(Operation operation) {
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -136,4 +140,91 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyCenteredRmsProp> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> mg;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * The momentum input
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var, ms and mom.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var, mg, ms, and mom tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyCenteredRmsProp(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      mg = (Operand<? extends TType>) op.input(inputIndex++);
+      ms = (Operand<? extends TType>) op.input(inputIndex++);
+      mom = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyFtrl.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyFtrl.java
index d4ff9eceb67..cfa21d59dc0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyFtrl.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyFtrl.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -63,7 +67,7 @@ private ResourceSparseApplyFtrl(Operation operation) {
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code ResourceSparseApplyFtrlV2} output and operands
@@ -157,4 +161,97 @@ public Options multiplyLinearByLr(Boolean multiplyLinearByLr) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyFtrl> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> linear;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 shrinkage regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The l2Shrinkage input
+     */
+    public final Operand<T> l2Shrinkage;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lrPower;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The multiplyLinearByLr attribute
+     */
+    public final boolean multiplyLinearByLr;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyFtrl(op), op, Arrays.asList("T", "Tindices", "use_locking", "multiply_linear_by_lr"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      linear = (Operand<? extends TType>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      l2Shrinkage = (Operand<T>) op.input(inputIndex++);
+      lrPower = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      multiplyLinearByLr = op.attributes().getAttrBool("multiply_linear_by_lr");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyKerasMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyKerasMomentum.java
index 3359aeb3d8f..94c2ad9bd17 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyKerasMomentum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyKerasMomentum.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -148,4 +152,75 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyKerasMomentum> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Momentum. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, the tensor passed to compute grad will be
+     * var + momentum * accum, so in the end, the var you get is actually
+     * var + momentum * accum.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyKerasMomentum(op), op, Arrays.asList("T", "Tindices", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyMomentum.java
index 37a53ca5174..1b52c885e67 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyMomentum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyMomentum.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -148,4 +152,75 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyMomentum> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Momentum. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, the tensor passed to compute grad will be
+     * var - lr * momentum * accum, so in the end, the var you get is actually
+     * var - lr * momentum * accum.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyMomentum(op), op, Arrays.asList("T", "Tindices", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalAdagrad.java
index 9beeb9b81d7..57b484d3b21 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalAdagrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -119,4 +123,72 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyProximalAdagrad> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyProximalAdagrad(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      accum = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalGradientDescent.java
index d7d2f5b85d1..2d266131daf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalGradientDescent.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyProximalGradientDescent.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -115,4 +119,66 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyProximalGradientDescent> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyProximalGradientDescent(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyRmsProp.java
index 0ff4e6f9003..ee73c441b8f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceSparseApplyRmsProp.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -60,7 +64,7 @@ private ResourceSparseApplyRmsProp(Operation operation) {
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -129,4 +133,85 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ResourceSparseApplyRmsProp> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<? extends TType> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * The momentum input
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var, ms and mom.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var, ms, and mom tensors is protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new ResourceSparseApplyRmsProp(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<? extends TType>) op.input(inputIndex++);
+      ms = (Operand<? extends TType>) op.input(inputIndex++);
+      mom = (Operand<? extends TType>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java
index 40dd24048f0..07682b56434 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java
@@ -20,15 +20,18 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -108,4 +111,37 @@ public List<Output<?>> tensors() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) tensors.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<Restore> {
+    /**
+     * Must have a single element.  The prefix of a V2 checkpoint.
+     */
+    public final Operand<TString> prefix;
+
+    /**
+     * shape {N}.  The names of the tensors to be restored.
+     */
+    public final Operand<TString> tensorNames;
+
+    /**
+     * shape {N}.  The slice specs of the tensors to be restored.
+     * Empty strings indicate that they are non-partitioned tensors.
+     */
+    public final Operand<TString> shapeAndSlices;
+
+    /**
+     * shape {N}.  The list of expected dtype for the tensors.  Must match
+     * those stored in the checkpoint.
+     */
+    public final DataType[] dtypes;
+
+    public Inputs(GraphOperation op) {
+      super(new Restore(op), op, Arrays.asList("dtypes"));
+      int inputIndex = 0;
+      prefix = (Operand<TString>) op.input(inputIndex++);
+      tensorNames = (Operand<TString>) op.input(inputIndex++);
+      shapeAndSlices = (Operand<TString>) op.input(inputIndex++);
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java
index 4bcd181e5f3..ee5496926cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
@@ -138,4 +142,45 @@ public Options preferredShard(Long preferredShard) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<RestoreSlice<?>> {
+    /**
+     * Must have a single element. The pattern of the files from
+     * which we read the tensor.
+     */
+    public final Operand<TString> filePattern;
+
+    /**
+     * Must have a single element. The name of the tensor to be
+     * restored.
+     */
+    public final Operand<TString> tensorName;
+
+    /**
+     * Scalar. The shapes and slice specifications to use when
+     * restoring a tensors.
+     */
+    public final Operand<TString> shapeAndSlice;
+
+    /**
+     * The type of the tensor to be restored.
+     */
+    public final DataType dt;
+
+    /**
+     * Index of file to open first if multiple files match
+     * `file_pattern`. See the documentation for `Restore`.
+     */
+    public final long preferredShard;
+
+    public Inputs(GraphOperation op) {
+      super(new RestoreSlice<>(op), op, Arrays.asList("dt", "preferred_shard"));
+      int inputIndex = 0;
+      filePattern = (Operand<TString>) op.input(inputIndex++);
+      tensorName = (Operand<TString>) op.input(inputIndex++);
+      shapeAndSlice = (Operand<TString>) op.input(inputIndex++);
+      dt = op.attributes().getAttrType("dt");
+      preferredShard = op.attributes().getAttrInt("preferred_shard");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Save.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Save.java
index 722c88f3eaa..57b0d9dc6df 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Save.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Save.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 
 /**
@@ -70,4 +74,45 @@ public static Save create(Scope scope, Operand<TString> prefix, Operand<TString>
     opBuilder.addInputList(Operands.asOutputs(tensors));
     return new Save(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<Save> {
+    /**
+     * Must have a single element. The prefix of the V2 checkpoint to which we
+     * write the tensors.
+     */
+    public final Operand<TString> prefix;
+
+    /**
+     * shape {N}. The names of the tensors to be saved.
+     */
+    public final Operand<TString> tensorNames;
+
+    /**
+     * shape {N}.  The slice specs of the tensors to be saved.
+     * Empty strings indicate that they are non-partitioned tensors.
+     */
+    public final Operand<TString> shapeAndSlices;
+
+    /**
+     * {@code N} tensors to save.
+     */
+    public final Iterable<Operand<?>> tensors;
+
+    /**
+     * The dtypes attribute
+     */
+    public final DataType[] dtypes;
+
+    public Inputs(GraphOperation op) {
+      super(new Save(op), op, Arrays.asList("dtypes"));
+      int inputIndex = 0;
+      prefix = (Operand<TString>) op.input(inputIndex++);
+      tensorNames = (Operand<TString>) op.input(inputIndex++);
+      shapeAndSlices = (Operand<TString>) op.input(inputIndex++);
+      int tensorsLength = op.inputListLength("tensors");
+      tensors = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, tensorsLength));
+      inputIndex += tensorsLength;
+      dtypes = op.attributes().getAttrTypeList("dtypes");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SaveSlices.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SaveSlices.java
index 50223df730d..e1b2ab7325a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SaveSlices.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SaveSlices.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TString;
 
 /**
@@ -87,4 +91,45 @@ public static SaveSlices create(Scope scope, Operand<TString> filename,
     opBuilder.addInputList(Operands.asOutputs(data));
     return new SaveSlices(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<SaveSlices> {
+    /**
+     * Must have a single element. The name of the file to which we write the
+     * tensor.
+     */
+    public final Operand<TString> filename;
+
+    /**
+     * Shape {@code [N]}. The names of the tensors to be saved.
+     */
+    public final Operand<TString> tensorNames;
+
+    /**
+     * Shape {@code [N]}.  The shapes and slice specifications to use when
+     * saving the tensors.
+     */
+    public final Operand<TString> shapesAndSlices;
+
+    /**
+     * {@code N} tensors to save.
+     */
+    public final Iterable<Operand<?>> data;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    public Inputs(GraphOperation op) {
+      super(new SaveSlices(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      filename = (Operand<TString>) op.input(inputIndex++);
+      tensorNames = (Operand<TString>) op.input(inputIndex++);
+      shapesAndSlices = (Operand<TString>) op.input(inputIndex++);
+      int dataLength = op.inputListLength("data");
+      data = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, dataLength));
+      inputIndex += dataLength;
+      T = op.attributes().getAttrTypeList("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaFprint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaFprint.java
index fb20638e575..0d7361ffed2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaFprint.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaFprint.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -78,4 +81,17 @@ public Output<TInt64> output() {
   public Output<TInt64> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<SdcaFprint> {
+    /**
+     * vector of strings to compute fingerprints on.
+     */
+    public final Operand<TString> input;
+
+    public Inputs(GraphOperation op) {
+      super(new SdcaFprint(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TString>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaOptimizer.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaOptimizer.java
index d8273b2b40d..3d271080556 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaOptimizer.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaOptimizer.java
@@ -19,12 +19,14 @@
 
 import java.util.Arrays;
 import java.util.List;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.types.TFloat32;
@@ -197,4 +199,129 @@ public Options adaptive(Boolean adaptive) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<SdcaOptimizer> {
+    /**
+     * a list of vectors which contain example indices.
+     */
+    public final Iterable<Operand<TInt64>> sparseExampleIndices;
+
+    /**
+     * a list of vectors which contain feature indices.
+     */
+    public final Iterable<Operand<TInt64>> sparseFeatureIndices;
+
+    /**
+     * a list of vectors which contains feature value
+     * associated with each feature group.
+     */
+    public final Iterable<Operand<TFloat32>> sparseFeatureValues;
+
+    /**
+     * a list of matrices which contains the dense feature values.
+     */
+    public final Iterable<Operand<TFloat32>> denseFeatures;
+
+    /**
+     * a vector which contains the weight associated with each
+     * example.
+     */
+    public final Operand<TFloat32> exampleWeights;
+
+    /**
+     * a vector which contains the label/target associated with each
+     * example.
+     */
+    public final Operand<TFloat32> exampleLabels;
+
+    /**
+     * a list of vectors where each value is the indices which has
+     * corresponding weights in sparse_weights. This field maybe omitted for the
+     * dense approach.
+     */
+    public final Iterable<Operand<TInt64>> sparseIndices;
+
+    /**
+     * a list of vectors where each value is the weight associated with
+     * a sparse feature group.
+     */
+    public final Iterable<Operand<TFloat32>> sparseWeights;
+
+    /**
+     * a list of vectors where the values are the weights associated
+     * with a dense feature group.
+     */
+    public final Iterable<Operand<TFloat32>> denseWeights;
+
+    /**
+     * a list of vectors containing the example state data.
+     */
+    public final Operand<TFloat32> exampleStateData;
+
+    /**
+     * Type of the primal loss. Currently SdcaSolver supports logistic,
+     * squared and hinge losses.
+     */
+    public final String lossType;
+
+    /**
+     * Whether to use Adaptive SDCA for the inner loop.
+     */
+    public final boolean adaptive;
+
+    /**
+     * Symmetric l1 regularization strength.
+     */
+    public final float l1;
+
+    /**
+     * Symmetric l2 regularization strength.
+     */
+    public final float l2;
+
+    /**
+     * Number of partitions of the global loss function.
+     */
+    public final long numLossPartitions;
+
+    /**
+     * Number of iterations per mini-batch.
+     */
+    public final long numInnerIterations;
+
+    public Inputs(GraphOperation op) {
+      super(new SdcaOptimizer(op), op, Arrays.asList("loss_type", "adaptive", "l1", "l2", "num_loss_partitions", "num_inner_iterations"));
+      int inputIndex = 0;
+      int sparseExampleIndicesLength = op.inputListLength("sparse_example_indices");
+      sparseExampleIndices = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, sparseExampleIndicesLength));
+      inputIndex += sparseExampleIndicesLength;
+      int sparseFeatureIndicesLength = op.inputListLength("sparse_feature_indices");
+      sparseFeatureIndices = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, sparseFeatureIndicesLength));
+      inputIndex += sparseFeatureIndicesLength;
+      int sparseFeatureValuesLength = op.inputListLength("sparse_feature_values");
+      sparseFeatureValues = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, sparseFeatureValuesLength));
+      inputIndex += sparseFeatureValuesLength;
+      int denseFeaturesLength = op.inputListLength("dense_features");
+      denseFeatures = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, denseFeaturesLength));
+      inputIndex += denseFeaturesLength;
+      exampleWeights = (Operand<TFloat32>) op.input(inputIndex++);
+      exampleLabels = (Operand<TFloat32>) op.input(inputIndex++);
+      int sparseIndicesLength = op.inputListLength("sparse_indices");
+      sparseIndices = Arrays.asList((Operand<TInt64>[]) op.inputList(inputIndex, sparseIndicesLength));
+      inputIndex += sparseIndicesLength;
+      int sparseWeightsLength = op.inputListLength("sparse_weights");
+      sparseWeights = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, sparseWeightsLength));
+      inputIndex += sparseWeightsLength;
+      int denseWeightsLength = op.inputListLength("dense_weights");
+      denseWeights = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, denseWeightsLength));
+      inputIndex += denseWeightsLength;
+      exampleStateData = (Operand<TFloat32>) op.input(inputIndex++);
+      lossType = op.attributes().getAttrString("loss_type");
+      adaptive = op.attributes().getAttrBool("adaptive");
+      l1 = op.attributes().getAttrFloat("l1");
+      l2 = op.attributes().getAttrFloat("l2");
+      numLossPartitions = op.attributes().getAttrInt("num_loss_partitions");
+      numInnerIterations = op.attributes().getAttrInt("num_inner_iterations");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaShrinkL1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaShrinkL1.java
index 5c30c4197ac..ac043e371b1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaShrinkL1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SdcaShrinkL1.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -64,4 +67,32 @@ public static SdcaShrinkL1 create(Scope scope, Iterable<Operand<TFloat32>> weigh
     opBuilder.setAttr("l2", l2);
     return new SdcaShrinkL1(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<SdcaShrinkL1> {
+    /**
+     * a list of vectors where each value is the weight associated with a
+     * feature group.
+     */
+    public final Iterable<Operand<TFloat32>> weights;
+
+    /**
+     * Symmetric l1 regularization strength.
+     */
+    public final float l1;
+
+    /**
+     * Symmetric l2 regularization strength. Should be a positive float.
+     */
+    public final float l2;
+
+    public Inputs(GraphOperation op) {
+      super(new SdcaShrinkL1(op), op, Arrays.asList("l1", "l2"));
+      int inputIndex = 0;
+      int weightsLength = op.inputListLength("weights");
+      weights = Arrays.asList((Operand<TFloat32>[]) op.inputList(inputIndex, weightsLength));
+      inputIndex += weightsLength;
+      l1 = op.attributes().getAttrFloat("l1");
+      l2 = op.attributes().getAttrFloat("l2");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java
index 067291732f4..5bb9b3f3d39 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -54,7 +58,7 @@ private SparseApplyAdadelta(Operation operation) {
    * Factory method to create a class wrapping a new SparseApplyAdadelta operation.
    *
    * @param scope current scope
-   * @param var the var value
+   * @param var The var value
    * @param accum Should be from a Variable().
    * @param accumUpdate : Should be from a Variable().
    * @param lr Learning rate. Must be a scalar.
@@ -137,4 +141,78 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyAdadelta<T>> {
+    /**
+     * The var input
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * : Should be from a Variable().
+     */
+    public final Operand<T> accumUpdate;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay factor. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyAdadelta<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      accumUpdate = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java
index 871e70cec9d..7485978329f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -160,4 +164,73 @@ public Options updateSlots(Boolean updateSlots) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyAdagrad<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Constant factor. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The updateSlots attribute
+     */
+    public final boolean updateSlots;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyAdagrad<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "update_slots"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      updateSlots = op.attributes().getAttrBool("update_slots");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java
index f54420becc3..b07ad601f9f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
@@ -141,4 +145,84 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyAdagradDa<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> gradientAccumulator;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> gradientSquaredAccumulator;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * Training step number. Must be a scalar.
+     */
+    public final Operand<TInt64> globalStep;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyAdagradDa<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      gradientAccumulator = (Operand<T>) op.input(inputIndex++);
+      gradientSquaredAccumulator = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      globalStep = (Operand<TInt64>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java
index 931e987a908..02d36702a5e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -73,7 +77,7 @@ private SparseApplyCenteredRmsProp(Operation operation) {
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -157,4 +161,91 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyCenteredRmsProp<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> mg;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * The momentum input
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var, ms and mom.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var, mg, ms, and mom tensors is
+     * protected by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyCenteredRmsProp<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      mg = (Operand<T>) op.input(inputIndex++);
+      ms = (Operand<T>) op.input(inputIndex++);
+      mom = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java
index 780d36208ff..b093d454dd1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -70,7 +74,7 @@ private SparseApplyFtrl(Operation operation) {
    * @param lr Scaling factor. Must be a scalar.
    * @param l1 L1 regularization. Must be a scalar.
    * @param l2 L2 shrinkage regularization. Must be a scalar.
-   * @param l2Shrinkage the l2Shrinkage value
+   * @param l2Shrinkage The l2Shrinkage value
    * @param lrPower Scaling factor. Must be a scalar.
    * @param options carries optional attribute values
    * @param <T> data type for {@code SparseApplyFtrlV2} output and operands
@@ -178,4 +182,97 @@ public Options multiplyLinearByLr(Boolean multiplyLinearByLr) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyFtrl<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> linear;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 shrinkage regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The l2Shrinkage input
+     */
+    public final Operand<T> l2Shrinkage;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lrPower;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * The multiplyLinearByLr attribute
+     */
+    public final boolean multiplyLinearByLr;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyFtrl<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "multiply_linear_by_lr"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      linear = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      l2Shrinkage = (Operand<T>) op.input(inputIndex++);
+      lrPower = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      multiplyLinearByLr = op.attributes().getAttrBool("multiply_linear_by_lr");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java
index dc6cd3beee5..9f36c04de51 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyMomentum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -169,4 +173,75 @@ public Options useNesterov(Boolean useNesterov) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyMomentum<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * Momentum. Must be a scalar.
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var and accum tensors will be protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    /**
+     * If `True`, the tensor passed to compute grad will be
+     * var - lr * momentum * accum, so in the end, the var you get is actually
+     * var - lr * momentum * accum.
+     */
+    public final boolean useNesterov;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyMomentum<>(op), op, Arrays.asList("T", "Tindices", "use_locking", "use_nesterov"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+      useNesterov = op.attributes().getAttrBool("use_nesterov");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java
index 68f56702597..d0f3ef64c4d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalAdagrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -140,4 +144,72 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyProximalAdagrad<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> accum;
+
+    /**
+     * Learning rate. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, updating of the var and accum tensors will be protected by
+     * a lock; otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyProximalAdagrad<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      accum = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java
index cae253e1891..ee51c62e9bb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -136,4 +140,66 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyProximalGradientDescent<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> alpha;
+
+    /**
+     * L1 regularization. Must be a scalar.
+     */
+    public final Operand<T> l1;
+
+    /**
+     * L2 regularization. Must be a scalar.
+     */
+    public final Operand<T> l2;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var and accum.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If True, the subtraction will be protected by a lock;
+     * otherwise the behavior is undefined, but may exhibit less contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyProximalGradientDescent<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      alpha = (Operand<T>) op.input(inputIndex++);
+      l1 = (Operand<T>) op.input(inputIndex++);
+      l2 = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java
index 5e1fc582838..af67871862b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -67,7 +71,7 @@ private SparseApplyRmsProp(Operation operation) {
    * @param mom Should be from a Variable().
    * @param lr Scaling factor. Must be a scalar.
    * @param rho Decay rate. Must be a scalar.
-   * @param momentum the momentum value
+   * @param momentum The momentum value
    * @param epsilon Ridge term. Must be a scalar.
    * @param grad The gradient.
    * @param indices A vector of indices into the first dimension of var, ms and mom.
@@ -149,4 +153,85 @@ public Options useLocking(Boolean useLocking) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SparseApplyRmsProp<T>> {
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> var;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> ms;
+
+    /**
+     * Should be from a Variable().
+     */
+    public final Operand<T> mom;
+
+    /**
+     * Scaling factor. Must be a scalar.
+     */
+    public final Operand<T> lr;
+
+    /**
+     * Decay rate. Must be a scalar.
+     */
+    public final Operand<T> rho;
+
+    /**
+     * The momentum input
+     */
+    public final Operand<T> momentum;
+
+    /**
+     * Ridge term. Must be a scalar.
+     */
+    public final Operand<T> epsilon;
+
+    /**
+     * The gradient.
+     */
+    public final Operand<T> grad;
+
+    /**
+     * A vector of indices into the first dimension of var, ms and mom.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * If `True`, updating of the var, ms, and mom tensors is protected
+     * by a lock; otherwise the behavior is undefined, but may exhibit less
+     * contention.
+     */
+    public final boolean useLocking;
+
+    public Inputs(GraphOperation op) {
+      super(new SparseApplyRmsProp<>(op), op, Arrays.asList("T", "Tindices", "use_locking"));
+      int inputIndex = 0;
+      var = (Operand<T>) op.input(inputIndex++);
+      ms = (Operand<T>) op.input(inputIndex++);
+      mom = (Operand<T>) op.input(inputIndex++);
+      lr = (Operand<T>) op.input(inputIndex++);
+      rho = (Operand<T>) op.input(inputIndex++);
+      momentum = (Operand<T>) op.input(inputIndex++);
+      epsilon = (Operand<T>) op.input(inputIndex++);
+      grad = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+      useLocking = op.attributes().getAttrBool("use_locking");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SymbolicGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SymbolicGradient.java
index 0bd82ac6525..205771ec423 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SymbolicGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SymbolicGradient.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -103,4 +106,31 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<SymbolicGradient> {
+    /**
+     * a list of input tensors of size N + M;
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * the type list for the input list.
+     */
+    public final DataType[] Tin;
+
+    /**
+     * the type list for the input list.
+     */
+    public final DataType[] Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new SymbolicGradient(op), op, Arrays.asList("Tin", "Tout"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java
index 9c18ef0054f..ccfe689fd89 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/TileGrad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.train;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -57,8 +61,8 @@ private TileGrad(Operation operation) {
    * Factory method to create a class wrapping a new TileGrad operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param multiples the multiples value
+   * @param input The input value
+   * @param multiples The multiples value
    * @param <T> data type for {@code TileGrad} output and operands
    * @return a new instance of TileGrad
    */
@@ -86,4 +90,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<TileGrad<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The multiples input
+     */
+    public final Operand<TInt32> multiples;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new TileGrad<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      multiples = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/BroadcastHelper.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/BroadcastHelper.java
index d32efe74374..31b51e9ef81 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/BroadcastHelper.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/BroadcastHelper.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -95,4 +99,41 @@ public Output<T> lhsOutput() {
   public Output<T> rhsOutput() {
     return rhsOutput;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<BroadcastHelper<T>> {
+    /**
+     * the LHS input tensor
+     */
+    public final Operand<T> lhs;
+
+    /**
+     * the RHS input tensor
+     */
+    public final Operand<T> rhs;
+
+    /**
+     * an XLA-style broadcast dimension specification
+     */
+    public final Operand<? extends TNumber> broadcastDims;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new BroadcastHelper<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      lhs = (Operand<T>) op.input(inputIndex++);
+      rhs = (Operand<T>) op.input(inputIndex++);
+      broadcastDims = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ClusterOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ClusterOutput.java
index 4f316783fd9..ad111378f34 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ClusterOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ClusterOutput.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,7 +57,7 @@ private ClusterOutput(Operation operation) {
    * Factory method to create a class wrapping a new XlaClusterOutput operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param <T> data type for {@code XlaClusterOutput} output and operands
    * @return a new instance of ClusterOutput
    */
@@ -79,4 +83,23 @@ public Output<T> outputs() {
   public Output<T> asOutput() {
     return outputs;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<ClusterOutput<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new ClusterOutput<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Conv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Conv.java
index 3ff4fc14d66..e8df7159368 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Conv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Conv.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -106,4 +110,89 @@ public Output<W> output() {
   public Output<W> asOutput() {
     return output;
   }
+
+  public static class Inputs<V extends TNumber> extends RawOpInputs<Conv<?>> {
+    /**
+     * the input tensor
+     */
+    public final Operand<? extends TType> lhs;
+
+    /**
+     * the kernel tensor
+     */
+    public final Operand<? extends TType> rhs;
+
+    /**
+     * the inter-window strides
+     */
+    public final Operand<V> windowStrides;
+
+    /**
+     * the padding to apply at the start and end of each input dimensions
+     */
+    public final Operand<V> padding;
+
+    /**
+     * dilation to apply between input elements
+     */
+    public final Operand<V> lhsDilation;
+
+    /**
+     * dilation to apply between kernel elements
+     */
+    public final Operand<V> rhsDilation;
+
+    /**
+     * number of feature groups for grouped convolution.
+     */
+    public final Operand<V> featureGroupCount;
+
+    /**
+     * The LhsT attribute
+     */
+    public final DataType LhsT;
+
+    /**
+     * The RhsT attribute
+     */
+    public final DataType RhsT;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    /**
+     * a serialized xla::ConvolutionDimensionNumbers proto.
+     */
+    public final String dimensionNumbers;
+
+    /**
+     * a serialized xla::PrecisionConfig proto.
+     */
+    public final String precisionConfig;
+
+    /**
+     * The type of the tensor.
+     */
+    public final DataType preferredElementType;
+
+    public Inputs(GraphOperation op) {
+      super(new Conv<>(op), op, Arrays.asList("LhsT", "RhsT", "Tindices", "dimension_numbers", "precision_config", "preferred_element_type"));
+      int inputIndex = 0;
+      lhs = (Operand<? extends TType>) op.input(inputIndex++);
+      rhs = (Operand<? extends TType>) op.input(inputIndex++);
+      windowStrides = (Operand<V>) op.input(inputIndex++);
+      padding = (Operand<V>) op.input(inputIndex++);
+      lhsDilation = (Operand<V>) op.input(inputIndex++);
+      rhsDilation = (Operand<V>) op.input(inputIndex++);
+      featureGroupCount = (Operand<V>) op.input(inputIndex++);
+      LhsT = op.attributes().getAttrType("LhsT");
+      RhsT = op.attributes().getAttrType("RhsT");
+      Tindices = op.attributes().getAttrType("Tindices");
+      dimensionNumbers = op.attributes().getAttrString("dimension_numbers");
+      precisionConfig = op.attributes().getAttrString("precision_config");
+      preferredElementType = op.attributes().getAttrType("preferred_element_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dequantize.java
index 40fb4ee2ecd..03cece9dc1e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dequantize.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -90,4 +93,42 @@ public Output<TBfloat16> output() {
   public Output<TBfloat16> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Dequantize> {
+    /**
+     * Input tensors whose types is uint32, shape is [d0, ..., dn].
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The minimum scalar value possibly produced for the input.
+     */
+    public final float minRange;
+
+    /**
+     * The maximum scalar value possibly produced for the input.
+     */
+    public final float maxRange;
+
+    /**
+     * String to determine the dequantize mode in {"MIN_COMBINED", "MIN_FIRST", "SCALED"}.
+     */
+    public final String mode;
+
+    /**
+     * Boolean to determine if output is transposed. transpose_output
+     * is faster when input is large and rank of input is higher than 1.
+     */
+    public final boolean transposeOutput;
+
+    public Inputs(GraphOperation op) {
+      super(new Dequantize(op), op, Arrays.asList("min_range", "max_range", "mode", "transpose_output"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      minRange = op.attributes().getAttrFloat("min_range");
+      maxRange = op.attributes().getAttrFloat("max_range");
+      mode = op.attributes().getAttrString("mode");
+      transposeOutput = op.attributes().getAttrBool("transpose_output");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dot.java
index 86253843b77..5e5c78e362c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dot.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Dot.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -92,4 +96,53 @@ public Output<V> output() {
   public Output<V> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<Dot<?>> {
+    /**
+     * the LHS tensor
+     */
+    public final Operand<? extends TType> lhs;
+
+    /**
+     * the RHS tensor
+     */
+    public final Operand<? extends TType> rhs;
+
+    /**
+     * The LhsT attribute
+     */
+    public final DataType LhsT;
+
+    /**
+     * The RhsT attribute
+     */
+    public final DataType RhsT;
+
+    /**
+     * a serialized xla::DotDimensionNumbers proto.
+     */
+    public final String dimensionNumbers;
+
+    /**
+     * a serialized xla::PrecisionConfig proto.
+     */
+    public final String precisionConfig;
+
+    /**
+     * The type of the tensor.
+     */
+    public final DataType preferredElementType;
+
+    public Inputs(GraphOperation op) {
+      super(new Dot<>(op), op, Arrays.asList("LhsT", "RhsT", "dimension_numbers", "precision_config", "preferred_element_type"));
+      int inputIndex = 0;
+      lhs = (Operand<? extends TType>) op.input(inputIndex++);
+      rhs = (Operand<? extends TType>) op.input(inputIndex++);
+      LhsT = op.attributes().getAttrType("LhsT");
+      RhsT = op.attributes().getAttrType("RhsT");
+      dimensionNumbers = op.attributes().getAttrString("dimension_numbers");
+      precisionConfig = op.attributes().getAttrString("precision_config");
+      preferredElementType = op.attributes().getAttrType("preferred_element_type");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicSlice.java
index 93d22721098..65f082eabc2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicSlice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicSlice.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -66,7 +70,7 @@ private DynamicSlice(Operation operation) {
    * dimension. Each value must be strictly greater than zero, and start + size
    * must be less than or equal to the size of the dimension to avoid
    * implementation defined behavior.
-   * @param sizeIndices the sizeIndices value
+   * @param sizeIndices The sizeIndices value
    * @param <T> data type for {@code XlaDynamicSlice} output and operands
    * @param <U> data type for {@code XlaDynamicSlice} output and operands
    * @return a new instance of DynamicSlice
@@ -96,4 +100,44 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<DynamicSlice<T>> {
+    /**
+     * A {@code Tensor} of type T.
+     */
+    public final Operand<T> input;
+
+    /**
+     * List of N integers containing the slice size for each
+     * dimension. Each value must be strictly greater than zero, and start + size
+     * must be less than or equal to the size of the dimension to avoid
+     * implementation defined behavior.
+     */
+    public final Operand<U> startIndices;
+
+    /**
+     * The sizeIndices input
+     */
+    public final Operand<U> sizeIndices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new DynamicSlice<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      startIndices = (Operand<U>) op.input(inputIndex++);
+      sizeIndices = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicUpdateSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicUpdateSlice.java
index 0355ff82f53..e1a4c0e7574 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicUpdateSlice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/DynamicUpdateSlice.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -93,4 +97,42 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<DynamicUpdateSlice<T>> {
+    /**
+     * A {@code Tensor} of type T.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A {@code Tensor} of type T. Same rank as {@code input}.
+     */
+    public final Operand<T> update;
+
+    /**
+     * A vector of indices into {@code input}. Must have length equal to the rank of
+     * {@code input}.
+     */
+    public final Operand<? extends TNumber> indices;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new DynamicUpdateSlice<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      update = (Operand<T>) op.input(inputIndex++);
+      indices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Einsum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Einsum.java
index 304d7a3889b..3048c1e6f06 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Einsum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Einsum.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -55,9 +59,9 @@ private Einsum(Operation operation) {
    * Factory method to create a class wrapping a new XlaEinsum operation.
    *
    * @param scope current scope
-   * @param a the a value
-   * @param b the b value
-   * @param equation the value of the equation property
+   * @param a The a value
+   * @param b The b value
+   * @param equation The value of the equation attribute
    * @param <T> data type for {@code XlaEinsum} output and operands
    * @return a new instance of Einsum
    */
@@ -86,4 +90,35 @@ public Output<T> product() {
   public Output<T> asOutput() {
     return product;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Einsum<T>> {
+    /**
+     * The a input
+     */
+    public final Operand<T> a;
+
+    /**
+     * The b input
+     */
+    public final Operand<T> b;
+
+    /**
+     * The equation attribute
+     */
+    public final String equation;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Einsum<>(op), op, Arrays.asList("equation", "T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      b = (Operand<T>) op.input(inputIndex++);
+      equation = op.attributes().getAttrString("equation");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Gather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Gather.java
index e24dc9531ad..d8b7cf0421a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Gather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Gather.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -92,4 +96,53 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<Gather<T>> {
+    /**
+     * The array we're gathering from.
+     */
+    public final Operand<T> operand;
+
+    /**
+     * Array containing the starting indices of the slices we gather.
+     */
+    public final Operand<U> startIndices;
+
+    /**
+     * slice_sizes[i] is the bounds for the slice on dimension i.
+     */
+    public final Operand<U> sliceSizes;
+
+    /**
+     * A serialized xla::GatherDimensionNumbers proto.
+     */
+    public final String dimensionNumbers;
+
+    /**
+     * Boolean indicating if the indices are sorted.
+     */
+    public final boolean indicesAreSorted;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new Gather<>(op), op, Arrays.asList("dimension_numbers", "indices_are_sorted", "T", "Tindices"));
+      int inputIndex = 0;
+      operand = (Operand<T>) op.input(inputIndex++);
+      startIndices = (Operand<U>) op.input(inputIndex++);
+      sliceSizes = (Operand<U>) op.input(inputIndex++);
+      dimensionNumbers = op.attributes().getAttrString("dimension_numbers");
+      indicesAreSorted = op.attributes().getAttrBool("indices_are_sorted");
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/If.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/If.java
index f12401bc398..31ac4815360 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/If.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/If.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -65,7 +68,7 @@ private If(Operation operation) {
    * whose types are the same as what else_branch returns.
    * @param elseBranch A function takes 'inputs' and returns a list of tensors.
    * whose types are the same as what then_branch returns.
-   * @param Tout the value of the Tout property
+   * @param Tout The value of the Tout attribute
    * @return a new instance of If
    */
   @Endpoint(
@@ -99,4 +102,43 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<If> {
+    /**
+     * A boolean scalar.
+     */
+    public final Operand<? extends TType> cond;
+
+    /**
+     * A list of input tensors.
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The Tcond attribute
+     */
+    public final DataType Tcond;
+
+    /**
+     * The Tin attribute
+     */
+    public final DataType[] Tin;
+
+    /**
+     * The Tout attribute
+     */
+    public final DataType[] Tout;
+
+    public Inputs(GraphOperation op) {
+      super(new If(op), op, Arrays.asList("Tcond", "Tin", "Tout"));
+      int inputIndex = 0;
+      cond = (Operand<? extends TType>) op.input(inputIndex++);
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      Tcond = op.attributes().getAttrType("Tcond");
+      Tin = op.attributes().getAttrTypeList("Tin");
+      Tout = op.attributes().getAttrTypeList("Tout");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/KeyValueSort.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/KeyValueSort.java
index c2e896d70f8..ad72e80c6f0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/KeyValueSort.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/KeyValueSort.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -96,4 +100,35 @@ public Output<T> sortedKeys() {
   public Output<U> sortedValues() {
     return sortedValues;
   }
+
+  public static class Inputs<T extends TNumber, U extends TType> extends RawOpInputs<KeyValueSort<T, U>> {
+    /**
+     * A {@code Tensor} of type K.
+     */
+    public final Operand<T> keys;
+
+    /**
+     * A {@code Tensor} of type V.
+     */
+    public final Operand<U> values;
+
+    /**
+     * The K attribute
+     */
+    public final DataType K;
+
+    /**
+     * The V attribute
+     */
+    public final DataType V;
+
+    public Inputs(GraphOperation op) {
+      super(new KeyValueSort<>(op), op, Arrays.asList("K", "V"));
+      int inputIndex = 0;
+      keys = (Operand<T>) op.input(inputIndex++);
+      values = (Operand<U>) op.input(inputIndex++);
+      K = op.attributes().getAttrType("K");
+      V = op.attributes().getAttrType("V");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Pad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Pad.java
index ef323534772..f28df38bbe0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Pad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Pad.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -97,4 +101,57 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<Pad<T>> {
+    /**
+     * A {@code Tensor} of type T.
+     */
+    public final Operand<T> input;
+
+    /**
+     * A scalar {@code Tensor} of type T.
+     */
+    public final Operand<T> paddingValue;
+
+    /**
+     * the padding to apply at the start of each input dimensions. Must
+     * be a compile-time constant 1D tensor of length equal to rank of input.
+     */
+    public final Operand<U> paddingLow;
+
+    /**
+     * the padding to apply at the end of each input dimension. Must
+     * be a compile-time constant 1D tensor of length equal to rank of input.
+     */
+    public final Operand<U> paddingHigh;
+
+    /**
+     * the padding to apply between each input element. Must
+     * be a compile-time constant 1D tensor of length equal to rank of input,
+     * containing only non-negative values.
+     */
+    public final Operand<U> paddingInterior;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new Pad<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      paddingValue = (Operand<T>) op.input(inputIndex++);
+      paddingLow = (Operand<U>) op.input(inputIndex++);
+      paddingHigh = (Operand<U>) op.input(inputIndex++);
+      paddingInterior = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java
index a66c8d99037..a660cd82f4c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -88,4 +92,29 @@ public Output<T> tensor() {
   public Output<T> asOutput() {
     return tensor;
   }
+
+  public static class Inputs extends RawOpInputs<Recv<?>> {
+    /**
+     * The type of the tensor.
+     */
+    public final DataType dtype;
+
+    /**
+     * A string key that identifies the channel.
+     */
+    public final String tensorName;
+
+    /**
+     * The shape of the tensor.
+     */
+    public final Shape shape;
+
+    public Inputs(GraphOperation op) {
+      super(new Recv<>(op), op, Arrays.asList("dtype", "tensor_name", "shape"));
+      int inputIndex = 0;
+      dtype = op.attributes().getAttrType("dtype");
+      tensorName = op.attributes().getAttrString("tensor_name");
+      shape = op.attributes().getAttrShape("shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Reduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Reduce.java
index 2f96544c034..3e25c7db1c0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Reduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Reduce.java
@@ -17,16 +17,20 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -93,4 +97,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Reduce<T>> {
+    /**
+     * the input tensor
+     */
+    public final Operand<T> input;
+
+    /**
+     * a scalar representing the initial value for the reduction
+     */
+    public final Operand<T> initValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * dimension numbers over which to reduce
+     */
+    public final long[] dimensionsToReduce;
+
+    public Inputs(GraphOperation op) {
+      super(new Reduce<>(op), op, Arrays.asList("T", "dimensions_to_reduce"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      initValue = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      dimensionsToReduce = op.attributes().getAttrIntList("dimensions_to_reduce");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReduceWindow.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReduceWindow.java
index a644b94382c..41cf0d5cfbe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReduceWindow.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReduceWindow.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -60,8 +64,8 @@ private ReduceWindow(Operation operation) {
    * @param initValue a scalar representing the initial value for the reduction
    * @param windowDimensions the shape of the window
    * @param windowStrides the inter-window strides
-   * @param baseDilations the baseDilations value
-   * @param windowDilations the windowDilations value
+   * @param baseDilations The baseDilations value
+   * @param windowDilations The windowDilations value
    * @param padding the padding to apply at the start and end of each input dimensions
    * @param computation a reducer function to apply
    * @param <T> data type for {@code XlaReduceWindow} output and operands
@@ -100,4 +104,65 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<ReduceWindow<T>> {
+    /**
+     * the input tensor
+     */
+    public final Operand<T> input;
+
+    /**
+     * a scalar representing the initial value for the reduction
+     */
+    public final Operand<T> initValue;
+
+    /**
+     * the shape of the window
+     */
+    public final Operand<U> windowDimensions;
+
+    /**
+     * the inter-window strides
+     */
+    public final Operand<U> windowStrides;
+
+    /**
+     * The baseDilations input
+     */
+    public final Operand<U> baseDilations;
+
+    /**
+     * The windowDilations input
+     */
+    public final Operand<U> windowDilations;
+
+    /**
+     * the padding to apply at the start and end of each input dimensions
+     */
+    public final Operand<U> padding;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new ReduceWindow<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      initValue = (Operand<T>) op.input(inputIndex++);
+      windowDimensions = (Operand<U>) op.input(inputIndex++);
+      windowStrides = (Operand<U>) op.input(inputIndex++);
+      baseDilations = (Operand<U>) op.input(inputIndex++);
+      windowDilations = (Operand<U>) op.input(inputIndex++);
+      padding = (Operand<U>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/RemoveDynamicDimensionSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/RemoveDynamicDimensionSize.java
index 2aa9d0b3b48..b657a92ee72 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/RemoveDynamicDimensionSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/RemoveDynamicDimensionSize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -58,8 +62,8 @@ private RemoveDynamicDimensionSize(Operation operation) {
    * Factory method to create a class wrapping a new XlaRemoveDynamicDimensionSize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param dimIndex the dimIndex value
+   * @param input The input value
+   * @param dimIndex The dimIndex value
    * @param <T> data type for {@code XlaRemoveDynamicDimensionSize} output and operands
    * @return a new instance of RemoveDynamicDimensionSize
    */
@@ -87,4 +91,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<RemoveDynamicDimensionSize<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimIndex input
+     */
+    public final Operand<TInt32> dimIndex;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new RemoveDynamicDimensionSize<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      dimIndex = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReplicaId.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReplicaId.java
index d6a886ea393..9b12ea45151 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReplicaId.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReplicaId.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -74,4 +77,11 @@ public Output<TInt32> id() {
   public Output<TInt32> asOutput() {
     return id;
   }
+
+  public static class Inputs extends RawOpInputs<ReplicaId> {
+    public Inputs(GraphOperation op) {
+      super(new ReplicaId(op), op, Arrays.asList());
+      int inputIndex = 0;
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Scatter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Scatter.java
index 36f7e495841..f5114c2979a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Scatter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Scatter.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -96,4 +100,54 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Scatter<T>> {
+    /**
+     * Array to be scattered into.
+     */
+    public final Operand<T> operand;
+
+    /**
+     * Array containing the starting indices of the slices that must
+     * be scattered to.
+     */
+    public final Operand<? extends TNumber> scatterIndices;
+
+    /**
+     * Array containing the values that must be used for scattering.
+     */
+    public final Operand<T> updates;
+
+    /**
+     * A serialized xla::ScatterDimensionNumbers proto.
+     */
+    public final String dimensionNumbers;
+
+    /**
+     * Boolean indicating if the indices are sorted.
+     */
+    public final boolean indicesAreSorted;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new Scatter<>(op), op, Arrays.asList("dimension_numbers", "indices_are_sorted", "T", "Tindices"));
+      int inputIndex = 0;
+      operand = (Operand<T>) op.input(inputIndex++);
+      scatterIndices = (Operand<? extends TNumber>) op.input(inputIndex++);
+      updates = (Operand<T>) op.input(inputIndex++);
+      dimensionNumbers = op.attributes().getAttrString("dimension_numbers");
+      indicesAreSorted = op.attributes().getAttrBool("indices_are_sorted");
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelectAndScatter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelectAndScatter.java
index 8da8b04a540..715c01a5a53 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelectAndScatter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelectAndScatter.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
@@ -100,4 +104,59 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType, U extends TNumber> extends RawOpInputs<SelectAndScatter<T>> {
+    /**
+     * the input tensor
+     */
+    public final Operand<T> operand;
+
+    /**
+     * the shape of the window
+     */
+    public final Operand<U> windowDimensions;
+
+    /**
+     * the inter-window strides
+     */
+    public final Operand<U> windowStrides;
+
+    /**
+     * the padding to apply at the start and end of each input dimensions
+     */
+    public final Operand<U> padding;
+
+    /**
+     * a tensor of values to scatter
+     */
+    public final Operand<T> source;
+
+    /**
+     * a scalar representing the initial value for the output tensor
+     */
+    public final Operand<T> initValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The Tindices attribute
+     */
+    public final DataType Tindices;
+
+    public Inputs(GraphOperation op) {
+      super(new SelectAndScatter<>(op), op, Arrays.asList("T", "Tindices"));
+      int inputIndex = 0;
+      operand = (Operand<T>) op.input(inputIndex++);
+      windowDimensions = (Operand<U>) op.input(inputIndex++);
+      windowStrides = (Operand<U>) op.input(inputIndex++);
+      padding = (Operand<U>) op.input(inputIndex++);
+      source = (Operand<T>) op.input(inputIndex++);
+      initValue = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      Tindices = op.attributes().getAttrType("Tindices");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelfAdjointEig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelfAdjointEig.java
index 144760c036a..0c190e36fe0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelfAdjointEig.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SelfAdjointEig.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -103,4 +107,45 @@ public Output<T> w() {
   public Output<T> v() {
     return v;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SelfAdjointEig<T>> {
+    /**
+     * the input tensor.
+     */
+    public final Operand<T> a;
+
+    /**
+     * a boolean specifies whether the calculation is done with the lower
+     * triangular part or the upper triangular part.
+     */
+    public final boolean lower;
+
+    /**
+     * maximum number of sweep update, i.e., the whole lower triangular
+     * part or upper triangular part based on parameter lower. Heuristically, it has
+     * been argued that approximately logN sweeps are needed in practice (Ref: Golub &
+     * van Loan "Matrix Computation").
+     */
+    public final long maxIter;
+
+    /**
+     * the tolerance ratio.
+     */
+    public final float epsilon;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SelfAdjointEig<>(op), op, Arrays.asList("lower", "max_iter", "epsilon", "T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      lower = op.attributes().getAttrBool("lower");
+      maxIter = op.attributes().getAttrInt("max_iter");
+      epsilon = op.attributes().getAttrFloat("epsilon");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Send.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Send.java
index a83150321d6..bb5010128fa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Send.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Send.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -61,4 +65,29 @@ public static Send create(Scope scope, Operand<? extends TType> tensor, String t
     opBuilder.setAttr("tensor_name", tensorName);
     return new Send(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<Send> {
+    /**
+     * The tensor to send.
+     */
+    public final Operand<? extends TType> tensor;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * A string key that identifies the channel.
+     */
+    public final String tensorName;
+
+    public Inputs(GraphOperation op) {
+      super(new Send(op), op, Arrays.asList("T", "tensor_name"));
+      int inputIndex = 0;
+      tensor = (Operand<? extends TType>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      tensorName = op.attributes().getAttrString("tensor_name");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SetDynamicDimensionSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SetDynamicDimensionSize.java
index 29f605bdc08..00c232c5319 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SetDynamicDimensionSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SetDynamicDimensionSize.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -58,9 +62,9 @@ private SetDynamicDimensionSize(Operation operation) {
    * Factory method to create a class wrapping a new XlaSetDynamicDimensionSize operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param dimIndex the dimIndex value
-   * @param sizeOutput the sizeOutput value
+   * @param input The input value
+   * @param dimIndex The dimIndex value
+   * @param sizeOutput The sizeOutput value
    * @param <T> data type for {@code XlaSetDynamicDimensionSize} output and operands
    * @return a new instance of SetDynamicDimensionSize
    */
@@ -89,4 +93,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SetDynamicDimensionSize<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The dimIndex input
+     */
+    public final Operand<TInt32> dimIndex;
+
+    /**
+     * The sizeOutput input
+     */
+    public final Operand<TInt32> sizeOutput;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new SetDynamicDimensionSize<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      dimIndex = (Operand<TInt32>) op.input(inputIndex++);
+      sizeOutput = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sharding.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sharding.java
index d0492f727e4..d39f3f93f21 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sharding.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sharding.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -53,7 +57,7 @@ private Sharding(Operation operation) {
    * Factory method to create a class wrapping a new XlaSharding operation.
    *
    * @param scope current scope
-   * @param input the input value
+   * @param input The input value
    * @param options carries optional attribute values
    * @param <T> data type for {@code XlaSharding} output and operands
    * @return a new instance of Sharding
@@ -119,4 +123,29 @@ public Options sharding(String sharding) {
       return this;
     }
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sharding<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The sharding attribute
+     */
+    public final String sharding;
+
+    public Inputs(GraphOperation op) {
+      super(new Sharding<>(op), op, Arrays.asList("T", "sharding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      sharding = op.attributes().getAttrString("sharding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sort.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sort.java
index fd61baf997a..70056c2c7c1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sort.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Sort.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -82,4 +86,23 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Sort<T>> {
+    /**
+     * A {@code Tensor} of type T.
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Sort<>(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdFullToShardShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdFullToShardShape.java
index c03b66f8d88..b717ed45b8b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdFullToShardShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdFullToShardShape.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,8 +61,8 @@ private SpmdFullToShardShape(Operation operation) {
    * Factory method to create a class wrapping a new XlaSpmdFullToShardShape operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param manualSharding the value of the manualSharding property
+   * @param input The input value
+   * @param manualSharding The value of the manualSharding attribute
    * @param <T> data type for {@code XlaSpmdFullToShardShape} output and operands
    * @return a new instance of SpmdFullToShardShape
    */
@@ -86,4 +90,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SpmdFullToShardShape<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The manualSharding attribute
+     */
+    public final String manualSharding;
+
+    public Inputs(GraphOperation op) {
+      super(new SpmdFullToShardShape<>(op), op, Arrays.asList("T", "manual_sharding"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      manualSharding = op.attributes().getAttrString("manual_sharding");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdShardToFullShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdShardToFullShape.java
index 8e44eb9e374..3a86c8b7b26 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdShardToFullShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SpmdShardToFullShape.java
@@ -17,15 +17,19 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,9 +61,9 @@ private SpmdShardToFullShape(Operation operation) {
    * Factory method to create a class wrapping a new XlaSpmdShardToFullShape operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param manualSharding the value of the manualSharding property
-   * @param fullShape the value of the fullShape property
+   * @param input The input value
+   * @param manualSharding The value of the manualSharding attribute
+   * @param fullShape The value of the fullShape attribute
    * @param <T> data type for {@code XlaSpmdShardToFullShape} output and operands
    * @return a new instance of SpmdShardToFullShape
    */
@@ -88,4 +92,35 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<SpmdShardToFullShape<T>> {
+    /**
+     * The input input
+     */
+    public final Operand<T> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * The manualSharding attribute
+     */
+    public final String manualSharding;
+
+    /**
+     * The fullShape attribute
+     */
+    public final Shape fullShape;
+
+    public Inputs(GraphOperation op) {
+      super(new SpmdShardToFullShape<>(op), op, Arrays.asList("T", "manual_sharding", "full_shape"));
+      int inputIndex = 0;
+      input = (Operand<T>) op.input(inputIndex++);
+      T = op.attributes().getAttrType("T");
+      manualSharding = op.attributes().getAttrString("manual_sharding");
+      fullShape = op.attributes().getAttrShape("full_shape");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Svd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Svd.java
index c979831e460..e6049fbf8fd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Svd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Svd.java
@@ -17,14 +17,18 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -112,4 +116,44 @@ public Output<T> u() {
   public Output<T> v() {
     return v;
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<Svd<T>> {
+    /**
+     * the input tensor.
+     */
+    public final Operand<T> a;
+
+    /**
+     * maximum number of sweep update, i.e., the whole lower triangular
+     * part or upper triangular part based on parameter lower. Heuristically, it has
+     * been argued that approximately log(min (M, N)) sweeps are needed in practice
+     * (Ref: Golub & van Loan "Matrix Computation").
+     */
+    public final long maxIter;
+
+    /**
+     * the tolerance ratio.
+     */
+    public final float epsilon;
+
+    /**
+     * a serialized xla::PrecisionConfig proto.
+     */
+    public final String precisionConfig;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    public Inputs(GraphOperation op) {
+      super(new Svd<>(op), op, Arrays.asList("max_iter", "epsilon", "precision_config", "T"));
+      int inputIndex = 0;
+      a = (Operand<T>) op.input(inputIndex++);
+      maxIter = op.attributes().getAttrInt("max_iter");
+      epsilon = op.attributes().getAttrFloat("epsilon");
+      precisionConfig = op.attributes().getAttrString("precision_config");
+      T = op.attributes().getAttrType("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/While.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/While.java
index 9e9ada04295..80002335b2b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/While.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/While.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -98,4 +101,25 @@ public List<Output<?>> output() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<While> {
+    /**
+     * A list of input tensors whose types are T.
+     */
+    public final Iterable<Operand<?>> input;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    public Inputs(GraphOperation op) {
+      super(new While(op), op, Arrays.asList("T"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      T = op.attributes().getAttrTypeList("T");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java
index 6e8d38cd19a..fcb5d6234e0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java
@@ -21,6 +21,7 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -28,9 +29,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -225,4 +228,74 @@ public Options tpuCore(Long tpuCore) {
       return this;
     }
   }
+
+  public static class Inputs extends RawOpInputs<XlaHostCompute> {
+    /**
+     * A list of tensors that will be sent to the host.
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The element types of each element in `inputs`.
+     */
+    public final DataType[] Tinputs;
+
+    /**
+     * The element types of each element in `outputs`.
+     */
+    public final DataType[] Toutputs;
+
+    /**
+     * A list of names of HostCompute computations that must be
+     * sequenced before this computation.
+     */
+    public final String[] ancestors;
+
+    /**
+     * If shape_inference_graph is empty, a list of the shapes of `outputs`.
+     */
+    public final Shape[] shapes;
+
+    /**
+     * A unique identifier for this region used to match up host transfers.
+     */
+    public final String key;
+
+    /**
+     * The sendKey attribute
+     */
+    public final String sendKey;
+
+    /**
+     * The recvKey attribute
+     */
+    public final String recvKey;
+
+    /**
+     * Estimated duration of the host computation in nanoseconds.
+     */
+    public final long costEstimateNs;
+
+    /**
+     * Default core to use for host to device transfers.
+     */
+    public final long tpuCore;
+
+    public Inputs(GraphOperation op) {
+      super(new XlaHostCompute(op), op, Arrays.asList("Tinputs", "Toutputs", "ancestors", "shapes", "key", "send_key", "recv_key", "cost_estimate_ns", "tpu_core"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      Tinputs = op.attributes().getAttrTypeList("Tinputs");
+      Toutputs = op.attributes().getAttrTypeList("Toutputs");
+      ancestors = op.attributes().getAttrStringList("ancestors");
+      shapes = op.attributes().getAttrShapeList("shapes");
+      key = op.attributes().getAttrString("key");
+      sendKey = op.attributes().getAttrString("send_key");
+      recvKey = op.attributes().getAttrString("recv_key");
+      costEstimateNs = op.attributes().getAttrInt("cost_estimate_ns");
+      tpuCore = op.attributes().getAttrInt("tpu_core");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaLaunch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaLaunch.java
index 6e83c779c1b..d8c864cea8f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaLaunch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaLaunch.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,11 +62,11 @@ private XlaLaunch(Operation operation) {
    * Factory method to create a class wrapping a new XlaLaunch operation.
    *
    * @param scope current scope
-   * @param constants the constants value
-   * @param args the args value
-   * @param resources the resources value
-   * @param Tresults the value of the Tresults property
-   * @param function the value of the function property
+   * @param constants The constants value
+   * @param args The args value
+   * @param resources The resources value
+   * @param Tresults The value of the Tresults attribute
+   * @param function The value of the function attribute
    * @return a new instance of XlaLaunch
    */
   @Endpoint(
@@ -95,4 +98,53 @@ public List<Output<?>> results() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) results.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<XlaLaunch> {
+    /**
+     * The constants input
+     */
+    public final Iterable<Operand<?>> constants;
+
+    /**
+     * The args input
+     */
+    public final Iterable<Operand<?>> args;
+
+    /**
+     * The resources input
+     */
+    public final Iterable<Operand<? extends TType>> resources;
+
+    /**
+     * The Tconstants attribute
+     */
+    public final DataType[] Tconstants;
+
+    /**
+     * The Targs attribute
+     */
+    public final DataType[] Targs;
+
+    /**
+     * The Tresults attribute
+     */
+    public final DataType[] Tresults;
+
+    public Inputs(GraphOperation op) {
+      super(new XlaLaunch(op), op, Arrays.asList("Tconstants", "Targs", "Tresults"));
+      int inputIndex = 0;
+      int constantsLength = op.inputListLength("constants");
+      constants = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, constantsLength));
+      inputIndex += constantsLength;
+      int argsLength = op.inputListLength("args");
+      args = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, argsLength));
+      inputIndex += argsLength;
+      int resourcesLength = op.inputListLength("resources");
+      resources = Arrays.asList((Operand<? extends TType>[]) op.inputList(inputIndex, resourcesLength));
+      inputIndex += resourcesLength;
+      Tconstants = op.attributes().getAttrTypeList("Tconstants");
+      Targs = op.attributes().getAttrTypeList("Targs");
+      Tresults = op.attributes().getAttrTypeList("Tresults");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java
index 06178290708..289a7ff2853 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java
@@ -17,6 +17,8 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -24,9 +26,11 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -59,9 +63,9 @@ private XlaRecvFromHost(Operation operation) {
    * Factory method to create a class wrapping a new XlaRecvFromHost operation.
    *
    * @param scope current scope
-   * @param Toutput the value of the Toutput property
-   * @param shape the value of the shape property
-   * @param key the value of the key property
+   * @param Toutput The value of the Toutput attribute
+   * @param shape The value of the shape attribute
+   * @param key The value of the key attribute
    * @param <T> data type for {@code XlaRecvFromHost} output and operands
    * @return a new instance of XlaRecvFromHost
    */
@@ -90,4 +94,29 @@ public Output<T> output() {
   public Output<T> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<XlaRecvFromHost<?>> {
+    /**
+     * The Toutput attribute
+     */
+    public final DataType Toutput;
+
+    /**
+     * The shape attribute
+     */
+    public final Shape shape;
+
+    /**
+     * The key attribute
+     */
+    public final String key;
+
+    public Inputs(GraphOperation op) {
+      super(new XlaRecvFromHost<>(op), op, Arrays.asList("Toutput", "shape", "key"));
+      int inputIndex = 0;
+      Toutput = op.attributes().getAttrType("Toutput");
+      shape = op.attributes().getAttrShape("shape");
+      key = op.attributes().getAttrString("key");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSendToHost.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSendToHost.java
index 25a9226f6ff..41478534837 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSendToHost.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSendToHost.java
@@ -17,13 +17,17 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -49,8 +53,8 @@ private XlaSendToHost(Operation operation) {
    * Factory method to create a class wrapping a new XlaSendToHost operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param key the value of the key property
+   * @param input The input value
+   * @param key The value of the key attribute
    * @return a new instance of XlaSendToHost
    */
   @Endpoint(
@@ -62,4 +66,29 @@ public static XlaSendToHost create(Scope scope, Operand<? extends TType> input,
     opBuilder.setAttr("key", key);
     return new XlaSendToHost(opBuilder.build());
   }
+
+  public static class Inputs extends RawOpInputs<XlaSendToHost> {
+    /**
+     * The input input
+     */
+    public final Operand<? extends TType> input;
+
+    /**
+     * The Tinput attribute
+     */
+    public final DataType Tinput;
+
+    /**
+     * The key attribute
+     */
+    public final String key;
+
+    public Inputs(GraphOperation op) {
+      super(new XlaSendToHost(op), op, Arrays.asList("Tinput", "key"));
+      int inputIndex = 0;
+      input = (Operand<? extends TType>) op.input(inputIndex++);
+      Tinput = op.attributes().getAttrType("Tinput");
+      key = op.attributes().getAttrString("key");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSetBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSetBound.java
index 22ae3a04750..7c51caf3b3b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSetBound.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSetBound.java
@@ -17,11 +17,14 @@
 
 package org.tensorflow.op.xla;
 
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -54,8 +57,8 @@ private XlaSetBound(Operation operation) {
    * Factory method to create a class wrapping a new XlaSetBound operation.
    *
    * @param scope current scope
-   * @param input the input value
-   * @param bound the bound value
+   * @param input The input value
+   * @param bound The bound value
    * @return a new instance of XlaSetBound
    */
   @Endpoint(
@@ -81,4 +84,23 @@ public Output<TInt32> output() {
   public Output<TInt32> asOutput() {
     return output;
   }
+
+  public static class Inputs extends RawOpInputs<XlaSetBound> {
+    /**
+     * The input input
+     */
+    public final Operand<TInt32> input;
+
+    /**
+     * The bound input
+     */
+    public final Operand<TInt32> bound;
+
+    public Inputs(GraphOperation op) {
+      super(new XlaSetBound(op), op, Arrays.asList());
+      int inputIndex = 0;
+      input = (Operand<TInt32>) op.input(inputIndex++);
+      bound = (Operand<TInt32>) op.input(inputIndex++);
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicReduce.java
index 2ac5ca797e5..15523c32a6e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicReduce.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -102,4 +105,39 @@ public List<Output<T>> output() {
   public Iterator<Operand<T>> iterator() {
     return (Iterator) output.iterator();
   }
+
+  public static class Inputs<T extends TType> extends RawOpInputs<XlaVariadicReduce<T>> {
+    /**
+     * the input tensor(s)
+     */
+    public final Iterable<Operand<T>> input;
+
+    /**
+     * scalar initial value(s) for the reduction
+     */
+    public final Iterable<Operand<T>> initValue;
+
+    /**
+     * The T attribute
+     */
+    public final DataType T;
+
+    /**
+     * dimension numbers over which to reduce
+     */
+    public final long[] dimensionsToReduce;
+
+    public Inputs(GraphOperation op) {
+      super(new XlaVariadicReduce<>(op), op, Arrays.asList("T", "dimensions_to_reduce"));
+      int inputIndex = 0;
+      int inputLength = op.inputListLength("input");
+      input = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, inputLength));
+      inputIndex += inputLength;
+      int initValueLength = op.inputListLength("init_value");
+      initValue = Arrays.asList((Operand<T>[]) op.inputList(inputIndex, initValueLength));
+      inputIndex += initValueLength;
+      T = op.attributes().getAttrType("T");
+      dimensionsToReduce = op.attributes().getAttrIntList("dimensions_to_reduce");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicSort.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicSort.java
index c4c8f9f7be4..8570842977b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicSort.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaVariadicSort.java
@@ -21,15 +21,18 @@
 import java.util.Iterator;
 import java.util.List;
 import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
@@ -99,4 +102,37 @@ public List<Output<?>> outputs() {
   public Iterator<Operand<TType>> iterator() {
     return (Iterator) outputs.iterator();
   }
+
+  public static class Inputs extends RawOpInputs<XlaVariadicSort> {
+    /**
+     * A list of {@code Tensor} of identical shape but possibly different types.
+     */
+    public final Iterable<Operand<?>> inputs;
+
+    /**
+     * The dimension along which to sort. Must be a compile-time constant.
+     */
+    public final Operand<TInt32> dimension;
+
+    /**
+     * The T attribute
+     */
+    public final DataType[] T;
+
+    /**
+     * Whether to use stable sort.
+     */
+    public final boolean isStable;
+
+    public Inputs(GraphOperation op) {
+      super(new XlaVariadicSort(op), op, Arrays.asList("T", "is_stable"));
+      int inputIndex = 0;
+      int inputsLength = op.inputListLength("inputs");
+      inputs = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, inputsLength));
+      inputIndex += inputsLength;
+      dimension = (Operand<TInt32>) op.input(inputIndex++);
+      T = op.attributes().getAttrTypeList("T");
+      isStable = op.attributes().getAttrBool("is_stable");
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java
index fa705ca6ea6..29449847be8 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java
@@ -118,6 +118,7 @@ public boolean equals(Object o) {
 
   @Override
   Shape shape(int outputIndex) {
+
     // If the tensor of this output has already been resolved, return its shape.
     // Otherwise, retrieve the tensor shape from the native library.
     Tensor tensor = outputTensors.get(outputIndex);
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java
index cc47083bfce..6de072ee101 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java
@@ -33,6 +33,7 @@
 import static org.tensorflow.internal.c_api.global.tensorflow.TFE_OpSetAttrTensor;
 import static org.tensorflow.internal.c_api.global.tensorflow.TFE_OpSetAttrType;
 import static org.tensorflow.internal.c_api.global.tensorflow.TFE_OpSetAttrTypeList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TFE_OpSetAttrValueProto;
 import static org.tensorflow.internal.c_api.global.tensorflow.TFE_OpSetDevice;
 
 import java.nio.charset.Charset;
@@ -54,6 +55,7 @@
 import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Scope;
+import org.tensorflow.proto.framework.AttrValue;
 import org.tensorflow.proto.framework.DataType;
 
 /**
@@ -250,7 +252,13 @@ public OperationBuilder setAttr(String name, ConcreteFunction[] value) {
     return this;
   }
 
-  private TFE_Op opHandle;
+  @Override
+  public OperationBuilder setAttr(String name, AttrValue value) {
+    setAttrValue(opHandle, name, value);
+    return this;
+  }
+
+  private final TFE_Op opHandle;
 
   private final EagerSession session;
   private final String type;
@@ -475,4 +483,14 @@ private static void setAttrFunctionList(
       TFE_OpSetAttrFunctionList(opHandle, new BytePointer(attrName), fns, functionNames.size());
     }
   }
+
+  private static void setAttrValue(TFE_Op opHandle, String name, AttrValue value) {
+    requireOp(opHandle);
+    try (PointerScope scope = new PointerScope()) {
+      TF_Status status = TF_Status.newStatus();
+      byte[] bytes = value.toByteArray();
+      TFE_OpSetAttrValueProto(opHandle, name, new BytePointer(bytes), bytes.length, status);
+      status.throwExceptionIfNotOK();
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java
index b97ef09a9e4..d811139e9a2 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java
@@ -18,8 +18,10 @@
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_GraphGetTensorNumDims;
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_GraphGetTensorShape;
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationAllInputs;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationDevice;
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetControlInputs;
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetControlOutputs;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationInput;
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationInputListLength;
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationName;
 import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationNumControlInputs;
@@ -36,6 +38,7 @@
 import java.util.LinkedHashSet;
 import java.util.List;
 import java.util.Set;
+import java.util.concurrent.atomic.AtomicReference;
 import org.bytedeco.javacpp.Pointer;
 import org.bytedeco.javacpp.PointerPointer;
 import org.bytedeco.javacpp.PointerScope;
@@ -184,16 +187,62 @@ Tensor tensor(int outputIdx) {
     throw new IllegalStateException("Graph tensors must be fetched by running a session");
   }
 
-  /**
-   * Get the number of inputs to the op, not including control inputs.
-   */
+  /** Get the op's device. */
+  public String device() {
+    return TF_OperationDevice(getCheckedNativeHandle()).getString();
+  }
+
+  /** Get the number of inputs to the op, not including control inputs. */
   public int numInputs() {
     return TF_OperationNumInputs(getUnsafeNativeHandle());
   }
 
+  /** Gets the input at the given index */
+  public Output<?> input(int idx) {
+    if (idx < 0) {
+      throw new IndexOutOfBoundsException("Can't get input with index < 0.");
+    }
+
+    int numInputs = numInputs();
+    if (idx >= numInputs) {
+      throw new IndexOutOfBoundsException(
+          "Can't get input with index " + idx + ", this op only has " + numInputs + " inputs.");
+    }
+
+    try (PointerScope scope = new PointerScope()) {
+      TF_Input input = new TF_Input().oper(getUnsafeNativeHandle()).index(idx);
+      TF_Output output = TF_OperationInput(input);
+      String opName = TF_OperationName(output.oper()).getString();
+      return graph.operation(opName).output(output.index());
+    }
+  }
+
+  private final AtomicReference<GraphOperationAttributeInspector> attrs =
+      new AtomicReference<>(null);
+
+  /** Get an inspector for the graph operation's attributes. */
+  public OperationAttributeInspector attributes() {
+    return attrs.updateAndGet(
+        (old) -> old == null ? new GraphOperationAttributeInspector(this) : old);
+  }
+
   /**
-   * Get the op's inputs, not including control inputs.
+   * Get the input list that starts at {@code idx} and has length {@code length}
+   *
+   * @param idx the starting index of the list
+   * @param length the length of the list
+   * @return the input list
+   * @see #inputListLength(String)
    */
+  public Output<?>[] inputList(int idx, int length) {
+    Output<?>[] inputs = new Output<?>[length];
+    for (int i = 0; i < length; ++i) {
+      inputs[i] = input(idx + i);
+    }
+    return inputs;
+  }
+
+  /** Get the op's inputs, not including control inputs. */
   public List<Operand<?>> inputs() {
     try (PointerScope scope = new PointerScope()) {
       int numInputs = numInputs();
@@ -214,7 +263,8 @@ public List<Operand<?>> inputs() {
   }
 
   /**
-   * Get the number of ops that use this op's designated output as an input, not including control dependencies.
+   * Get the number of ops that use this op's designated output as an input, not including control
+   * dependencies.
    *
    * @param index the output to look for usages of
    */
@@ -226,7 +276,8 @@ public int numConsumers(int index) {
   }
 
   /**
-   * Get the ops that use this op's designated output as an input, not including control dependencies.
+   * Get the ops that use this op's designated output as an input, not including control
+   * dependencies.
    *
    * @param index the output to look for usages of
    */
@@ -250,7 +301,8 @@ public Set<GraphOperation> consumers(int index) {
   }
 
   /**
-   * Get the number of ops that use any of this op's outputs as an input, not including control dependencies.
+   * Get the number of ops that use any of this op's outputs as an input, not including control
+   * dependencies.
    */
   public int numConsumers() {
     int all = 0;
@@ -260,7 +312,6 @@ public int numConsumers() {
     return all;
   }
 
-
   /**
    * Get the ops that use any of this op's outputs as an input, not including control dependencies.
    */
@@ -272,18 +323,14 @@ public Set<GraphOperation> consumers() {
     return all;
   }
 
-  /**
-   * Get the number of control inputs for this op.
-   */
+  /** Get the number of control inputs for this op. */
   public int numControlInputs() {
     try (PointerScope scope = new PointerScope()) {
       return TF_OperationNumControlInputs(getUnsafeNativeHandle());
     }
   }
 
-  /**
-   * Get the control inputs of this op.
-   */
+  /** Get the control inputs of this op. */
   public Set<GraphOperation> controlInputs() {
     try (PointerScope scope = new PointerScope()) {
       int numInputs = numControlInputs();
@@ -301,18 +348,14 @@ public Set<GraphOperation> controlInputs() {
     }
   }
 
-  /**
-   * Get the number of ops with this op as a control dependency.
-   */
+  /** Get the number of ops with this op as a control dependency. */
   public int numControlConsumers() {
     try (PointerScope scope = new PointerScope()) {
       return TF_OperationNumControlOutputs(getUnsafeNativeHandle());
     }
   }
 
-  /**
-   * Get the ops with this op as a control dependency.
-   */
+  /** Get the ops with this op as a control dependency. */
   public Set<GraphOperation> controlConsumers() {
     try (PointerScope scope = new PointerScope()) {
       int numConsumers = numControlConsumers();
@@ -330,18 +373,27 @@ public Set<GraphOperation> controlConsumers() {
     }
   }
 
-
   TF_Operation getUnsafeNativeHandle() {
     return unsafeNativeHandle;
   }
 
+  TF_Operation getCheckedNativeHandle() {
+    requireHandle(unsafeNativeHandle);
+    return unsafeNativeHandle;
+  }
+
+  Graph graph() {
+    return graph;
+  }
+
   private final Graph graph;
 
   private final TF_Operation unsafeNativeHandle;
 
   private static void requireHandle(Pointer handle) {
     if (handle == null || handle.isNull()) {
-      throw new IllegalStateException("close() has been called on the Graph this Operation was a part of");
+      throw new IllegalStateException(
+          "close() has been called on the Graph this Operation was a part of");
     }
   }
 
@@ -388,8 +440,12 @@ private static long[] shape(TF_Graph graphHandle, TF_Operation opHandle, int out
 
     int numOutputs = TF_OperationNumOutputs(opHandle);
     if (outputIndex < 0 || outputIndex >= numOutputs) {
-      throw new IndexOutOfBoundsException("invalid output index (" + outputIndex
-          + ") for an operation that has " + numOutputs + " outputs");
+      throw new IndexOutOfBoundsException(
+          "invalid output index ("
+              + outputIndex
+              + ") for an operation that has "
+              + numOutputs
+              + " outputs");
     }
 
     try (PointerScope scope = new PointerScope()) {
@@ -397,7 +453,9 @@ private static long[] shape(TF_Graph graphHandle, TF_Operation opHandle, int out
       TF_Status status = TF_Status.newStatus();
       int numDims = TF_GraphGetTensorNumDims(graphHandle, output, status);
       status.throwExceptionIfNotOK();
-      if (numDims < 0) return null;
+      if (numDims < 0) {
+        return null;
+      }
       long[] dims = new long[numDims];
       TF_GraphGetTensorShape(graphHandle, output, dims, numDims, status);
       status.throwExceptionIfNotOK();
@@ -411,8 +469,12 @@ private static int dtype(TF_Graph graphHandle, TF_Operation opHandle, int output
 
     int numOutputs = TF_OperationNumOutputs(opHandle);
     if (outputIndex < 0 || outputIndex >= numOutputs) {
-        throw new IndexOutOfBoundsException("invalid output index (" + outputIndex
-            + ") for an operation that has " + numOutputs + " outputs");
+      throw new IndexOutOfBoundsException(
+          "invalid output index ("
+              + outputIndex
+              + ") for an operation that has "
+              + numOutputs
+              + " outputs");
     }
 
     try (PointerScope scope = new PointerScope()) {
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationAttributeInspector.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationAttributeInspector.java
new file mode 100644
index 00000000000..4dbfa68cd59
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationAttributeInspector.java
@@ -0,0 +1,367 @@
+/*
+ Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+=======================================================================
+
+*/
+package org.tensorflow;
+
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrBool;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrBoolList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrFloat;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrFloatList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrInt;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrIntList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrMetadata;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrShape;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrShapeList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrString;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrStringList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrTensor;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrTensorList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrType;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrTypeList;
+import static org.tensorflow.internal.c_api.global.tensorflow.TF_OperationGetAttrValueProto;
+
+import com.google.protobuf.InvalidProtocolBufferException;
+import java.nio.charset.StandardCharsets;
+import org.bytedeco.javacpp.BytePointer;
+import org.bytedeco.javacpp.IntPointer;
+import org.bytedeco.javacpp.LongPointer;
+import org.bytedeco.javacpp.PointerPointer;
+import org.bytedeco.javacpp.PointerScope;
+import org.bytedeco.javacpp.SizeTPointer;
+import org.tensorflow.internal.c_api.TF_AttrMetadata;
+import org.tensorflow.internal.c_api.TF_Buffer;
+import org.tensorflow.internal.c_api.TF_Status;
+import org.tensorflow.internal.c_api.TF_Tensor;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.AttributeMetadata;
+import org.tensorflow.proto.framework.AttrValue;
+import org.tensorflow.proto.framework.DataType;
+
+class GraphOperationAttributeInspector implements OperationAttributeInspector {
+  private final GraphOperation op;
+
+  GraphOperationAttributeInspector(GraphOperation op) {
+    this.op = op;
+  }
+
+  @Override
+  public AttributeMetadata getAttrMetadata(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      TF_Status status = TF_Status.newStatus();
+      TF_AttrMetadata r = TF_OperationGetAttrMetadata(op.getCheckedNativeHandle(), name, status);
+      status.throwExceptionIfNotOK();
+      return new AttributeMetadata(r);
+    }
+  }
+
+  @Override
+  public AttrValue getAttrValueProto(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      TF_Buffer buffer = TF_Buffer.newBuffer();
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrValueProto(op.getCheckedNativeHandle(), name, buffer, status);
+      status.throwExceptionIfNotOK();
+      return AttrValue.parseFrom(buffer.dataAsByteBuffer());
+    } catch (InvalidProtocolBufferException e) {
+      throw new IllegalStateException("Invalid protobuf for attribute " + name, e);
+    }
+  }
+
+  @Override
+  public String getAttrString(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long size = getAttrMetadata(name).totalSize;
+      BytePointer result = new BytePointer(size);
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrString(op.getCheckedNativeHandle(), name, result, size, status);
+      status.throwExceptionIfNotOK();
+      return result.getString();
+    }
+  }
+
+  @Override
+  public String[] getAttrStringList(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      AttributeMetadata metadata = getAttrMetadata(name);
+      int listSize = (int) metadata.listSize;
+      long totalSize = metadata.totalSize;
+
+      PointerPointer<BytePointer> values = new PointerPointer<>(listSize);
+      SizeTPointer lengths = new SizeTPointer(listSize);
+      BytePointer storage = new BytePointer(totalSize);
+
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrStringList(
+          op.getCheckedNativeHandle(),
+          new BytePointer(name),
+          values,
+          lengths,
+          listSize,
+          storage,
+          totalSize,
+          status);
+      status.throwExceptionIfNotOK();
+
+      String[] results = new String[listSize];
+
+      for (int i = 0; i < results.length; i++) {
+        int length = (int) lengths.get(i);
+
+        if (length == 0) {
+          results[i] = "";
+          continue;
+        }
+
+        byte[] bytes = new byte[length];
+        BytePointer p = values.get(BytePointer.class, i);
+        p.get(bytes);
+
+        results[i] = new String(bytes, StandardCharsets.UTF_8);
+      }
+
+      return results;
+    }
+  }
+
+  @Override
+  public long getAttrInt(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long[] result = new long[1];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrInt(op.getCheckedNativeHandle(), name, result, status);
+      status.throwExceptionIfNotOK();
+      return result[0];
+    }
+  }
+
+  @Override
+  public long[] getAttrIntList(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long size = getAttrMetadata(name).listSize;
+      long[] result = new long[(int) size];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrIntList(op.getCheckedNativeHandle(), name, result, result.length, status);
+      status.throwExceptionIfNotOK();
+      return result;
+    }
+  }
+
+  @Override
+  public float getAttrFloat(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      float[] result = new float[1];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrFloat(op.getCheckedNativeHandle(), name, result, status);
+      status.throwExceptionIfNotOK();
+      return result[0];
+    }
+  }
+
+  @Override
+  public float[] getAttrFloatList(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long size = getAttrMetadata(name).listSize;
+      float[] result = new float[(int) size];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrFloatList(
+          op.getCheckedNativeHandle(), name, result, result.length, status);
+      status.throwExceptionIfNotOK();
+      return result;
+    }
+  }
+
+  @Override
+  public boolean getAttrBool(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      byte[] result = new byte[1];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrBool(op.getCheckedNativeHandle(), name, result, status);
+      status.throwExceptionIfNotOK();
+      return result[0] == 1;
+    }
+  }
+
+  @Override
+  public boolean[] getAttrBoolList(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long size = getAttrMetadata(name).listSize;
+      byte[] byteResults = new byte[(int) size];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrBoolList(
+          op.getCheckedNativeHandle(), name, byteResults, byteResults.length, status);
+      status.throwExceptionIfNotOK();
+
+      boolean[] results = new boolean[byteResults.length];
+
+      for (int i = 0; i < results.length; i++) {
+        results[i] = byteResults[i] == 1;
+      }
+
+      return results;
+    }
+  }
+
+  @Override
+  public DataType getAttrType(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      int[] result = new int[1];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrType(op.getCheckedNativeHandle(), name, result, status);
+      status.throwExceptionIfNotOK();
+      return DataType.forNumber(result[0]);
+    }
+  }
+
+  @Override
+  public DataType[] getAttrTypeList(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long size = getAttrMetadata(name).listSize;
+      int[] typeInts = new int[(int) size];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrTypeList(
+          op.getCheckedNativeHandle(), name, typeInts, typeInts.length, status);
+      status.throwExceptionIfNotOK();
+
+      DataType[] results = new DataType[typeInts.length];
+
+      for (int i = 0; i < results.length; i++) {
+        results[i] = DataType.forNumber(typeInts[i]);
+      }
+
+      return results;
+    }
+  }
+
+  @Override
+  public Tensor getAttrTensor(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      PointerPointer<TF_Tensor> result = new PointerPointer<>(1);
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrTensor(op.getCheckedNativeHandle(), new BytePointer(name), result, status);
+      status.throwExceptionIfNotOK();
+      return RawTensor.fromHandle(result.get(TF_Tensor.class, 0).withDeallocator());
+    }
+  }
+
+  @Override
+  public Tensor[] getAttrTensorList(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long size = getAttrMetadata(name).listSize;
+      PointerPointer<TF_Tensor> pointers = new PointerPointer<>(size);
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrTensorList(
+          op.getCheckedNativeHandle(), new BytePointer(name), pointers, (int) size, status);
+      status.throwExceptionIfNotOK();
+
+      Tensor[] results = new Tensor[(int) size];
+      for (int i = 0; i < results.length; i++) {
+        results[i] = RawTensor.fromHandle(pointers.get(TF_Tensor.class, i).withDeallocator());
+      }
+
+      return results;
+    }
+  }
+
+  @Override
+  public Shape getAttrShape(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      long size = getAttrMetadata(name).totalSize;
+
+      if (size == -1) {
+        return Shape.unknown();
+      }
+
+      long[] result = new long[(int) size];
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrShape(op.getCheckedNativeHandle(), name, result, result.length, status);
+      status.throwExceptionIfNotOK();
+      return Shape.of(result);
+    }
+  }
+
+  @Override
+  public Shape[] getAttrShapeList(String name) {
+    try (PointerScope scope = new PointerScope()) {
+      AttributeMetadata metadata = getAttrMetadata(name);
+      int listSize = (int) metadata.listSize;
+      int totalSize = (int) metadata.totalSize;
+
+      PointerPointer<LongPointer> dimPointers = new PointerPointer<>(listSize);
+      IntPointer numDims = new IntPointer(listSize);
+      LongPointer storage = new LongPointer(totalSize);
+
+      TF_Status status = TF_Status.newStatus();
+      TF_OperationGetAttrShapeList(
+          op.getCheckedNativeHandle(),
+          new BytePointer(name),
+          dimPointers,
+          numDims,
+          listSize,
+          storage,
+          totalSize,
+          status);
+      status.throwExceptionIfNotOK();
+
+      Shape[] results = new Shape[listSize];
+
+      for (int i = 0; i < results.length; i++) {
+        int length = numDims.get(i);
+
+        if (length == -1) {
+          results[i] = Shape.unknown();
+          continue;
+        }
+
+        long[] shape = new long[length];
+        dimPointers.get(LongPointer.class, i).get(shape);
+        results[i] = Shape.of(shape);
+      }
+
+      return results;
+    }
+  }
+
+  @Override
+  public ConcreteFunction getAttrFunction(String name) {
+    AttrValue proto = getAttrValueProto(name);
+    if (!proto.hasFunc())
+      throw new IllegalArgumentException("Attribute \"" + name + "\" is not a function.");
+    return op.graph().getFunction(proto.getFunc().getName());
+  }
+
+  @Override
+  public ConcreteFunction[] getAttrFunctionList(String name) {
+    AttrValue proto = getAttrValueProto(name);
+    if (!proto.hasList())
+      throw new IllegalArgumentException("Attribute \"" + name + "\" is not a list.");
+
+    AttrValue.ListValue list = proto.getList();
+
+    int size = list.getFuncCount();
+    if (size < 0) {
+      throw new IllegalArgumentException("Attribute \"" + name + "\" is not a list of functions.");
+    } else if (size == 0) {
+      return new ConcreteFunction[0];
+    } else {
+      ConcreteFunction[] functions = new ConcreteFunction[size];
+      for (int i = 0; i < size; i++) {
+        functions[i] = op.graph().getFunction(list.getFunc(i).getName());
+      }
+      return functions;
+    }
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java
index d1040469992..63434a9638b 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java
@@ -377,8 +377,19 @@ public OperationBuilder setAttr(String name, ConcreteFunction[] value) {
     return this;
   }
 
+  @Override
+  public OperationBuilder setAttr(String name, AttrValue value) {
+    Graph.Reference r = graph.ref();
+    try {
+      setAttrValue(unsafeNativeHandle, name, value);
+    } finally {
+      r.close();
+    }
+    return this;
+  }
+
   private TF_OperationDescription unsafeNativeHandle;
-  private Graph graph;
+  private final Graph graph;
   private final Scope scope;
 
   private static void requireHandle(Pointer handle) {
@@ -597,19 +608,24 @@ private static void setAttrFunctionName(
 
   private static void setAttrFunctionList(
       TF_OperationDescription opHandle, String attrName, List<String> functionNames) {
+    AttrValue value =
+        AttrValue.newBuilder()
+            .setList(
+                ListValue.newBuilder()
+                    .addAllFunc(
+                        functionNames.stream()
+                            .map(x -> NameAttrList.newBuilder().setName(x).build())
+                            .collect(Collectors.toList()))
+                    .build())
+            .build();
+    setAttrValue(opHandle, attrName, value);
+  }
+
+  private static void setAttrValue(
+      TF_OperationDescription opHandle, String attrName, AttrValue value) {
     requireHandle(opHandle);
     try (PointerScope scope = new PointerScope()) {
       TF_Status status = TF_Status.newStatus();
-      AttrValue value =
-          AttrValue.newBuilder()
-              .setList(
-                  ListValue.newBuilder()
-                      .addAllFunc(
-                          functionNames.stream()
-                              .map(x -> NameAttrList.newBuilder().setName(x).build())
-                              .collect(Collectors.toList()))
-                      .build())
-              .build();
       byte[] bytes = value.toByteArray();
       TF_SetAttrValueProto(opHandle, attrName, new BytePointer(bytes), bytes.length, status);
       status.throwExceptionIfNotOK();
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationAttributeInspector.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationAttributeInspector.java
new file mode 100644
index 00000000000..77be7c7791f
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationAttributeInspector.java
@@ -0,0 +1,173 @@
+/*
+ Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+=======================================================================
+
+*/
+package org.tensorflow;
+
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.AttributeMetadata;
+import org.tensorflow.proto.framework.AttrValue;
+import org.tensorflow.proto.framework.DataType;
+
+/** Helper type for attribute getters, so we don't clutter the operation classes too much. */
+public interface OperationAttributeInspector {
+
+  /**
+   * Get the metadata of an attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the metadata of the attribute
+   */
+  AttributeMetadata getAttrMetadata(String name);
+
+  /**
+   * Get the value of an attribute of this operation as an {@link AttrValue} proto.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute as an {@link AttrValue} proto
+   */
+  AttrValue getAttrValueProto(String name);
+
+  // TODO get attribute names.  Needs TF 2.7
+
+  /**
+   * Get the value of a string attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  String getAttrString(String name);
+
+  /**
+   * Get the value of a string list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  String[] getAttrStringList(String name);
+
+  /**
+   * Get the value of a int attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  long getAttrInt(String name);
+
+  /**
+   * Get the value of a int list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  long[] getAttrIntList(String name);
+
+  /**
+   * Get the value of a float attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  float getAttrFloat(String name);
+
+  /**
+   * Get the value of a float list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  float[] getAttrFloatList(String name);
+
+  /**
+   * Get the value of a boolean attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  boolean getAttrBool(String name);
+
+  /**
+   * Get the value of a boolean list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  boolean[] getAttrBoolList(String name);
+
+  /**
+   * Get the value of a data type attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  DataType getAttrType(String name);
+
+  /**
+   * Get the value of a data type list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  DataType[] getAttrTypeList(String name);
+
+  /**
+   * Get the value of a tensor attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  Tensor getAttrTensor(String name);
+
+  /**
+   * Get the value of a tensor list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  Tensor[] getAttrTensorList(String name);
+
+  /**
+   * Get the value of a shape attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  Shape getAttrShape(String name);
+
+  /**
+   * Get the value of a shape list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  Shape[] getAttrShapeList(String name);
+
+  /**
+   * Get the value of a function attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  ConcreteFunction getAttrFunction(String name);
+
+  /**
+   * Get the value of a function list attribute of this operation.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute
+   */
+  ConcreteFunction[] getAttrFunctionList(String name);
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java
index 569f37c8f4a..17cad6e1751 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java
@@ -1,21 +1,22 @@
 /* Copyright 2019-2021 The TensorFlow Authors. All Rights Reserved.
 
- Licensed under the Apache License, Version 2.0 (the "License");
- you may not use this file except in compliance with the License.
- You may obtain a copy of the License at
-
-     http://www.apache.org/licenses/LICENSE-2.0
-
- Unless required by applicable law or agreed to in writing, software
- distributed under the License is distributed on an "AS IS" BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
- =======================================================================
- */
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+=======================================================================
+*/
 package org.tensorflow;
 
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.AttrValue;
 import org.tensorflow.proto.framework.DataType;
 
 /**
@@ -244,4 +245,13 @@ public interface OperationBuilder {
    * @return the OperationBuilder instance for chaining.
    */
   OperationBuilder setAttr(String name, ConcreteFunction[] value);
+
+  /**
+   * Set value of an attribute of the operation being built. Does not attach any functions.
+   *
+   * @param name attribute name
+   * @param value attribute value
+   * @return the OperationBuilder instance for chaining.
+   */
+  OperationBuilder setAttr(String name, AttrValue value);
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java
index 6cb3be62eb7..20bf7e89832 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java
@@ -46,7 +46,8 @@
             //                "tensorflow/c/env.h",
             "tensorflow/c/kernels.h",
             "tensorflow/c/ops.h",
-            "tensorflow/c/eager/c_api.h"
+            "tensorflow/c/eager/c_api.h",
+            "tensorflow/c/eager/c_api_experimental.h"
           },
           link = "tensorflow_cc@.2",
           preload = {"iomp5", "mklml", "mklml_intel", "tensorflow_framework@.2"},
@@ -385,6 +386,7 @@ public void map(InfoMap infoMap) {
                     "TF_ShapeInferenceContextDimValueKnown",
                     "TFE_NewTensorHandle(const tensorflow::Tensor&, TF_Status*)",
                     "TF_InitKernel")
-                .skip());
+                .skip())
+        .put(new Info("TFE_CustomDeviceTensorHandle", "TFE_CustomDevice").skip());
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/AttributeMetadata.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/AttributeMetadata.java
new file mode 100644
index 00000000000..29ff5950786
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/AttributeMetadata.java
@@ -0,0 +1,57 @@
+/*
+ Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================
+*/
+package org.tensorflow.op;
+
+import org.tensorflow.internal.c_api.TF_AttrMetadata;
+
+/**
+ * Metadata of an op's attribute.
+ *
+ * @see org.tensorflow.internal.c_api.TF_AttrMetadata
+ */
+public class AttributeMetadata {
+
+  /** Whether this attribute is a list. */
+  public final boolean isList;
+
+  /** The size of the list if this attribute is a list, undefined otherwise. */
+  public final long listSize;
+  /**
+   * The type of this attribute, or the type of the list values if it is a list.
+   *
+   * <p>See {@code tensorflow/c/tf_attrtype.h}.
+   */
+  public final int type;
+
+  /** The total size of this attribute. Exact meaning depends on the type. */
+  public final long totalSize;
+
+  public AttributeMetadata(boolean isList, long listSize, int type, long totalSize) {
+    this.isList = isList;
+    this.listSize = listSize;
+    this.type = type;
+    this.totalSize = totalSize;
+  }
+
+  public AttributeMetadata(TF_AttrMetadata nativeMetadata) {
+    this(
+        nativeMetadata.is_list() == 1,
+        nativeMetadata.list_size(),
+        nativeMetadata.type(),
+        nativeMetadata.total_size());
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/RawOpInputs.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/RawOpInputs.java
new file mode 100644
index 00000000000..d347c2c429b
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/RawOpInputs.java
@@ -0,0 +1,110 @@
+/*
+ Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================
+*/
+package org.tensorflow.op;
+
+import java.util.Collection;
+import java.util.Collections;
+import java.util.LinkedHashMap;
+import java.util.LinkedHashSet;
+import java.util.Map;
+import java.util.Set;
+import org.tensorflow.GraphOperation;
+import org.tensorflow.OperationAttributeInspector;
+import org.tensorflow.proto.framework.AttrValue;
+
+/** A base class for operation input accessors. */
+public abstract class RawOpInputs<T extends RawOp> {
+
+  /** The outputs of this operation. */
+  public T getOutputs() {
+    return outputs;
+  }
+
+  /** Get the names of this op's attributes */
+  public Set<String> attributeNames() {
+    return attributeNames;
+  }
+
+  /**
+   * Get the value of an attribute as an {@link AttrValue} proto. The type-safe accessors should be
+   * preferred when possible.
+   *
+   * @param name the name of the attribute
+   * @return the value of the attribute, as an {@link AttrValue} proto
+   */
+  public AttrValue attributeValue(String name) {
+    return op.attributes().getAttrValueProto(name);
+  }
+
+  /** Get all attribute value protos */
+  public Map<String, AttrValue> attributeValues() {
+    Map<String, AttrValue> values = new LinkedHashMap<>(attributeNames.size());
+    for (String name : attributeNames) {
+      values.put(name, attributeValue(name));
+    }
+    return values;
+  }
+
+  /**
+   * Get the metadata for an attribute
+   *
+   * @param name the name of the attribute
+   * @return the attribute's metadata
+   */
+  public AttributeMetadata attributeMetadata(String name) {
+    return op.attributes().getAttrMetadata(name);
+  }
+
+  /** Get an inspector for the operation's attributes. */
+  public OperationAttributeInspector attributes() {
+    return op.attributes();
+  }
+
+  @Override
+  public final int hashCode() {
+    return op.hashCode();
+  }
+
+  @Override
+  public final boolean equals(Object obj) {
+    if (this == obj) {
+      return true;
+    }
+    // Note: we consider that all objects wrapping the same operation are equal, no matter their
+    // implementation
+    if (!(obj instanceof RawOpInputs)) {
+      return false;
+    }
+    return op.equals(((RawOpInputs) obj).op);
+  }
+
+  @Override
+  public final String toString() {
+    return String.format("Inputs of <%s '%s'>", op.type(), op.name());
+  }
+
+  protected RawOpInputs(T outputs, GraphOperation op, Collection<String> attributeNames) {
+    this.outputs = outputs;
+    this.op = op;
+    this.attributeNames = Collections.unmodifiableSet(new LinkedHashSet<>(attributeNames));
+  }
+
+  // don't expose, this will be converted to a ForwardOperation w/ new gradient support
+  private final GraphOperation op;
+  private final T outputs;
+  private final Set<String> attributeNames;
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationTest.java
index ac9694adabd..f52166aaac3 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationTest.java
@@ -15,6 +15,7 @@
 
 package org.tensorflow;
 
+import static org.junit.jupiter.api.Assertions.assertArrayEquals;
 import static org.junit.jupiter.api.Assertions.assertEquals;
 import static org.junit.jupiter.api.Assertions.assertNotEquals;
 import static org.junit.jupiter.api.Assertions.assertNotNull;
@@ -28,9 +29,14 @@
 import java.util.Set;
 import org.junit.jupiter.api.Test;
 import org.tensorflow.exceptions.TFInvalidArgumentException;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Ops;
+import org.tensorflow.op.core.Barrier;
+import org.tensorflow.op.debugging.DebugIdentity;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
+import org.tensorflow.types.TString;
 
 /** Unit tests for {@link org.tensorflow.GraphOperation}. */
 public class GraphOperationTest {
@@ -56,8 +62,8 @@ public void operationEquality() {
     GraphOperation op1;
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g);
-      op1 = (GraphOperation)tf.withName("op1").constant(1).op();
-      GraphOperation op2 = (GraphOperation)tf.withName("op2").constant(2).op();
+      op1 = (GraphOperation) tf.withName("op1").constant(1).op();
+      GraphOperation op2 = (GraphOperation) tf.withName("op2").constant(2).op();
       GraphOperation op3 = new GraphOperation(g, op1.getUnsafeNativeHandle());
       GraphOperation op4 = g.operation("op1");
       assertEquals(op1, op1);
@@ -81,8 +87,8 @@ public void operationEquality() {
   public void operationCollection() {
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g);
-      GraphOperation op1 = (GraphOperation)tf.withName("op1").constant(1).op();
-      GraphOperation op2 = (GraphOperation)tf.withName("op2").constant(2).op();
+      GraphOperation op1 = (GraphOperation) tf.withName("op1").constant(1).op();
+      GraphOperation op2 = (GraphOperation) tf.withName("op2").constant(2).op();
       GraphOperation op3 = new GraphOperation(g, op1.getUnsafeNativeHandle());
       GraphOperation op4 = g.operation("op1");
       Set<Operation> ops = new HashSet<>();
@@ -149,7 +155,8 @@ public void outputListLength() {
       Ops tf = Ops.create(g);
       assertEquals(1, tf.split(tf.constant(0), tf.array(0, 1), 1L).op().outputListLength("output"));
       assertEquals(2, tf.split(tf.constant(0), tf.array(0, 1), 2L).op().outputListLength("output"));
-      assertEquals(3, tf.split(tf.constant(0), tf.array(0, 1, 2), 3L).op().outputListLength("output"));
+      assertEquals(
+          3, tf.split(tf.constant(0), tf.array(0, 1, 2), 3L).op().outputListLength("output"));
     }
   }
 
@@ -157,7 +164,8 @@ public void outputListLength() {
   public void inputListLength() {
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g);
-      assertEquals(1, tf.split(tf.constant(0), tf.array(0, 1), 1L).op().inputListLength("split_dim"));
+      assertEquals(
+          1, tf.split(tf.constant(0), tf.array(0, 1), 1L).op().inputListLength("split_dim"));
       try {
         tf.split(tf.constant(0), tf.array(0, 1), 2L).op().inputListLength("inputs");
       } catch (TFInvalidArgumentException iae) {
@@ -206,6 +214,8 @@ public void inputs() {
 
       assertEquals(2, op.numInputs());
       assertEquals(Arrays.asList(a.asOutput(), b.asOutput()), op.inputs());
+      assertEquals(a.asOutput(), op.input(0));
+      assertEquals(b.asOutput(), op.input(1));
     }
   }
 
@@ -256,4 +266,36 @@ public void controlConsumers() {
       assertEquals(new LinkedHashSet<>(Collections.singletonList(c.op())), op.controlConsumers());
     }
   }
+
+  @Test
+  public void getAttributes() {
+    try (Graph g = new Graph()) {
+      Ops tf = Ops.create(g);
+
+      Operand<TFloat32> a = tf.array(1f);
+      Operand<TFloat32> c =
+          DebugIdentity.create(
+              tf.scope(),
+              a,
+              DebugIdentity.debugUrls(Arrays.asList("a", "b")),
+              DebugIdentity.outputSlot(0L));
+      Operand<TString> barrier =
+          tf.barrier(
+              Arrays.asList(TInt32.class, TInt32.class),
+              Barrier.shapes(new Shape[] {Shape.of(1, 2), Shape.of(3, 4)}));
+
+      GraphOperation op1 = (GraphOperation) c.op();
+
+      assertEquals(0, op1.attributes().getAttrInt("output_slot"));
+      assertArrayEquals(new String[] {"a", "b"}, op1.attributes().getAttrStringList("debug_urls"));
+
+      GraphOperation op2 = (GraphOperation) barrier.op();
+      assertArrayEquals(
+          new DataType[] {DataType.DT_INT32, DataType.DT_INT32},
+          op2.attributes().getAttrTypeList("component_types"));
+      assertArrayEquals(
+          new Shape[] {Shape.of(1, 2), Shape.of(3, 4)},
+          op2.attributes().getAttrShapeList("shapes"));
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/Names.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/Names.java
index 38987e81cb3..4176f517022 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/Names.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/Names.java
@@ -49,7 +49,9 @@ public class Names {
 
   public static final TypeName Op = ClassName.get(OpPackage, "Op");
   public static final ClassName RawOp = ClassName.get(OpPackage, "RawOp");
+  public static final ClassName RawOpInputs = ClassName.get(OpPackage, "RawOpInputs");
   public static final ClassName Operation = ClassName.get(TensorflowPackage, "Operation");
+  public static final ClassName GraphOperation = ClassName.get(TensorflowPackage, "GraphOperation");
   public static final ClassName Operands = ClassName.get(OpPackage, "Operands");
   public static final ClassName OperationBuilder =
       ClassName.get(TensorflowPackage, "OperationBuilder");
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/AttributeType.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/AttributeType.java
new file mode 100644
index 00000000000..50f8599d043
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/AttributeType.java
@@ -0,0 +1,42 @@
+/*
+ Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================
+*/
+package org.tensorflow.op.generator;
+
+public enum AttributeType {
+  STRING("String"),
+  INT("Int"),
+  FLOAT("Float"),
+  BOOL("Bool"),
+  SHAPE("Shape"),
+  TENSOR("Tensor"),
+  TYPE("Type");
+  // TODO add Func once supported
+
+  private final String methodName;
+
+  private AttributeType(String methodName) {
+    this.methodName = methodName;
+  }
+
+  public String getterName(boolean isList) {
+    if (isList) {
+      return methodName + "List";
+    } else {
+      return methodName;
+    }
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ClassGenerator.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ClassGenerator.java
index 54f153b1988..14d3f31a977 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ClassGenerator.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ClassGenerator.java
@@ -340,6 +340,7 @@ void buildClass() {
       }
 
       buildConstructor();
+      buildInputsClass();
     }
   }
 
@@ -527,7 +528,7 @@ private void buildFactoryMethods() {
       ParameterSpec.Builder param = ParameterSpec.builder(type.iterableIfIterable().javaType, name);
       String description =
           argDef.getDescription().isEmpty()
-              ? String.format("the %s value", name)
+              ? String.format("The %s value", name)
               : argDef.getDescription();
       paramTags.put(name, CodeBlock.of("$L", parseDocumentation(description)));
       factoryBuilder.addParameter(param.build());
@@ -567,7 +568,7 @@ private void buildFactoryMethods() {
 
       String description =
           apiAttr.getDescription().isEmpty()
-              ? String.format("the value of the %s property", javaName)
+              ? String.format("The value of the %s attribute", javaName)
               : apiAttr.getDescription();
       paramTags.put(javaName, CodeBlock.of("$L", parseDocumentation(description)));
 
@@ -778,6 +779,7 @@ private void buildGettersAndSetters() {
                         .returns(ClassName.get(fullPackage, className, "Options"))
                         .addModifiers(Modifier.PUBLIC, Modifier.STATIC)
                         .addCode("return new Options().$L($L);", method.name, argName)
+                        .varargs(method.varargs)
                         .build());
               });
     }
@@ -916,4 +918,117 @@ private void buildConstructor() {
     ctor.addCode(body.build());
     builder.addMethod(ctor.build());
   }
+
+  private void buildInputsClass() {
+    TypeSpec.Builder inputsBuilder =
+        TypeSpec.classBuilder("Inputs").addModifiers(Modifier.PUBLIC, Modifier.STATIC);
+    MethodSpec.Builder ctor = MethodSpec.constructorBuilder().addModifiers(Modifier.PUBLIC);
+    ctor.addParameter(Names.GraphOperation, "op");
+
+    StringJoiner attrNames = new StringJoiner(", ");
+
+    Set<TypeVariableName> typeVars = new LinkedHashSet<>();
+    CodeBlock.Builder fieldInits = CodeBlock.builder();
+
+    fieldInits.addStatement("int inputIndex = 0");
+
+    // add the inputs as parameters, and add them to the op builder
+    for (ArgDef input : op.getInputArgList()) {
+      ResolvedType type = resolver.typeOf(input);
+      String name = getJavaName(input);
+      ApiDef.Arg argDef = argApis.get(input);
+
+      typeVars.addAll(type.findGenerics());
+
+      TypeName javaType = type.iterableIfIterable().javaType;
+
+      String description =
+          argDef.getDescription().isEmpty()
+              ? String.format("The %s input", name)
+              : argDef.getDescription();
+
+      inputsBuilder.addField(
+          FieldSpec.builder(javaType, name, Modifier.PUBLIC, Modifier.FINAL)
+              .addJavadoc("$L", parseDocumentation(description))
+              .build());
+
+      if (type.iterable) {
+        String inputListLength = name + "Length";
+        fieldInits.addStatement(
+            "int $L = op.inputListLength($S)", inputListLength, input.getName());
+        fieldInits.addStatement(
+            "$L = $T.asList(($T) op.inputList(inputIndex, $L))",
+            name,
+            Names.Arrays,
+            ArrayTypeName.of(type.javaType),
+            inputListLength);
+        fieldInits.addStatement("inputIndex += $L", inputListLength);
+      } else {
+        fieldInits.addStatement("$L = ($T) op.input(inputIndex++)", name, javaType);
+      }
+    }
+
+    for (AttrDef attr : op.getAttrList()) {
+      ResolvedType type = resolver.typeOf(attr);
+      String name = getJavaName(attr);
+
+      if (type.attributeType != null) {
+
+        ApiDef.Attr apiAttr = attrApis.get(attr);
+
+        String description =
+            apiAttr.getDescription().isEmpty()
+                ? String.format("The %s attribute", name)
+                : apiAttr.getDescription();
+
+        TypeName javaType = type.jniType;
+        if (type.iterable) {
+          javaType = ArrayTypeName.of(javaType);
+        }
+
+        attrNames.add(CodeBlock.of("$S", attr.getName()).toString());
+        inputsBuilder.addField(
+            FieldSpec.builder(javaType, name, Modifier.PUBLIC, Modifier.FINAL)
+                .addJavadoc("$L", description)
+                .build());
+        fieldInits.addStatement(
+            "$L = op.attributes().getAttr$L($S)",
+            name,
+            type.attributeType.getterName(type.iterable),
+            attr.getName());
+      }
+    }
+
+    List<TypeName> sharedTypeVars = new ArrayList<>();
+    for (TypeVariableName onClass : this.builder.typeVariables) {
+      if (typeVars.contains(onClass)) {
+        sharedTypeVars.add(onClass);
+      } else {
+        sharedTypeVars.add(WildcardTypeName.subtypeOf(TypeName.OBJECT));
+      }
+    }
+
+    TypeName outputClass = ClassName.get(fullPackage, className);
+    if (!this.builder.typeVariables.isEmpty()) {
+      outputClass =
+          ParameterizedTypeName.get(
+              (ClassName) outputClass, sharedTypeVars.toArray(new TypeName[0]));
+    }
+
+    inputsBuilder.superclass(ParameterizedTypeName.get(Names.RawOpInputs, outputClass));
+
+    CodeBlock.Builder body = CodeBlock.builder();
+    body.addStatement(
+        "super(new $L(op), op, $T.asList($L))",
+        this.builder.typeVariables.isEmpty() ? className : className + "<>",
+        Names.Arrays,
+        attrNames.toString());
+
+    body.add(fieldInits.build());
+    ctor.addCode(body.build());
+
+    inputsBuilder.addMethod(ctor.build());
+    inputsBuilder.addTypeVariables(typeVars);
+    this.builder.addType(inputsBuilder.build());
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ResolvedType.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ResolvedType.java
index 65d4547e263..b14e3de0aba 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ResolvedType.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/ResolvedType.java
@@ -22,14 +22,13 @@
 import com.squareup.javapoet.TypeName;
 import com.squareup.javapoet.TypeVariableName;
 import com.squareup.javapoet.WildcardTypeName;
-import org.tensorflow.Names;
-
 import java.util.Collections;
 import java.util.LinkedHashSet;
 import java.util.List;
 import java.util.Objects;
 import java.util.Set;
 import java.util.StringJoiner;
+import org.tensorflow.Names;
 
 /** Holds type information for inputs, outputs, or attributes, and provides utilities. */
 final class ResolvedType {
@@ -40,6 +39,9 @@ final class ResolvedType {
   /** The type for jni/attribute setting use. */
   final TypeName jniType;
 
+  /** The type of the attribute, for accessors, if supported. */
+  final AttributeType attributeType;
+
   /**
    * Whether this type should be made iterable when used.
    *
@@ -47,7 +49,7 @@ final class ResolvedType {
    */
   final boolean iterable;
 
-  ResolvedType(TypeName javaType, TypeName jniType, boolean iterable) {
+  ResolvedType(TypeName javaType, TypeName jniType, AttributeType attributeType, boolean iterable) {
     if (javaType == null) {
       throw new NullPointerException("Can't create with a null javaType");
     }
@@ -58,50 +60,51 @@ final class ResolvedType {
     this.javaType = javaType;
     this.jniType = jniType;
     this.iterable = iterable;
+    this.attributeType = attributeType;
+  }
+
+  ResolvedType(TypeName javaType, TypeName jniType, boolean iterable) {
+    this(javaType, jniType, null, iterable);
+  }
+
+  ResolvedType(TypeName javaType, TypeName jniType, AttributeType attributeType) {
+    this(javaType, jniType, attributeType, false);
   }
 
   ResolvedType(TypeName javaType, TypeName jniType) {
-    this(javaType, jniType, false);
+    this(javaType, jniType, null, false);
   }
 
-  ResolvedType(TypeName type, boolean iterable) {
+  ResolvedType(TypeName type, AttributeType attributeType, boolean iterable) {
     if (type == null) {
       throw new NullPointerException("Can't create with a null type");
     }
 
     if (type.isPrimitive()) {
       this.javaType = type.box();
-      jniType = type;
     } else {
       this.javaType = type;
-      this.jniType = type;
     }
+    jniType = type;
     this.iterable = iterable;
+    this.attributeType = attributeType;
   }
 
-  ResolvedType(TypeName type) {
-    this(type, false);
-  }
-
-  ResolvedType(Class<?> javaType, Class<?> jniType, boolean iterable) {
-    this(TypeName.get(javaType), TypeName.get(jniType), iterable);
-  }
-
-  ResolvedType(Class<?> javaType, Class<?> jniType) {
-    this(TypeName.get(javaType), TypeName.get(jniType), false);
+  ResolvedType(TypeName type, boolean iterable) {
+    this(type, (AttributeType) null, iterable);
   }
 
-  ResolvedType(Class<?> type, boolean iterable) {
-    this(TypeName.get(type), iterable);
+  ResolvedType(TypeName type, AttributeType attributeType) {
+    this(type, attributeType, false);
   }
 
-  ResolvedType(Class<?> type) {
+  ResolvedType(TypeName type) {
     this(type, false);
   }
 
   /** Returns a copy of this type with the specified {@code iterable} value. */
   ResolvedType withIterable(boolean iterable) {
-    return new ResolvedType(javaType, jniType, iterable);
+    return new ResolvedType(javaType, jniType, attributeType, iterable);
   }
 
   /** Get the unboxed version of {@code javaType} if it is a boxed primitive. */
@@ -121,7 +124,7 @@ ResolvedType arrayIfIterable() {
     } else {
       newJType = javaType;
     }
-    return new ResolvedType(newJType, jniType, iterable);
+    return new ResolvedType(newJType, jniType, attributeType, iterable);
   }
 
   /** Return a copy, wrapping {@code javaType} in {@link Iterable} if this type is iterable. */
@@ -132,7 +135,7 @@ ResolvedType iterableIfIterable() {
     } else {
       newJType = javaType;
     }
-    return new ResolvedType(newJType, jniType, iterable);
+    return new ResolvedType(newJType, jniType, attributeType, iterable);
   }
 
   /** Return a copy, wrapping {@code javaType} in {@link List} if this type is iterable. */
@@ -143,7 +146,7 @@ ResolvedType listIfIterable() {
     } else {
       newJType = javaType;
     }
-    return new ResolvedType(newJType, jniType, iterable);
+    return new ResolvedType(newJType, jniType, attributeType, iterable);
   }
 
   /** True if wrapping will be done by {@link #classIfGeneric()} */
@@ -162,7 +165,7 @@ ResolvedType classIfGeneric() {
     } else {
       newJType = javaType;
     }
-    return new ResolvedType(newJType, jniType, iterable);
+    return new ResolvedType(newJType, jniType, attributeType, iterable);
   }
 
   /** Recursively get all type variable names in {@code javaType}. */
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/TypeResolver.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/TypeResolver.java
index f24813598ce..9887c71d498 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/TypeResolver.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/op/generator/TypeResolver.java
@@ -21,6 +21,11 @@
 import com.squareup.javapoet.TypeName;
 import com.squareup.javapoet.TypeVariableName;
 import com.squareup.javapoet.WildcardTypeName;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
 import org.tensorflow.Names;
 import org.tensorflow.proto.framework.AttrValue;
 import org.tensorflow.proto.framework.DataType;
@@ -28,12 +33,6 @@
 import org.tensorflow.proto.framework.OpDef.ArgDef;
 import org.tensorflow.proto.framework.OpDef.AttrDef;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.HashSet;
-import java.util.Map;
-import java.util.Set;
-
 /**
  * A utility class to handle type calculations for a {@link ClassGenerator}. Should be one to one
  * with {@link ClassGenerator} instances.
@@ -77,6 +76,7 @@ final class TypeResolver {
    * <p>These are excluded from factory methods.
    */
   private final Set<String> reachedFromInput = new HashSet<>();
+
   private char nextGenericLetter = 'T';
 
   TypeResolver(OpDef op) {
@@ -225,30 +225,31 @@ private ResolvedType typeOf(AttrDef attr, boolean fromInput) {
 
     switch (typeName) {
       case "string":
-        types = new ResolvedType(STRING);
+        types = new ResolvedType(STRING, AttributeType.STRING);
         break;
       case "int":
-        types = new ResolvedType(TypeName.LONG);
+        types = new ResolvedType(TypeName.LONG, AttributeType.INT);
         break;
       case "float":
-        types = new ResolvedType(TypeName.FLOAT);
+        types = new ResolvedType(TypeName.FLOAT, AttributeType.FLOAT);
         break;
       case "bool":
-        types = new ResolvedType(TypeName.BOOLEAN);
+        types = new ResolvedType(TypeName.BOOLEAN, AttributeType.BOOL);
         break;
       case "shape":
-        types = new ResolvedType(Names.Shape);
+        types = new ResolvedType(Names.Shape, AttributeType.SHAPE);
         break;
       case "tensor":
-        types = new ResolvedType(Names.Tensor);
+        types = new ResolvedType(Names.Tensor, AttributeType.TENSOR);
         break;
       case "type":
         TypeName family = typeFamily(attr);
         TypeName type =
             iterable ? WildcardTypeName.subtypeOf(family) : nextGeneric().withBounds(family);
-        types = new ResolvedType(type, TypeName.get(DataType.class));
+        types = new ResolvedType(type, TypeName.get(DataType.class), AttributeType.TYPE);
         break;
       case "func":
+        // TODO add attribute type once supported
         types = new ResolvedType(Names.ConcreteFunction);
         break;
       default: