Generate op input and attribute accessors

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
    */

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

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
    */

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) {