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Fix generation regression
Signed-off-by: Ryan Nett <[email protected]>
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tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java

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@@ -1853,7 +1853,6 @@ public <T extends TNumber> Selu<T> selu(Operand<T> features) {
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*
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* <p>
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*
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* @param scope The TensorFlow scope
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* @param labels the labels
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* @param logits the logits of type float32 or float64
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* @param <T> the type of labels and logits
@@ -1915,7 +1914,6 @@ public <T extends TNumber> Softmax<T> softmax(Operand<T> logits) {
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* disallow backpropagation into <code>labels</code>, pass label tensors through <code>
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* tf.stopGradient</code> before feeding it to this function.
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*
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* @param scope current scope
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* @param labels Each vector along the class dimension should hold a valid probability
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* distribution e.g. for the case in which labels are of shape <code>[batch_size, num_classes]
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* </code>, each row of <code>labels[i]</code> must be a valid probability distribution.
@@ -2143,7 +2141,6 @@ public <T extends TType> SpaceToDepth<T> spaceToDepth(Operand<T> input, Long blo
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* , or <code>TFloat64</code>, and <code>labels</code> must have the dtype of <code>TInt32</code>
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* or <code>TInt64</code>.
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*
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* @param scope current scope
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* @param labels <code>Tensor</code> of shape <code>[d_0, d_1, ..., d_{r-1}]</code> (where <code>r
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* </code> is rank of <code>labels</code> and result) and the dataType is <code>TInt32</code>
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* or <code>TInt64</code>. Each entry in <code>labels</code> must be an index in <code>[0,

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