From ef0ce67a2e79628380729cf16fb0cd4d99cbe6a3 Mon Sep 17 00:00:00 2001 From: Jim Clarke Date: Tue, 28 Jul 2020 16:26:34 -0400 Subject: [PATCH 01/33] Initial checkin of Keras Optimzers and helper classes. Fixed dependencies in pom.xml --- tensorflow-keras/pom.xml | 140 ++- .../java/org/tensorflow/keras/backend/K.java | 713 +++++++++++ .../keras/backend/tf/ConfusionMatrix.java | 193 +++ .../keras/backend/tf/ControlDependencies.java | 84 ++ .../org/tensorflow/keras/backend/tf/NN.java | 134 +++ .../keras/backend/tf/SparseTensor.java | 64 + .../tensorflow/keras/backend/tf/Tuple.java | 109 ++ .../keras/backend/tf/WeightsBroadcastOps.java | 158 +++ .../tensorflow/keras/optimizer/AdaDelta.java | 202 ++++ .../tensorflow/keras/optimizer/AdaGrad.java | 167 +++ .../tensorflow/keras/optimizer/AdaGradDA.java | 191 +++ .../org/tensorflow/keras/optimizer/Adam.java | 182 +++ .../tensorflow/keras/optimizer/Adamax.java | 283 +++++ .../org/tensorflow/keras/optimizer/Ftrl.java | 360 ++++++ .../org/tensorflow/keras/optimizer/Nadam.java | 402 +++++++ .../keras/optimizer/OptimizerInterface.java | 59 + .../keras/optimizer/Optimizers.java | 124 ++ .../tensorflow/keras/optimizer/RMSProp.java | 201 ++++ .../org/tensorflow/keras/optimizer/SGD.java | 199 +++ .../java/org/tensorflow/keras/utils/ND.java | 717 +++++++++++ .../keras/utils/PlaceholderStringFormat.java | 81 ++ .../tensorflow/keras/utils/PrintUtils.java | 152 +++ .../tensorflow/keras/utils/ProgressBar.java | 311 +++++ .../tensorflow/keras/utils/ShapeUtils.java | 110 ++ .../org/tensorflow/keras/utils/SmartCond.java | 107 ++ .../tensorflow/keras/utils/SymbolicShape.java | 92 ++ .../keras/utils/SymbolicShapeDict.java | 58 + .../org/tensorflow/keras/utils/TypeUtils.java | 98 ++ .../keras/optimizers/AdaDeltaTest.java | 226 ++++ .../keras/optimizers/AdaGradDATest.java | 126 ++ .../keras/optimizers/AdaGradTest.java | 170 +++ .../tensorflow/keras/optimizers/AdamTest.java | 263 ++++ .../keras/optimizers/AdamaxTest.java | 242 ++++ .../tensorflow/keras/optimizers/FtrlTest.java | 352 ++++++ .../keras/optimizers/NadamTest.java | 286 +++++ .../keras/optimizers/RMSPropTest.java | 307 +++++ .../tensorflow/keras/optimizers/SGDTest.java | 227 ++++ .../keras/utils/EagerTestSession.java | 747 ++++++++++++ .../keras/utils/GraphTestSession.java | 1066 +++++++++++++++++ .../tensorflow/keras/utils/SmartCondTest.java | 247 ++++ .../tensorflow/keras/utils/TestSession.java | 618 ++++++++++ .../tensorflow/keras/utils/TypeUtilTest.java | 234 ++++ 42 files changed, 10760 insertions(+), 42 deletions(-) create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaDelta.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGrad.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGradDA.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adam.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adamax.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Ftrl.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Nadam.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/OptimizerInterface.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Optimizers.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/RMSProp.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/SGD.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ND.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java create mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/utils/GraphTestSession.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TestSession.java create mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java diff --git a/tensorflow-keras/pom.xml b/tensorflow-keras/pom.xml index 4dd41d6a36b..c314b53bcc0 100644 --- a/tensorflow-keras/pom.xml +++ b/tensorflow-keras/pom.xml @@ -14,53 +14,109 @@ limitations under the License. ======================================================================= --> - + - 4.0.0 + 4.0.0 - - org.tensorflow - tensorflow-java - 0.2.0-SNAPSHOT - - tensorflow-keras - jar + + org.tensorflow + tensorflow-java + 0.2.0-SNAPSHOT + + tensorflow-keras + jar - TensorFlow Keras Library - Java implementation of the TensorFlow Keras API + TensorFlow Keras Library + + + + Java implementation of the TensorFlow Keras API - - - org.junit.jupiter - junit-jupiter-api - test - - - org.junit.jupiter - junit-jupiter-engine - test - - + + + org.tensorflow + tensorflow-core-api + ${project.version} + + + org.tensorflow + tensorflow-core-generator + ${project.version} + + + org.tensorflow + tensorflow-framework + ${project.version} + + + org.tensorflow + ndarray + ${project.version} + + + + com.google.protobuf + protobuf-java + 3.11.4 + - - - - org.apache.maven.plugins - maven-surefire-plugin - 2.22.2 - - 1 - false - -Xmx2G -XX:MaxPermSize=256m - false - - **/*Test.java - - - - - + + org.json + json + 20190722 + + + + org.apache.commons + commons-csv + 1.8 + + + + org.tensorflow + tensorflow-core-platform + ${project.version} + + + org.junit.jupiter + junit-jupiter-api + test + + + org.junit.jupiter + junit-jupiter-engine + test + + + + + org.tensorflow + tensorflow-core-platform${javacpp.platform.extension} + ${project.version} + test + + + + + + + org.apache.maven.plugins + maven-surefire-plugin + 2.22.2 + + 1 + false + -Xmx2G -XX:MaxPermSize=256m + false + + **/*Test.java + + + + + diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java new file mode 100644 index 00000000000..51a5fdaa5ff --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java @@ -0,0 +1,713 @@ +/* Copyright 2020 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.keras.backend; + +import java.util.Arrays; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.function.Function; +import org.tensorflow.DataType; +import org.tensorflow.EagerSession; +import org.tensorflow.ExecutionEnvironment; +import org.tensorflow.Graph; +import org.tensorflow.Operand; +import org.tensorflow.Session; +import org.tensorflow.Tensor; +import org.tensorflow.keras.backend.tf.ConfusionMatrix; +import org.tensorflow.keras.backend.tf.NN; +import org.tensorflow.keras.backend.tf.Tuple; +import org.tensorflow.ndarray.NdArraySequence; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.ReduceSum; +import org.tensorflow.op.core.Squeeze; +import org.tensorflow.op.core.Variable; +import org.tensorflow.op.math.Mean; +import org.tensorflow.op.nn.SoftmaxCrossEntropyWithLogits; +import org.tensorflow.types.TBfloat16; +import org.tensorflow.types.TBool; +import org.tensorflow.types.TFloat16; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TFloat64; +import org.tensorflow.types.TInt32; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.TUint8; +import org.tensorflow.types.family.TNumber; +import org.tensorflow.types.family.TType; + +/** Keras backend methods */ +public class K { + + public static final double Epsilon = 1e-7; + public static final float EpsilonF = 1e-7F; + + public static final double epsilon() { + return Epsilon; + } + + public static final Operand epsilonConstant(Ops tf) { + return tf.constant(Epsilon); + } + + public static final Operand epsilonConstant(Ops tf, DataType dtype) { + return tf.dtypes.cast(tf.constant(Epsilon), dtype); + } + + public static final Operand one(Ops tf) { + return tf.constant(1); + } + + public static final Operand one(Ops tf, DataType dtype) { + return tf.dtypes.cast(tf.constant(1), dtype); + } + + public static final Operand minusOne(Ops tf) { + return tf.constant(-1); + } + + public static final Operand minusOne(Ops tf, DataType dtype) { + return tf.dtypes.cast(tf.constant(-1), dtype); + } + + public static final Operand zero(Ops tf) { + return tf.constant(0); + } + + public static final Operand zero(Ops tf, DataType dtype) { + return tf.dtypes.cast(tf.constant(0), dtype); + } + + public static final Operand constant(Ops tf, double number, DataType dtype) { + return tf.dtypes.cast(tf.constant(number), dtype); + } + + public static Operand clip(Ops tf, Operand x, double minValue, double maxValue) { + assert x != null : "Operand x must not be null"; + DataType dtype = x.asOutput().dataType(); + if (maxValue < minValue) { + double tmp = maxValue; + maxValue = minValue; + minValue = tmp; + } + Operand minValueConstant = tf.dtypes.cast(tf.constant(minValue), dtype); + Operand maxValueConstant = tf.dtypes.cast(tf.constant(maxValue), dtype); + return tf.clipByValue(x, minValueConstant, maxValueConstant); + } + + public static Operand mean(Ops tf, Operand x) { + return mean(tf, x, null, false); + } + + public static Operand mean(Ops tf, Operand x, Operand axis) { + return mean(tf, x, axis, false); + } + + public static Operand mean(Ops tf, Operand x, boolean keepDims) { + return mean(tf, x, null, keepDims); + } + + public static Operand mean(Ops tf, Operand x, Operand axis, boolean keepDims) { + if (x.asOutput().dataType() == TBool.DTYPE) { + x = tf.dtypes.cast(x, TFloat32.DTYPE); + } + if (axis == null) { + axis = allAxis(tf, x); + } + return tf.math.mean(x, axis, Mean.keepDims(keepDims)); + } + + // alias for mean + public static Operand reduceMean(Ops tf, Operand x, Operand axis, boolean keepDims) { + return mean(tf, x, axis, keepDims); + } + + public static Operand maximum(Ops tf, Operand x, Operand y) { + y = tf.dtypes.cast(y, x.asOutput().dataType()); + return tf.math.maximum(x, y); + } + + public static Operand sqrt(Ops tf, Operand x) { + DataType dType = x.asOutput().dataType(); + Operand zero = tf.dtypes.cast(tf.constant(0), dType); + Operand inf = tf.dtypes.cast(tf.constant(Float.POSITIVE_INFINITY), dType); + x = tf.clipByValue(x, zero, inf); + return tf.math.sqrt(x); + } + + public static Shape merge(Shape a, Shape b) { + assert a.numDimensions() == b.numDimensions() + : String.format("Shapes %s and %s are incompatible", a, b); + long[] array = new long[a.numDimensions()]; + for (int i = 0; i < a.numDimensions(); i++) { + if (a.size(i) != Shape.UNKNOWN_SIZE) { + if (b.size(i) != Shape.UNKNOWN_SIZE) { + assert a.size(i) == b.size(i) : String.format("Shapes %s and %s are incompatible", a, b); + } + array[i] = a.size(i); + } else { + array[i] = b.size(i); + } + } + return Shape.of(array); + } + + // this is from nn in Python, I could not find it in the Java frameworks. + public static Operand sigmoidCrossEntropyWithLogits(Ops tf, Operand labels, Operand logits) { + Shape lablesShape = labels.asOutput().shape(); + Shape logitsShape = logits.asOutput().shape(); + Shape newShape = merge(lablesShape, logitsShape); + + Operand zeros = tf.dtypes.cast(tf.zerosLike(logits), logits.asOutput().dataType()); + Operand cond = tf.math.greaterEqual(logits, zeros); + + Operand relu_logits = tf.select(cond, logits, zeros); + Operand neg_abs_logits = tf.select(cond, tf.math.neg(logits), logits); + return tf.math.add( + tf.math.sub(relu_logits, tf.math.mul(logits, labels)), + tf.math.log1p(tf.math.exp(neg_abs_logits))); + } + + // TODO need to walk back identity until it hits something else + // not sure how to get the input nodes for the Operand. + private static Operand backtrackIdentity(Operand output) { + // while(!output.op().type().equals("Identity")) + // output = output.op().output(0); + return output; + } + + public static Operand binary_crossentropy( + Ops tf, Operand target, Operand output, boolean fromLogits) { + if (fromLogits) { + return sigmoidCrossEntropyWithLogits(tf, target, output); + } + + if (!(output instanceof Variable) && (!tf.scope().env().isEager())) { + // output = backtrackIdentity(output); // TODO - this does not work, goes infinite loop + if (output.op().type().equals("Sigmoid")) { + assert output.op().numOutputs() == 1; + output = output.op().output(0); + return sigmoidCrossEntropyWithLogits(tf, target, output); + } + } + DataType dtype = output.asOutput().dataType(); + Operand one = one(tf, dtype); + Operand epsilonConst = K.epsilonConstant(tf, dtype); + Operand oneMinusEpsilonConst = tf.math.sub(one, epsilonConst); + output = tf.clipByValue(output, epsilonConst, oneMinusEpsilonConst); + + // Compute cross entropy from probabilities. + Operand bce = tf.math.mul(target, tf.math.log(tf.math.add(output, epsilonConst))); + bce = + tf.math.add( + bce, + tf.math.mul( + tf.math.sub(one, target), + tf.math.log(tf.math.add(tf.math.sub(one, output), epsilonConst)))); + Operand result = tf.math.neg(bce); + return result; + } + + public static Operand categorical_crossentropy( + Ops tf, Operand target, Operand output, boolean fromLogits) { + return categorical_crossentropy(tf, target, output, fromLogits, -1); + } + + public static Operand categorical_crossentropy( + Ops tf, Operand target, Operand output, boolean fromLogits, int axis) { + + if (fromLogits) { + return softmax_cross_entropy_with_logits(tf, target, output); + } + if (!(output instanceof Variable) && (!tf.scope().env().isEager())) { + // TODO output = backtrackIdentity(output); doesn't seem to work with Java version. + if (output.op().type().equals("Softmax")) { + assert output.op().numOutputs() == 1; + output = output.op().output(0); + Operand op = softmax_cross_entropy_with_logits(tf, target, output); + return op; + } + } + DataType dtype = output.asOutput().dataType(); + Operand one = one(tf, dtype); + Operand epsilonConst = K.epsilonConstant(tf, dtype); + Operand oneMinusepsilonConst = tf.math.sub(one, epsilonConst); + output = + tf.math.div( + output, tf.reduceSum(output, tf.constant(axis), ReduceSum.keepDims(Boolean.TRUE))); + output = tf.clipByValue(output, epsilonConst, oneMinusepsilonConst); + + // Compute cross entropy from probabilities. + Operand cce = + tf.reduceSum( + tf.math.mul(target, tf.math.log(output)), + tf.constant(axis), + ReduceSum.keepDims(Boolean.FALSE)); + return tf.math.neg(cce); + } + + public static Operand flatten(Ops tf, Operand t) { + Shape shape = Shape.of(1L); + return tf.reshape(t, tf.constant(shape)); + } + + public static Operand sparse_categorical_crossentropy( + Ops tf, Operand target, Operand output, boolean fromLogits, int axis) { + DataType dType = output.asOutput().dataType(); + if (!(output instanceof Variable) && (!tf.scope().env().isEager())) { + // TODO output = backtrackIdentity(output); doesn't seem to work with Java version. + if (output.op().type().equals("Softmax")) { + // assert output.op().numOutputs() == 1; + // When softmax activation function is used for output operation, we + // use logits from the softmax function directly to compute loss in order + // to prevent collapsing zero when training. + // TODO assert len(output.op.inputs) == 1 + // TODO output = output.op.inputs[0] + fromLogits = true; + } + } + if (!fromLogits) { + Operand epsilonConst = epsilonConstant(tf, dType); + Operand one = one(tf, dType); + Operand oneMinusEpsilonConst = tf.math.sub(one, epsilonConst); + output = tf.clipByValue(output, epsilonConst, oneMinusEpsilonConst); + output = tf.math.log(output); + } + Shape outputShape = output.asOutput().shape(); + int outputRank = outputShape.numDimensions(); + axis %= outputRank; + if (axis < 0) { + axis += outputRank; + } + if (axis != outputRank - 1) { + int[] axisNew = moveAxisToEnd(axis, outputRank); + output = tf.linalg.transpose(output, tf.constant(axisNew)); + } + + target = tf.dtypes.cast(target, TInt64.DTYPE); + // TODO Try to adjust the shape so that rank of labels = rank of logits - 1. + outputShape = output.asOutput().shape(); + Shape targetShape = target.asOutput().shape(); + int targetRank = targetShape.numDimensions(); + + boolean updateShape = targetRank != outputRank - 1; + if (updateShape) { // TODO check to see if this is right + target = tf.reshape(target, tf.constant(-1L)); // flatten + output = + tf.reshape( + output, + tf.constant(new long[] {-1L, outputShape.size(outputShape.numDimensions() - 1)})); + } + + // call nn.nn.sparse_softmax_cross_entropy_with_logits_v2 + Operand loss = NN.sparse_softmax_cross_entropy_with_logits(tf, target, output); + if (updateShape && outputRank >= 3) { + long[] dims = outputShape.asArray(); + long[] newDims = new long[dims.length - 1]; + System.arraycopy(dims, 0, newDims, 0, newDims.length); + loss = tf.reshape(loss, tf.constant(newDims)); + } + return loss; + } + + private static int[] allAxis(Operand op) { + int rank = op.asOutput().shape().numDimensions(); + int[] ranks = new int[rank]; + for (int i = 0; i < rank; i++) { + ranks[i] = i; + } + return ranks; + } + + public static Operand allAxis(Ops tf, Operand op) { + int[] ranks = allAxis(op); + return tf.constant(ranks); + } + + // TODO shouldn't these be in tensorflow itself under nn? + private static Operand moveDimToEnd( + Ops tf, Operand tensor, int dim_index, Operand rank) { + Operand one = one(tf, TInt32.DTYPE); + List> concatList = + Arrays.asList( + tf.range(tf.constant(dim_index), one, one), + tf.range(tf.constant(dim_index + 1), rank, one)); + return tf.linalg.transpose( + tensor, + (Operand) tf.concat((Iterable>) concatList, (Operand) tf.constant(0))); + } + + private static Operand flattenOuterDims( + Ops tf, Operand logits) { + Operand zero = zero(tf, TInt64.DTYPE); + Operand one = one(tf, TInt64.DTYPE); + Operand minusOne = tf.constant(-1); + + // Shape logitsShape = logits.asOutput().shape(); + // long lastDimSize = logitsShape.size(logitsShape.numDimensions()-1); + // if(!tf.scope().env().isEager()) { + Shape shape = logits.asOutput().shape(); + int ndims = shape.numDimensions(); + if (!shape.hasUnknownDimension()) { + long product = 1L; + boolean productValid = true; + for (int i = ndims - 2; i >= 0; i--) { + long d = shape.size(i); + if (d == Shape.UNKNOWN_SIZE) { + productValid = false; + break; + } + product *= d; + } + if (productValid) { + Shape outputShape = Shape.of(product, shape.size(ndims - 1)); + return tf.reshape(logits, tf.constant(outputShape.asArray())); + } + } + // } + + Operand rank = tf.dtypes.cast(tf.rank(logits), TInt64.DTYPE); + Operand rankMinusOne = tf.math.sub(rank, one); + + Operand last_dim_size = tf.slice(tf.shape(logits), rankMinusOne, tf.constant(1)); + Operand concat = + tf.concat(Arrays.asList(tf.constant(new int[] {-1}), last_dim_size), tf.constant(0)); + return tf.reshape(zero, concat); + } + + private static int[] moveAxisToEnd(int axis, int outputRank) { + int[] axisNew = new int[outputRank]; + for (int i = 0; i < axis; i++) { + axisNew[i] = i; + } + for (int i = axis + 1; i < outputRank; i++) { + axisNew[i - 1] = i; + } + axisNew[outputRank - 1] = axis; + return axisNew; + } + + // TODO, maybe part of Shape ?? + private static boolean shapeIsCompatible(Shape a, Shape b) { + if (a.numDimensions() != b.numDimensions()) { + return false; + } + for (int i = 0; i < a.numDimensions(); i++) { + long aSize = a.size(i); + long bSize = b.size(i); + if (aSize != Shape.UNKNOWN_SIZE && bSize != Shape.UNKNOWN_SIZE && aSize != bSize) { + return false; + } + } + return true; + } + + // TODO these are "nn" ops + public static Operand softmax_cross_entropy_with_logits(Ops tf, Operand labels, Operand logits) { + return softmax_cross_entropy_with_logits(tf, labels, logits, -1); + } + + public static Operand softmax_cross_entropy_with_logits( + Ops tf, Operand labels, Operand logits, int axis) { + axis = axis % logits.asOutput().shape().numDimensions(); + if (axis < 0) { + axis += logits.asOutput().shape().numDimensions(); + } + + Operand minusOne = tf.constant(-1); + Operand precise_logits = logits; + Operand one = tf.constant(1L); + + boolean convertToFloat32 = + logits.asOutput().dataType() == TFloat16.DTYPE + || logits.asOutput().dataType() == TBfloat16.DTYPE; + if (convertToFloat32) { + precise_logits = tf.dtypes.cast(logits, TFloat32.DTYPE); + } + DataType dtype = precise_logits.asOutput().dataType(); + labels = tf.dtypes.cast(labels, dtype); + Operand inputRank = tf.dtypes.cast(tf.rank(precise_logits), TInt64.DTYPE); + Operand inputRankMinusOne = tf.dtypes.cast(tf.math.sub(inputRank, one), TInt64.DTYPE); + Shape shape = logits.asOutput().shape(); + + // Move the dim to the end if dim is not the last dimension. + if (axis != -1 && axis != precise_logits.asOutput().shape().numDimensions() - 1) { + precise_logits = moveDimToEnd(tf, precise_logits, axis, inputRank); + labels = moveDimToEnd(tf, labels, axis, inputRank); + } + + Shape inputShape = precise_logits.asOutput().shape(); + precise_logits = flattenOuterDims(tf, precise_logits); + labels = flattenOuterDims(tf, labels); + SoftmaxCrossEntropyWithLogits smax = + tf.nn.softmaxCrossEntropyWithLogits(precise_logits, labels); + Operand cost = smax.loss(); + Operand outputShape = + tf.slice( + tf.constant(inputShape.asArray()), + tf.constant(new long[] {0}), + tf.constant(new long[] {inputShape.numDimensions() - 1})); + cost = tf.reshape(cost, outputShape); + if (tf.scope().env().isGraph() && !shape.hasUnknownDimension()) { + long[] array = shape.asArray(); + long[] newArray = new long[array.length - 1]; + if (axis < 0) { + axis = shape.numDimensions() + axis; + } + for (int i = 0; i < axis; i++) { + newArray[i] = shape.size(i); + } + for (int i = axis + 1; i < shape.numDimensions(); i++) { + newArray[i - 1] = shape.size(i); + } + Shape newShape = Shape.of(newArray); + cost = tf.reshape(cost, tf.constant(newShape.asArray())); + } + + if (convertToFloat32) { + cost = tf.dtypes.cast(cost, logits.asOutput().dataType()); + } + return cost; + } + + public static Operand map( + Operand input, Function, Operand> mapFunc) { + return null; + } + + public static long[] concatenate(long first, long... remaining) { + long[] dims = new long[remaining.length + 1]; + System.arraycopy(remaining, 0, dims, 1, remaining.length); + dims[0] = first; + return dims; + } + + private static Map> uidMap = new HashMap<>(); + + /** + * Associates a string prefix with an integer counter in a TensorFlow graph. + * + *

Example: + * + * 

+   * get_uid('dense')
+   * 1
+   * get_uid('dense')
+   * 2
+   *
+ * + * @param tf the TensorFlow Ops + * @param prefix String prefix to index. + * @return Unique integer ID. + */ + public static int getUid(Ops tf, String prefix) { + ExecutionEnvironment env = tf.scope().env(); + Map uids = uidMap.get(env); + if (uids == null) { + uids = new HashMap<>(); + uidMap.put(env, uids); + } + Integer id = uids.get(prefix); + if (id == null) { + id = 0; + } else { + id++; + } + + uids.put(prefix, id); + return id; + } + + /** + * returns the larger DataType between the two. + * + * @param a the first DataType to compare + * @param b the second DataType to compare + * @return the wider DataType + */ + public DataType wider(DataType a, DataType b) { + return a.byteSize() < b.byteSize() ? b : a; + } + + /** + * returns the smaller DataType between the two. + * + * @param a the first DataType to compare + * @param b the second DataType to compare + * @return the smaller DataType + */ + public DataType narrower(DataType a, DataType b) { + return a.byteSize() > b.byteSize() ? b : a; + } + + public NdArraySequence getTensorValue(Ops tf, Operand operand) { + DataType dtype = operand.asOutput().dataType(); + if (tf.scope().env().isGraph()) { + try (Session session = new Session((Graph) tf.scope().env())) { + if (dtype.equals(TInt32.DTYPE)) { + try (Tensor result = + session.runner().fetch(operand).run().get(0).expect(TInt32.DTYPE)) { + return result.data().scalars(); + } + } else if (dtype.equals(TInt64.DTYPE)) { + try (Tensor result = + session.runner().fetch(operand).run().get(0).expect(TInt64.DTYPE)) { + return result.data().scalars(); + } + } else if (dtype.equals(TUint8.DTYPE)) { + try (Tensor result = + session.runner().fetch(operand).run().get(0).expect(TUint8.DTYPE)) { + return result.data().scalars(); + } + } else if (dtype.equals(TBfloat16.DTYPE)) { + try (Tensor result = + session.runner().fetch(operand).run().get(0).expect(TBfloat16.DTYPE)) { + return result.data().scalars(); + } + } else if (dtype.equals(TFloat16.DTYPE)) { + try (Tensor result = + session.runner().fetch(operand).run().get(0).expect(TFloat16.DTYPE)) { + return result.data().scalars(); + } + } else if (dtype.equals(TFloat32.DTYPE)) { + try (Tensor result = + session.runner().fetch(operand).run().get(0).expect(TFloat32.DTYPE)) { + return result.data().scalars(); + } + } else if (dtype.equals(TFloat64.DTYPE)) { + try (Tensor result = + session.runner().fetch(operand).run().get(0).expect(TFloat64.DTYPE)) { + return result.data().scalars(); + } + } else { + return null; + } + } + } else { + try (EagerSession session = EagerSession.create()) { + if (dtype.equals(TInt32.DTYPE)) { + return ((Operand) operand).data().scalars(); + } else if (dtype.equals(TInt64.DTYPE)) { + return ((Operand) operand).data().scalars(); + } else if (dtype.equals(TUint8.DTYPE)) { + return ((Operand) operand).data().scalars(); + } else if (dtype.equals(TBfloat16.DTYPE)) { + return ((Operand) operand).data().scalars(); + } else if (dtype.equals(TFloat16.DTYPE)) { + return ((Operand) operand).data().scalars(); + } else if (dtype.equals(TFloat32.DTYPE)) { + return ((Operand) operand).data().scalars(); + } else if (dtype.equals(TFloat64.DTYPE)) { + return ((Operand) operand).data().scalars(); + } else { + return null; + } + } + } + } + + /** + * Squeeze or expand last dimension if needed. 1. Squeezes last dim of `y_pred` or `y_true` if + * their rank differs by 1 (using `confusion_matrix.remove_squeezable_dimensions`). 2. Squeezes or + * expands last dim of `sample_weight` if its rank differs by 1 from the new rank of `y_pred`. If + * `sample_weight` is scalar, it is kept scalar. + * + * @param tf the TensorVlow Ops + * @param yPred Predicted values, a `Tensor` of arbitrary dimensions. + * @param yTrue Optional label `Tensor` whose dimensions match `y_pred`. + * @return Tuple of `y_pred`, `y_true` and `sample_weight`. Each of them possibly has the last + * dimension squeezed, `sample_weight` could be extended by one dimension. If `sample_weight` + * is null, (y_pred, y_true) is returned. + */ + public static Tuple squeezeOrExpandDimensions(Ops tf, Operand yTrue, Operand yPred) { + return squeezeOrExpandDimensions(tf, yTrue, yPred, null); + } + + /** + * Squeeze or expand last dimension if needed. 1. Squeezes last dim of `y_pred` or `y_true` if + * their rank differs by 1 (using `confusion_matrix.remove_squeezable_dimensions`). 2. Squeezes or + * expands last dim of `sample_weight` if its rank differs by 1 from the new rank of `y_pred`. If + * `sample_weight` is scalar, it is kept scalar. + * + * @param tf the TensorVlow Ops + * @param yPred Predicted values, a `Tensor` of arbitrary dimensions. + * @param yTrue Optional label `Tensor` whose dimensions match `y_pred`. + * @param sampleWeight Optional weight scalar or `Tensor` whose dimensions match `y_pred`. + * @return Tuple of `y_pred`, `y_true` and `sample_weight`. Each of them possibly has the last + * dimension squeezed, `sample_weight` could be extended by one dimension. If `sample_weight` + * is null, (y_pred, y_true) is returned. + */ + public static Tuple squeezeOrExpandDimensions( + Ops tf, Operand yTrue, Operand yPred, Operand sampleWeight) { + Tuple tuple = new Tuple(yTrue, yPred); + Shape ypredShape = yPred.asOutput().shape(); + long ypredRank = ypredShape.numDimensions(); + + if (yTrue != null) { + Shape ytrueShape = yTrue.asOutput().shape(); + long ytrueRank = ytrueShape.numDimensions(); + if (ytrueRank != Shape.UNKNOWN_SIZE && ypredRank != Shape.UNKNOWN_SIZE) { + // Use static rank for `y_true` and `y_pred`. + if (ypredRank - ytrueRank != 1 || ypredShape.size(-1) == 1) { + // y_true, y_pred = confusion_matrix.remove_squeezable_dimensions(y_true, y_pred) + tuple = ConfusionMatrix.removeSqueezableDimensions(tf, yTrue, yPred); + } + } else { // use dynamic rank + tuple = ConfusionMatrix.removeSqueezableDimensions(tf, yTrue, yPred); + } + } + if (sampleWeight == null) { + return tuple; + } + Shape weightsShape = sampleWeight.asOutput().shape(); + long weightsRank = weightsShape.numDimensions(); + if (weightsRank == 0) { // scalar + return new Tuple(yTrue, yPred, sampleWeight); + } + + if (ypredRank != Shape.UNKNOWN_SIZE && weightsRank != Shape.UNKNOWN_SIZE) { + + if (weightsRank - ypredRank == 1) { + sampleWeight = tf.squeeze(sampleWeight); + } else if (ypredRank - weightsRank == 1) { + sampleWeight = tf.expandDims(sampleWeight, tf.constant(-1L)); + } + return new Tuple(yTrue, yPred, sampleWeight); + } + // Use dynamic rank. + Operand weightsRankTensor = tf.rank(sampleWeight); + Operand rankDiff = tf.math.sub(weightsRankTensor, tf.rank(yPred)); + sampleWeight = + tf.select( + tf.math.equal(weightsRankTensor, tf.constant(0)), + sampleWeight, + maybeAdjustWeights(tf, sampleWeight, rankDiff)); + return new Tuple(yTrue, yPred, sampleWeight); + } + + private static Operand maybeAdjustWeights(Ops tf, Operand sampleWeight, Operand rankDiff) { + return tf.select( + tf.math.equal(rankDiff, tf.constant(1)), + tf.squeeze(sampleWeight, Squeeze.axis(Arrays.asList(-1L))), + maybeExpandWeights(tf, sampleWeight, rankDiff)); + } + + private static Operand maybeExpandWeights(Ops tf, Operand sampleWeight, Operand rankDiff) { + return tf.select( + tf.math.equal(rankDiff, tf.constant(-1)), + tf.expandDims(sampleWeight, tf.constant(-1)), + sampleWeight); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java new file mode 100644 index 00000000000..2860adb9d8b --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java @@ -0,0 +1,193 @@ +/* Copyright 2020 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.keras.backend.tf; + +import org.tensorflow.keras.backend.*; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; +import org.tensorflow.DataType; +import org.tensorflow.Operand; +import org.tensorflow.keras.utils.ShapeUtils; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Squeeze; +import org.tensorflow.op.core.Stack; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.family.TNumber; +import org.tensorflow.types.family.TType; + +/** ConfusionMatrix operations */ +public class ConfusionMatrix { + + /** + * Squeeze last dim if ranks differ from expected by exactly 1. + * + * @param tf the TensorFlowOps + * @param labels Label values, a `Tensor` whose dimensions match `predictions`. + * @param predictions Predicted values, a `Tensor` of arbitrary dimensions. + * @return `labels` and `predictions`, possibly with last dim squeezed. + */ + public static Tuple removeSqueezableDimensions(Ops tf, Operand labels, Operand predictions) { + return removeSqueezableDimensions(tf, labels, predictions, 0); + } + + /** + * Squeeze last dim if ranks differ from expected by exactly 1. + * + * @param tf the TensorFlowOps + * @param labels Label values, a `Tensor` whose dimensions match `predictions`. + * @param predictions Predicted values, a `Tensor` of arbitrary dimensions. + * @param expectedRankDiff Expected result of `rank(predictions) - rank(labels)`. + * @return `labels` and `predictions`, possibly with last dim squeezed. + */ + public static Tuple removeSqueezableDimensions( + Ops tf, Operand labels, Operand predictions, int expectedRankDiff) { + + tf = tf.withSubScope("removeSqueezableDimensions"); + Shape predictionsShape = predictions.asOutput().shape(); + int predictionsRank = predictionsShape.numDimensions(); + Shape labelsShape = labels.asOutput().shape(); + int labelsRank = labelsShape.numDimensions(); + + if (predictionsRank != Shape.UNKNOWN_SIZE && labelsRank != Shape.UNKNOWN_SIZE) { + // Use static rank. + int rankDiff = predictionsRank - labelsRank; + if (rankDiff == expectedRankDiff + 1 + && ShapeUtils.isCompatible(predictionsShape.size(-1), 1)) { + predictions = tf.squeeze(predictions); + } else if (rankDiff == expectedRankDiff - 1 + && ShapeUtils.isCompatible(labelsShape.size(-1), 1)) { + labels = tf.squeeze(labels); + } + return new Tuple(labels, predictions); + } + // Use dynamic rank. + Operand rankDiff = tf.math.sub(tf.rank(predictions), tf.rank(labels)); + if (predictionsRank == Shape.UNKNOWN_SIZE + && ShapeUtils.isCompatible(predictionsShape.size(-1), 1)) { + /** + * TODO, if we ever get a select that does lazy evaluation, but for now do the tf.squeeze + * predictions = tf.select( tf.math.equal(tf.constant(expectedRankDiff+1),rankDiff ), + * tf.squeeze(predictions, Squeeze.axis(Arrays.asList(-1L))), predictions ); * + */ + predictions = tf.squeeze(predictions, Squeeze.axis(Arrays.asList(-1L))); + } + if (labelsRank == Shape.UNKNOWN_SIZE && ShapeUtils.isCompatible(labelsShape.size(-1), 1)) { + /** + * TODO, if we ever get a select that does lazy evaluation labels = tf.select( + * tf.math.equal(tf.constant(expectedRankDiff+1),rankDiff ), tf.squeeze(labels, + * Squeeze.axis(Arrays.asList(-1L))), predictions ); * + */ + labels = tf.squeeze(labels, Squeeze.axis(Arrays.asList(-1L))); + } + return new Tuple(labels, predictions); + } + + /** + * Computes the confusion matrix from predictions and labels. + * + * @param tf the TensorFlow Ops + * @param labels 1-D `Tensor` of real labels for the classification task. + * @param predictions 1-D `Tensor` of predictions for a given classification. + * @param numClasses The possible number of labels the classification task can have. + * @param weights optional weights to be applied to the confusion matris + * @param dtype Data type of the confusion matrix. + * @param the type of Operands + * @param the data type. + * @return A `Tensor` of type `dtype` with shape `[n, n]` representing the confusion matrix, where + * `n` is the number of possible labels in the classification task. + * @throws IllegalArgumentException If both predictions and labels are not 1-D vectors and have + * mismatched shapes, or if `weights` is not `None` and its shape doesn't match `predictions`. + */ + public static Operand confusionMatrix( + Ops tf, + Operand labels, + Operand predictions, + Operand numClasses, + Operand weights, + DataType dtype) { + tf = tf.withSubScope("confusion_matrix"); + Tuple ops = K.squeezeOrExpandDimensions(tf, predictions, labels, null); + predictions = tf.dtypes.cast(ops.getPredictions(), TInt64.DTYPE); + labels = tf.dtypes.cast(ops.getLabels(), TInt64.DTYPE); + + List labelControls = new ArrayList<>(); + List predictionControls = new ArrayList<>(); + + labelControls.add( + tf.assertThat( + tf.reduceAny( + tf.math.greaterEqual((Operand) labels, tf.constant(0L)), + K.allAxis(tf, labels)), + Arrays.asList(tf.constant("`labels` contains negative values")))); + + predictionControls.add( + tf.assertThat( + tf.reduceAny( + tf.math.greaterEqual((Operand) predictions, tf.constant(0L)), + K.allAxis(tf, labels)), + Arrays.asList(tf.constant("`predictions` contains negative values")))); + if (numClasses == null) { + numClasses = + tf.math.maximum( + tf.reduceMax(predictions, K.allAxis(tf, predictions)), + tf.reduceMax(labels, K.allAxis(tf, labels))); + } else { + labelControls.add( + tf.assertThat( + tf.reduceAny( + tf.math.less((Operand) labels, numClasses), K.allAxis(tf, labels)), + Arrays.asList(tf.constant("``labels` out of bound")))); + predictionControls.add( + tf.assertThat( + tf.reduceAny( + tf.math.less((Operand) predictions, numClasses), + K.allAxis(tf, predictions)), + Arrays.asList(tf.constant("``predictions` out of bound")))); + } + + if (weights != null) { + if (!ShapeUtils.isCompatibleWith( + predictions.asOutput().shape(), weights.asOutput().shape())) { + throw new IllegalArgumentException( + String.format( + "Prediction shape %s is not compatible with weights shaope %s", + predictions.asOutput().shape(), weights.asOutput().shape())); + } + } + final Operand labelsFinal = labels; + labels = + ControlDependencies.addControlDependencies( + tf, tfc -> tfc.identity(labelsFinal), "confusionMatrix", labelControls); + final Operand predictionsFinal = predictions; + predictions = + ControlDependencies.addControlDependencies( + tf, tfc -> tfc.identity(predictionsFinal), "confusionMatrix", labelControls); + + Operand shape = tf.stack(Arrays.asList(numClasses, numClasses)); + Operand indices = tf.stack(Arrays.asList(labels, predictions), Stack.axis(1L)); + Operand values = + weights == null + ? tf.dtypes.cast(tf.onesLike(predictions), dtype) + : tf.dtypes.cast(weights, dtype); + SparseTensor cmSparse = new SparseTensor(indices, values, shape); + Operand zeroMatrix = tf.zeros(shape, dtype); + + return tf.sparse.sparseTensorDenseAdd( + cmSparse.getIndices(), cmSparse.getValues(), cmSparse.getDenseShape(), zeroMatrix); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java new file mode 100644 index 00000000000..5b323a79ea9 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java @@ -0,0 +1,84 @@ +/* Copyright 2020 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.keras.backend.tf; + +import org.tensorflow.keras.backend.*; +import java.util.Arrays; +import java.util.List; +import java.util.function.Function; +import org.tensorflow.Operand; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.types.family.TType; + +/** Container for ControlDepencies, so that the primary Operand is remembered. */ +public class ControlDependencies { + + /** + * Create a control dependency for the operand; + * + * @param tf the TensorFlow Ops + * @param createOperand a function that creates an operand with the control dependency context + * @param name the scope name to use + * @param dependencies a list of control ops. + * @param the type of Operand + * @return the Operand with control dependency scope + */ + public static Operand addControlDependencies( + Ops tf, Function> createOperand, String name, Op... dependencies) { + return addControlDependencies(tf, createOperand, name, Arrays.asList(dependencies)); + } + + /** + * Create a control dependency for an operand. + * + * @param tf the TensorFlow Ops + * @param createOperand function that creates an operand with the control dependency context + * @param name the scope name to use + * @param dependencies a list of control ops. + * @param the type of Operand + * @return the Operand with control dependency scope + */ + public static Operand addControlDependencies( + Ops tf, Function> createOperand, String name, List dependencies) { + tf = tf.withSubScope(name).withControlDependencies(dependencies); + return createOperand.apply(tf); + } + + /** + * Create a control dependency as a NoOp + * + * @param tf the TensorFlow Ops + * @param name the scope name to use + * @param dependencies a list of control ops. + * @return NoOp with control dependency scope + */ + public static Op addControlDependencies(Ops tf, String name, Op... dependencies) { + return addControlDependencies(tf, name, Arrays.asList(dependencies)); + } + + /** + * Create a control dependency as a NoOp + * + * @param tf the TensorFlow Ops + * @param name the scope name to use + * @param dependencies a list of control ops. + * @return NoOp with control dependency scope + */ + public static Op addControlDependencies(Ops tf, String name, List dependencies) { + tf = tf.withSubScope(name).withControlDependencies(dependencies); + return tf.noOp(); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java new file mode 100644 index 00000000000..e49fed5ba95 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java @@ -0,0 +1,134 @@ +/* Copyright 2020 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.keras.backend.tf; + +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; +import org.tensorflow.Operand; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.nn.SparseSoftmaxCrossEntropyWithLogits; +import org.tensorflow.types.TBfloat16; +import org.tensorflow.types.TFloat16; +import org.tensorflow.types.TFloat32; + +/** NN Operations */ +public class NN { + + /** + * Computes sparse softmax cross entropy between `logits` and `labels`. + * + * @param tf + * @param labels `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of `labels` and + * result) and dtype `int32` or `int64`. Each entry in `labels` must be an index in `[0, + * num_classes)`. Other values will raise an exception when this op is run on CPU, and return + * `NaN` for corresponding loss and gradient rows on GPU. + * @param logits Per-label activations (typically a linear output) of shape `[d_0, d_1, ..., + * d_{r-1}, num_classes]` and dtype `float16`, `float32`, or `float64`. These activation + * energies are interpreted as unnormalized log probabilities. + * @return A `Tensor` of the same shape as `labels` and of the same type as `logits` with the + * softmax cross entropy loss. + */ + public static Operand sparse_softmax_cross_entropy_with_logits( + Ops tf, Operand labels, Operand logits) { + // assert shapeIsCompatible(labels.asOutput().shape(), logits.asOutput().shape()): + // String.format("Shapes %s and %s are incompatible", + // labels.asOutput().shape(), logits.asOutput().shape()); + tf = tf.withSubScope("SparseSoftmaxCrossEntropyWithLogits"); + Operand precise_logits = logits; + boolean convertToFloat32 = + logits.asOutput().dataType() == TFloat16.DTYPE + || logits.asOutput().dataType() == TBfloat16.DTYPE; + if (convertToFloat32) { + precise_logits = tf.dtypes.cast(logits, TFloat32.DTYPE); + } + Shape labelsStaticShape = labels.asOutput().shape(); + org.tensorflow.op.core.Shape labelsShape = tf.shape(labels); + Shape logitsShape = logits.asOutput().shape(); + Operand labels_shape = tf.shape(labels); + Shape logitsShortened = logitsShape.take(logitsShape.numDimensions() - 1); + + boolean staticShapesFullyDefined = + !labelsStaticShape.hasUnknownDimension() && !logitsShortened.hasUnknownDimension(); + if (logitsShape.numDimensions() == 0) { + throw new IllegalArgumentException( + String.format("Logits cannot be scalars - received shape %s.", logitsShape)); + } + if (!logitsShape.hasUnknownDimension() + && !labelsStaticShape.hasUnknownDimension() + && labelsStaticShape.numDimensions() != logitsShape.numDimensions() - 1) { + throw new IllegalArgumentException( + String.format( + "Rank mismatch: Rank of labels (received %s) should equal rank of logits minus 1 (received %s).", + labelsStaticShape.toString(), logitsShape.toString())); + } + + if (staticShapesFullyDefined && !labelsStaticShape.equals(logitsShortened)) { + throw new IllegalArgumentException( + String.format( + "Shape mismatch: The shape of labels (received %s) " + + "should equal the shape of logits except for the last " + + "dimension (received %s).", + labelsStaticShape.toString(), logitsShape.toString())); + } + // Check if no reshapes are required. + if (logitsShape.numDimensions() == 2) { + SparseSoftmaxCrossEntropyWithLogits smax = + tf.nn.sparseSoftmaxCrossEntropyWithLogits(precise_logits, labels); + Operand loss = smax.loss(); + if (logits.asOutput().dataType() == TFloat16.DTYPE) { + loss = tf.dtypes.cast(loss, TFloat16.DTYPE); + } + return loss; + } + + List shapeChecks = new ArrayList<>(); + + if (!staticShapesFullyDefined) { + shapeChecks.add( + tf.assertThat( + tf.math.equal(tf.shape(labels), tf.shape.take(tf.shape(logits), tf.constant(-1))), + Arrays.asList( + tf.constant( + "Shape mismatch: The shape of labels " + + "should equal the shape of logits except for the last " + + "dimension ")))); + } + + // Reshape logits to 2 dim, labels to 1 dim. + long numClassses = logitsShape.size(logitsShape.numDimensions() - 1); + + precise_logits = tf.reshape(precise_logits, tf.constant(new long[] {-1, numClassses})); + labels = tf.reshape(labels, tf.constant(-1)); + SparseSoftmaxCrossEntropyWithLogits smax = + tf.nn.sparseSoftmaxCrossEntropyWithLogits(precise_logits, labels); + + return ControlDependencies.addControlDependencies( + tf, + tfc -> { + Operand cost = smax.loss(); + + cost = tfc.reshape(cost, labels_shape); + if (logits.asOutput().dataType() == TFloat16.DTYPE) { + cost = tfc.dtypes.cast(cost, TFloat16.DTYPE); + } + return cost; + }, + "sparse_softmax_cross_entropy_with_logits", + shapeChecks); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java new file mode 100644 index 00000000000..45d9ec5b071 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java @@ -0,0 +1,64 @@ +/* Copyright 2020 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.keras.backend.tf; + +import org.tensorflow.Operand; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.family.TType; + +/** + * Represents a sparse tensor. + * + * @param the type of the SparseTensor + */ +public class SparseTensor { + + private final Operand indices; + private final Operand values; + private final Operand denseShape; + + /** + * Create a SparseTensor + * + * @param indices A 2-D int64 tensor of shape `[N, ndims]`, which specifies the indices of the + * elements in the sparse tensor that contain nonzero values + * @param values A 1-D tensor of any type and shape `[N]`, which supplies the values for each + * element in `indices`. + * @param denseShape A 1-D int64 tensor of shape `[ndims]`, which specifies the dense_shape of the + * sparse tensor + * @throws IllegalArgumentException When building an eager SparseTensor if `dense_shape` is + * unknown or contains unknown elements (None or -1). + */ + public SparseTensor(Operand indices, Operand values, Operand denseShape) { + this.indices = indices; + this.values = values; + this.denseShape = denseShape; + } + + /** @return the indices */ + public Operand getIndices() { + return indices; + } + + /** @return the values */ + public Operand getValues() { + return values; + } + + /** @return the denseShape */ + public Operand getDenseShape() { + return denseShape; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java new file mode 100644 index 00000000000..9f2f11285b4 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java @@ -0,0 +1,109 @@ +/* Copyright 2020 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.keras.backend.tf; + +import org.tensorflow.Operand; +import org.tensorflow.types.family.TType; + +/** + * Returns labels, losses or predictions and sample weights as a Tuple + * + * @param the type of Operand + */ +public class Tuple { + + private final Operand labels; + private final Operand lossesOrPredictions; + private final Operand sampleWeights; + + /** + * Creates a Tuple of Operands for labels, predictions, and sampleWeights + * + * @param labels the labels + * @param lossesOrPredictions the losses or predictions + */ + public Tuple(Operand labels, Operand lossesOrPredictions) { + this(labels, lossesOrPredictions, null); + } + + /** + * Creates a Tuple of Operands for labels, predictions, and sampleWeights + * + * @param labels the labels + * @param lossesOrPredictions the losses or predictions + * @param sampleWeights the sample weights + */ + public Tuple(Operand labels, Operand lossesOrPredictions, Operand sampleWeights) { + this.labels = labels; + this.lossesOrPredictions = lossesOrPredictions; + this.sampleWeights = sampleWeights; + } + + /** + * Indicates whether this Tuple contains Labels + * + * @return true is this Tuple contains Labels + */ + public boolean containsLabels() { + return this.labels != null; + } + + /** + * Indicates whether this Tuple contains Labels + * + * @return true is this Tuple contains Labels + */ + public boolean containsPredictions() { + return this.lossesOrPredictions != null; + } + + /** + * Indicates whether this Tuple contains Labels + * + * @return true is this Tuple contains Labels + */ + public boolean containsLosses() { + return this.lossesOrPredictions != null; + } + + /** + * Indicates whether this Tuple contains Labels + * + * @return true is this Tuple contains Labels + */ + public boolean containsSampleWeights() { + return this.sampleWeights != null; + } + + /** @return the labels */ + public Operand getLabels() { + return labels; + } + + /** @return the predictions */ + public Operand getPredictions() { + return lossesOrPredictions; + } + + /** @return the predictions */ + public Operand getLosses() { + return lossesOrPredictions; + } + + /** @return the sampleWeights */ + public Operand getSampleWeights() { + return sampleWeights; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java new file mode 100644 index 00000000000..391436ff8bd --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java @@ -0,0 +1,158 @@ +/* Copyright 2020 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.keras.backend.tf; + +import java.util.Arrays; +import java.util.List; +import org.tensorflow.Operand; +import org.tensorflow.keras.utils.ShapeUtils; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.types.TBool; +import org.tensorflow.types.family.TNumber; +import org.tensorflow.types.family.TType; + + +/** Weights Broadcast Ops */ +public class WeightsBroadcastOps { + + private static final String ASSERT_BROADCASTABLE_ERROR_PREFIX = + "weights can not be broadcast to values."; + + /** + * Asserts `weights` can be broadcast to `values` + * + * @param + * @param tf the TensorFlow Ops + * @param weights `Tensor` of weights. + * @param values `Tensor` of values to which weights are applied. + * @return `Operation` raising `InvalidArgumentError` if `weights` has incorrect shape. `no_op` if + * static checks determine `weights` has correct shape. + * @param the type of Operand + * @throws IllegalArgumentException If static checks determine `weights` has incorrect shape. + */ + public static Op assertBroadcastable( + Ops tf, Operand weights, Operand values) { + Operand weightsShape = tf.shape(weights); + Operand weightsRank = tf.rank(weights); + Shape weightsShapeStatic = weights.asOutput().shape(); + int weightsRankStatic = weightsShapeStatic.numDimensions(); + + Operand valuesShape = tf.shape(values); + Operand valuesRank = tf.rank(values); + Shape valuesShapeStatic = values.asOutput().shape(); + int valuesRankStatic = valuesShapeStatic.numDimensions(); + + if (weightsRankStatic != -1 && valuesRankStatic != -1) { + if (weightsRankStatic == 0) { + return ControlDependencies.addControlDependencies(tf, "static_scalar_check_success"); + } + if (weightsRankStatic != valuesRankStatic) { + throw new IllegalArgumentException( + String.format( + "", + "%s values.rank=%d. weights.rank=%d. values.shape=%s. weights.shape=%s.", + ASSERT_BROADCASTABLE_ERROR_PREFIX, + valuesRankStatic, + weightsRankStatic, + valuesShapeStatic.toString(), + weightsShapeStatic.toString())); + } + + for (int i = 0; i < valuesRankStatic; i++) { + if (valuesShapeStatic.size(i) != weightsShapeStatic.size(i)) { + throw new IllegalArgumentException( + String.format( + "", + "%s Mismatch at dim %s. values.shape=%s weights.shape=%s.", + ASSERT_BROADCASTABLE_ERROR_PREFIX, + i, + valuesShapeStatic.toString(), + weightsShapeStatic.toString())); + } + } + return ControlDependencies.addControlDependencies(tf, "static_dims_check_success"); + } + // Dynamic checks. + Operand is_scalar = tf.math.equal(weightsRank, tf.constant(0)); + List> data = + Arrays.asList( + tf.constant(ASSERT_BROADCASTABLE_ERROR_PREFIX), + tf.constant("weights.shape="), + weightsShape, + tf.constant("values.shape="), + valuesShape, + tf.constant("is_scalar="), + is_scalar); + + Operand isValidShape = + tf.select( + is_scalar, + is_scalar, + hasValidNonscalarShape(tf, weightsRank, weightsShape, valuesRank, valuesShape)); + + return tf.assertThat(isValidShape, data); + } + + private static Operand hasValidNonscalarShape( + Ops tf, + Operand weightsRank, + Operand weightsShape, + Operand valuesRank, + Operand valuesShape) { + tf = tf.withSubScope("has_valid_nonscalar_shape"); + Operand isSameRank = tf.math.equal(valuesRank, weightsRank); + return tf.select(isSameRank, hasValidDims(tf, weightsShape, valuesShape), isSameRank); + } + + private static Operand hasValidDims( + Ops tf, Operand weightsShape, Operand valuesShape) { + tf = tf.withSubScope("has_invalid_dims"); + Operand diff = tf.reduceSum(tf.math.sub(weightsShape, valuesShape), tf.constant(0)); + return tf.math.equal(tf.constant(0), diff); + } + + /** + * Broadcast `weights` to the same shape as `values`. + * + * @param tf the TensorFlow ops + * @param weights `Tensor` whose shape is broadcastable to `values` + * @param values Tensor` of any shape + * @param the type of Operand + * @return `weights` broadcast to `values` shape + */ + public static Operand broadcastWeights( + Ops tf, Operand weights, Operand values) { + tf = tf.withSubScope("broadcast_weights"); + values = tf.dtypes.cast(values, weights.asOutput().dataType()); + + Shape weightsShape = weights.asOutput().shape(); + Shape valuesShape = values.asOutput().shape(); + + if (!weightsShape.hasUnknownDimension() + && !valuesShape.hasUnknownDimension() + && ShapeUtils.isCompatibleWith(weightsShape, valuesShape)) { + return weights; + } + + weights = tf.math.mul(weights, tf.onesLike(values)); + Op dependencies = assertBroadcastable(tf, weights, values); + final Operand weightsFinal = weights; + return ControlDependencies.addControlDependencies( + tf, tfc -> tfc.identity(weightsFinal), "assertBroadcastable", dependencies); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaDelta.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaDelta.java new file mode 100644 index 00000000000..f02d2664759 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaDelta.java @@ -0,0 +1,202 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Optional; +import org.tensorflow.keras.backend.tf.ControlDependencies; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; + +/** + * AdaDelta Optimizer that implements the AdaDelta algorithm. Keras wrapper around the Tensorflow + * Framework optimizer. Adadelta optimization is a stochastic gradient descent method that is based + * on adaptive learning rate per dimension to address two drawbacks: 1) the continual decay of + * learning rates throughout training 2) the need for a manually selected global learning rate + * + *

Two accumulation steps are required: 1) the accumulation of gradients squared, 2) the + * accumulation of updates squared. + * + * @param The Type for the call operation + */ +public class AdaDelta extends org.tensorflow.framework.optimizers.AdaDelta + implements OptimizerInterface { + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String RHO_RATE_KEY = "rho"; + public static final String EPSILON_KEY = "epsilon"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; + public static final float RHO_DEFAULT = 0.95F; + public static final float EPSILON_DEFAULT = 1e-7F; + + private Map config = new HashMap<>(); + private float learningRate; + + private List initializers = new ArrayList<>(); + + + /** + * Create an Adadelta optimizer with default name="Adadelta", learning_rate=0.001F, rho=0.95F, and + * epsilon=1e-7F + * + * @param tf the tensorflow Ops + */ + public AdaDelta(Ops tf) { + this(tf, LEARNING_RATE_DEFAULT, RHO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adadelta optimizer with default learning_rate=0.001F, rho=0.95F, and epsilon=1e-7F + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adadelta" + */ + public AdaDelta(Ops tf, String name) { + this(tf, LEARNING_RATE_DEFAULT, RHO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adadelta optimizer with default name="Adadelta", rho=0.95F, and epsilon=1e-7F + * + * @param tf the tensorflow Ops + * @param learningRate The learning rate + */ + public AdaDelta(Ops tf, float learningRate) { + this(tf, learningRate, RHO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adadelta optimizer with default rho=0.95F, and epsilon=1e-7F + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adadelta" + * @param learningRate The learning rate + */ + public AdaDelta(Ops tf, String name, float learningRate) { + this(tf, learningRate, RHO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adadelta optimizer with default name="Adadelta", + * + * @param tf the tensorflow Ops + * @param learningRate The learning rate + * @param rho The decay rate. + * @param epsilon A constant epsilon used to better conditioning the grad update. + */ + public AdaDelta(Ops tf, float learningRate, float rho, float epsilon) { + super(assertGraph(tf), learningRate, rho, epsilon); + initConfig(learningRate, rho, epsilon); + } + + /** + * Create an Adadelta optimizer + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adadelta" + * @param learningRate The learning rate + * @param rho The decay rate. + * @param epsilon A constant epsilon used to better conditioning the grad update. + */ + public AdaDelta(Ops tf, String name, float learningRate, float rho, float epsilon) { + super(assertGraph(tf), name, learningRate, rho, epsilon); + initConfig(learningRate, rho, epsilon); + } + + /** {@inheritDoc} */ + @Override + protected Optional prepare(String name) { + switch (initializers.size()) { + case 0: + return Optional.empty(); + case 1: + return Optional.of(initializers.get(0)); + default: + return Optional.of( + ControlDependencies.addControlDependencies(tf, this.getOptimizerName(), initializers)); + } + } + + /** + * Create an Adam Optimizer from a config object + * + * @param graph the tensorflow graph + * @param config a config object to initialize, he config object has keys for "name", + * "learning_rate", "rho" and "epsilon". If a key is missing the default value is used. + */ + public static AdaDelta fromConfig(Ops tf, Map config) { + return create(tf, config); + } + + /** + * Create an Adadelta optimizer + * + * @param graph the tensorflow graph @@param config a config object to initialize, the config + * object has keys for "name", "learning_rate", "rho" and "epsilon". If a key is missing the + * default value is used. + */ + public static AdaDelta create(Ops tf, Map config) { + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float rho = (float) config.getOrDefault(RHO_RATE_KEY, RHO_DEFAULT); + float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT); + if (name == null) // doe this to get the default name + { + return new AdaDelta(tf, learningRate, rho, epsilon); + } else { + return new AdaDelta(tf, name, learningRate, rho, epsilon); + } + } + + /** + * Initialize the configuration based on which constructor is called. + * + * @param learningRate The learning rate + * @param rho The decay rate. + * @param epsilon A constant epsilon used to better conditioning the grad update. + */ + private void initConfig(float learningRate, float rho, float epsilon) { + this.learningRate = learningRate; + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(RHO_RATE_KEY, rho); + config.put(EPSILON_KEY, epsilon); + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } + + +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGrad.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGrad.java new file mode 100644 index 00000000000..6010a95b199 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGrad.java @@ -0,0 +1,167 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.Map; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.op.Ops; + +/** + * AdaGrad Optimizer that implements the AdaGrad algorithm. Adagrad is an optimizer with + * parameter-specific learning rates, which are adapted relative to how frequently a parameter gets + * updated during training. The more updates a parameter receives, the smaller the updates. + */ +public class AdaGrad extends org.tensorflow.framework.optimizers.AdaGrad + implements OptimizerInterface { + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String INITIAL_ACCUM_KEY = "accumulator"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; + public static final float INITIAL_ACCUM__DEFAULT = 0.1f; + + private Map config = new HashMap<>(); + private float learningRate; + + /** + * Create an AdaGrad Optimizer with name="Adagrad", learningRate=0.001F, and initial + * accumulator=0.1 + * + * @param tf the tensorflow Ops + */ + public AdaGrad(Ops tf) { + this(tf, LEARNING_RATE_DEFAULT, INITIAL_ACCUM__DEFAULT); + } + + /** + * Create an AdaGrad Optimizer with learningRate=0.001F, and initial accumulator=0.1 + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adagrad" + */ + public AdaGrad(Ops tf, String name) { + this(tf, name, LEARNING_RATE_DEFAULT, INITIAL_ACCUM__DEFAULT); + } + + /** + * Create an AdaGrad Optimizer with initial accumulator=0.1 + * + * @param tf the tensorflow Ops + * @param learningRate The learning rate. Defaults to 0.001. + */ + public AdaGrad(Ops tf, float learningRate) { + this(tf, learningRate, INITIAL_ACCUM__DEFAULT); + } + + /** + * Create an AdaGrad Optimizer + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adagrad" + * @param learningRate The learning rate. Defaults to 0.01. + */ + public AdaGrad(Ops tf, String name, float learningRate) { + this(tf, name, learningRate, INITIAL_ACCUM__DEFAULT); + } + + /** + * Create an AdaGrad Optimizer + * + * @param tf the tensorflow Ops + * @param learningRate The learning rate + * @param initialAccumulatorValue initial accumulator value + */ + public AdaGrad(Ops tf, float learningRate, float initialAccumulatorValue) { + super(assertGraph(tf), learningRate, initialAccumulatorValue); + initConfig(learningRate, initialAccumulatorValue); + } + + /** + * Create an AdaGrad Optimizer + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adagrad" + * @param learningRate The learning rate + * @param initialAccumulatorValue initial accumulator value, must be >= 0. + */ + public AdaGrad(Ops tf, String name, float learningRate, float initialAccumulatorValue) { + super(assertGraph(tf), name, learningRate, initialAccumulatorValue); + assert initialAccumulatorValue >= 0.0F + : "initial_accumulator_value must be non-negative: " + initialAccumulatorValue; + initConfig(learningRate, initialAccumulatorValue); + } + + /** + * Create an AdaGrad Optimizer from a config object + * + * @param graph the tensorflow graph + * @param config a config object to initialize, , the config object has keys for "name", + * "learning_rate" and "accumulator". If a key is missing the default value is used. + */ + public static AdaGrad fromConfig(Ops tf, Map config) { + return create(tf, config); + } + + /** + * Create an AdaGrad Optimizer from a config object + * + * @param graph the tensorflow graph + * @param config a config object to initialize, the config object has keys for "name", + * "learning_rate" and "accumulator". If a key is missing the default value is used. + */ + public static AdaGrad create(Ops tf, Map config) { + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float initialAccumulatorValue = + (float) config.getOrDefault(INITIAL_ACCUM_KEY, INITIAL_ACCUM__DEFAULT); + if (name != null) { + return new AdaGrad(tf, name, learningRate, initialAccumulatorValue); + } else { + return new AdaGrad(tf, learningRate, initialAccumulatorValue); + } + } + + /** + * Initialize the configuration + * + * @param learningRate + * @param initialAccumulatorValue + */ + private void initConfig(float learningRate, float initialAccumulatorValue) { + this.learningRate = learningRate; + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(INITIAL_ACCUM_KEY, initialAccumulatorValue); + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGradDA.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGradDA.java new file mode 100644 index 00000000000..d7ee03338c8 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGradDA.java @@ -0,0 +1,191 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.Map; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.op.Ops; + +/** Optimizer that implements the Adagrad Dual-Averaging algorithm. */ +public class AdaGradDA extends org.tensorflow.framework.optimizers.AdaGradDA + implements OptimizerInterface { + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String INITIAL_ACCUM_KEY = "accumulator"; + public static final String L1STRENGTH_KEY = "l1Strength"; + public static final String L2STRENGTH_KEY = "l2Strength"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; // arbitray number + public static final float INITIAL_ACCUM__DEFAULT = 0.1f; + public static final float L1STRENGTH_DEFAULT = 0.0F; + public static final float L2STRENGTH_DEFAULT = 0.0F; + + private Map config = new HashMap<>(); + private float learningRate; + + /** + * Create an AdagradDA Optimizer with default values name="adagrad-da". learning_rate=.001, + * initial accumulator= 0.1, l1Strength=0.0, l2Strength=0.0; + * + * @param tf the tensorflow tf + */ + public AdaGradDA(Ops tf) { + this(tf, LEARNING_RATE_DEFAULT, INITIAL_ACCUM__DEFAULT, L1STRENGTH_DEFAULT, L2STRENGTH_DEFAULT); + } + + /** + * Create an AdagradDA Optimizer with default values initial accumulator= 0.1, l1Strength=0.0, + * l2Strength=0.0; + * + * @param tf the tensorflow tf + * @param learningRate The learning rate. + */ + public AdaGradDA(Ops tf, float learningRate) { + this(tf, learningRate, INITIAL_ACCUM__DEFAULT, L1STRENGTH_DEFAULT, L2STRENGTH_DEFAULT); + } + + /** + * Create an AdagradDA Optimizer with default values initial accumulator= 0.1, l1Strength=0.0, + * l2Strength=0.0; + * + * @param tf the tensorflow tf + * @param name the name of the Optimizer, defaults to "adagrad-da" + * @param learningRate The learning rate. + */ + public AdaGradDA(Ops tf, String name, float learningRate) { + this(tf, name, learningRate, INITIAL_ACCUM__DEFAULT, L1STRENGTH_DEFAULT, L2STRENGTH_DEFAULT); + } + + /** + * Create an AdagradDA Optimizer + * + * @param tf the tensorflow tf + * @param learningRate the learning rate, default is 0.001 + * @param initialAccumulatorValue Starting value for the accumulators, must be >= 0.0. + * @param l1Strength L1 Regularization Strength + * @param l2Strength L2 Regularization Strength + */ + public AdaGradDA( + Ops tf, + float learningRate, + float initialAccumulatorValue, + float l1Strength, + float l2Strength) { + super(assertGraph(tf), learningRate, initialAccumulatorValue, l1Strength, l2Strength); + assert initialAccumulatorValue >= 0.0F + : "initial_accumulator_value must be non-negative: " + initialAccumulatorValue; + assert l1Strength >= 0.0F : "l1Strength must be non-negative: " + l1Strength; + assert l2Strength >= 0.0F : "l2Strength must be non-negative: " + l2Strength; + initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength); + } + + /** + * Create an AdagradDA Optimizer + * + * @param tf the tensorflow tf + * @param name the name of the Optimizer, defaults to "adagrad-da" + * @param learningRate the learning rate, default is 0.001 + * @param initialAccumulatorValue Starting value for the accumulators, must be positive. + * @param l1Strength L1 Regularization Strength + * @param l2Strength L2 Regularization Strength + */ + public AdaGradDA( + Ops tf, + String name, + float learningRate, + float initialAccumulatorValue, + float l1Strength, + float l2Strength) { + super(assertGraph(tf), name, learningRate, initialAccumulatorValue, l1Strength, l2Strength); + assert initialAccumulatorValue >= 0.0F + : "initial_accumulator_value must be non-negative: " + initialAccumulatorValue; + assert l1Strength >= 0.0F : "l1Strength must be non-negative: " + l1Strength; + assert l2Strength >= 0.0F : "l2Strength must be non-negative: " + l2Strength; + initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength); + } + + /** + * Create an AdaGrad Optimizer from a config object + * + * @param tf the tensorflow tf + * @param config a config object to initialize, , the config object has keys for "name", + * "learning_rate", "accumulator", "l1Strength" and "l2Strength". If a key is missing the + * default value is used. + * @return the new AdaGradDA Optimizer + */ + public static AdaGradDA fromConfig(Ops tf, Map config) { + return create(tf, config); + } + + /** + * Create an AdaGradDA Optimizer from a config object + * + * @param tf the tensorflow tf + * @param config a config object to initialize, the config object has keys for "name", + * "learning_rate", "accumulator", "l1Strength" and "l2Strength". If a key is missing the + * default value is used. + * @return the new AdaGradDA Optimizer + */ + public static AdaGradDA create(Ops tf, Map config) { + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float initialAccumulatorValue = + (float) config.getOrDefault(INITIAL_ACCUM_KEY, INITIAL_ACCUM__DEFAULT); + float l1Strength = (float) config.getOrDefault(L1STRENGTH_KEY, L2STRENGTH_DEFAULT); + float l2Strength = (float) config.getOrDefault(L2STRENGTH_KEY, L2STRENGTH_DEFAULT); + if (name != null) { + return new AdaGradDA(tf, name, learningRate, initialAccumulatorValue, l1Strength, l2Strength); + } else { + return new AdaGradDA(tf, learningRate, initialAccumulatorValue, l1Strength, l2Strength); + } + } + + /** + * Initialize the Optimizer from a config object based on which constructor is called. + * + * @param learningRate the learning rate, default is 0.001 + * @param initialAccumulatorValue Starting value for the accumulators, must be >= 0.0. + * @param l1Strength L1 Regularization Strength + * @param l2Strength L2 Regularization Strength + */ + private void initConfig( + float learningRate, float initialAccumulatorValue, float l1Strength, float l2Strength) { + this.learningRate = learningRate; + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(INITIAL_ACCUM_KEY, initialAccumulatorValue); + config.put(L1STRENGTH_KEY, l1Strength); + config.put(L2STRENGTH_KEY, l2Strength); + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adam.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adam.java new file mode 100644 index 00000000000..5d74c7e27f4 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adam.java @@ -0,0 +1,182 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.Map; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.op.Ops; + +/** Adam Optimizer that implements the Adam algorithm. */ +public class Adam extends org.tensorflow.framework.optimizers.Adam implements OptimizerInterface { + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String EPSILON_KEY = "epsilon"; + public static final String BETA_ONE_KEY = "beta_1"; + public static final String BETA_TWO_KEY = "beta_2"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; + public static final float EPSILON_DEFAULT = 1e-07F; + public static final float BETA_ONE_DEFAULT = 0.9F; + public static final float BETA_TWO_DEFAULT = 0.999F; + + private float learningRate; + private Map config = new HashMap<>(); + + /** + * Create an Adam Optimizer + * + * @param tf the tensorflow Ops + */ + public Adam(Ops tf) { + this(tf, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adam Optimizer + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adam" + */ + public Adam(Ops tf, String name) { + this(tf, name, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adam Optimizer + * + * @param tf the tensorflow Ops + * @param learningRate The learning rate. Defaults to 0.001. + */ + public Adam(Ops tf, float learningRate) { + this(tf, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adam Optimizer + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adam" + * @param learningRate The learning rate. Defaults to 0.001. + */ + public Adam(Ops tf, String name, float learningRate) { + this(tf, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Adam Optimizer + * + * @param tf the tensorflow Ops + * @param learningRate The learning rate. Defaults to 0.001. + * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9. + * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999. + * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the + * Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm + * 1 of the paper. Defaults to 1e-7. + */ + public Adam(Ops tf, float learningRate, float betaOne, float betaTwo, float epsilon) { + super(assertGraph(tf), learningRate, betaOne, betaTwo, epsilon); + initConfig(learningRate, betaOne, betaTwo, epsilon); + } + + /** + * Create an Adam Optimizer + * + * @param tf the tensorflow Ops + * @param name the name of the Optimizer, defaults to "Adam" + * @param learningRate The learning rate. Defaults to 0.001. + * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9. + * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999. + * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the + * Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm + * 1 of the paper. Defaults to 1e-7. + */ + public Adam( + Ops tf, String name, float learningRate, float betaOne, float betaTwo, float epsilon) { + super(assertGraph(tf), name, learningRate, betaOne, betaTwo, epsilon); + initConfig(learningRate, betaOne, betaTwo, epsilon); + } + + /** + * Create an Adam Optimizer from a config object + * + * @param tf the tensorflow Ops + * @param config a config object to initialize, the config object has keys for "name", + * "learning_rate", "epsilon", "beta_1", "beta_2". If a key is missing the default value is + * used. + */ + public static Adam fromConfig(Ops tf, Map config) { + return create(tf, config); + } + + /** + * Create an Adam Optimizer from a config object + * + * @param tf the tensorflow Ops + * @param config a config object to initialize, the config object has keys for "name", + * "learning_rate", "epsilon", "beta_1", "beta_2". If a key is missing the default value is + * used. + */ + public static Adam create(Ops tf, Map config) { + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT); + float betaOne = (float) config.getOrDefault(BETA_ONE_KEY, BETA_ONE_DEFAULT); + float betaTwo = (float) config.getOrDefault(BETA_TWO_KEY, BETA_TWO_DEFAULT); + if (name == null) { + return new Adam(tf, learningRate, betaOne, betaTwo, epsilon); + } else { + return new Adam(tf, name, learningRate, betaOne, betaTwo, epsilon); + } + } + + /** + * Initialize the Optimizer from a config object based on which constructor is called. + * + * @param learningRate The learning rate. Defaults to 0.001. + * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9. + * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999. + * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the + * Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm + * 1 of the paper. Defaults to 1e-7. + */ + protected void initConfig(float learningRate, float betaOne, float betaTwo, float epsilon) { + this.learningRate = learningRate; + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(EPSILON_KEY, epsilon); + config.put(BETA_ONE_KEY, betaOne); + config.put(BETA_TWO_KEY, betaTwo); + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adamax.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adamax.java new file mode 100644 index 00000000000..a976a6e51dd --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adamax.java @@ -0,0 +1,283 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Optional; +import org.tensorflow.Graph; +import org.tensorflow.Operand; +import org.tensorflow.Output; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.Scope; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.op.train.ApplyAdaMax; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.family.TType; + +/** Adamax Optimizer that implements the Adamax algorithm. */ +public class Adamax extends org.tensorflow.framework.optimizers.Optimizer + implements OptimizerInterface { + + public static final String FIRST_MOMENT = "m"; + public static final String SECOND_MOMENT = "v"; + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String EPSILON_KEY = "epsilon"; + public static final String BETA_ONE_KEY = "beta_1"; + public static final String BETA_TWO_KEY = "beta_2"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; + public static final float EPSILON_DEFAULT = 1e-07F; + public static final float BETA_ONE_DEFAULT = 0.9F; + public static final float BETA_TWO_DEFAULT = 0.999F; + + private Scope scope; + private Map config = new HashMap<>(); + + private float learningRate; + private final float betaOne; + private final float betaTwo; + private final float epsilon; + + private Constant learningRateConst; + private Constant epsilonConst; + private Constant betaOneConst; + private Constant betaTwoConst; + private Variable betaOnePower; + + /** + * Create an Optimizer that implements the Adamax algorithm. + * + * @param tf the TensoFlow Ops + */ + public Adamax(Ops tf) { + this(tf, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the Adamax algorithm. + * + * @param tf the TensoFlow Ops + * @param name name for the operations Created when applying gradients. Defaults to "Adamax". + */ + public Adamax(Ops tf, String name) { + this(tf, name, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the Adamax algorithm. + * + * @param tf the TensoFlow Ops + * @param learningRate The learning rate. + */ + public Adamax(Ops tf, float learningRate) { + this(tf, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the Adamax algorithm. + * + * @param tf the TensoFlow Ops + * @param name name for the operations Created when applying gradients. Defaults to "Adamax". + * @param learningRate The learning rate. + */ + public Adamax(Ops tf, String name, float learningRate) { + this(tf, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the Adamax algorithm. + * + * @param tf the TensoFlow Ops + * @param learningRate The learning rate. + * @param betaOne The exponential decay rate for the 1st moment estimates. + * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm. + * @param epsilon A small constant for numerical stability. + */ + public Adamax(Ops tf, float learningRate, float betaOne, float betaTwo, float epsilon) { + super(assertGraph(tf)); + this.learningRate = learningRate; + this.betaOne = betaOne; + this.betaTwo = betaTwo; + this.epsilon = epsilon; + this.scope = tf.scope(); + initConfig(learningRate, betaOne, betaTwo, epsilon); + } + + /** + * Create an Optimizer that implements the Adamax algorithm. + * + * @param tf the TensoFlow Ops + * @param name name for the operations Created when applying gradients. Defaults to "Adamax". + * @param learningRate The learning rate. + * @param betaOne The exponential decay rate for the 1st moment estimates. + * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm. + * @param epsilon A small constant for numerical stability. + */ + public Adamax( + Ops tf, String name, float learningRate, float betaOne, float betaTwo, float epsilon) { + super(assertGraph(tf), name); + this.learningRate = learningRate; + this.betaOne = betaOne; + this.betaTwo = betaTwo; + this.epsilon = epsilon; + this.scope = tf.scope(); + + initConfig(learningRate, betaOne, betaTwo, epsilon); + } + + /** + * Create an Optimizer that implements the Adamax algorithm from a config object + * + * @param tf the TensoFlow Ops + * @param config a config object to initialize, the config object has keys for "name", + * "learning_rate", "epsilon", "beta_1", "beta_2". If a key is missing the default value is + * used. + */ + public static Adamax fromConfig(Ops tf, Map config) { + return create(tf, config); + } + + /** + * Create an Optimizer that implements the Adamax algorithm from a config object + * + * @param tf the TensoFlow Ops + * @param config a config object to initialize + */ + public static Adamax create(Ops tf, Map config) { + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT); + float betaOne = (float) config.getOrDefault(BETA_ONE_KEY, BETA_ONE_DEFAULT); + float betaTwo = (float) config.getOrDefault(BETA_TWO_KEY, BETA_TWO_DEFAULT); + if (name == null) { + return new Adamax(tf, learningRate, betaOne, betaTwo, epsilon); + } else { + return new Adamax(tf, name, learningRate, betaOne, betaTwo, epsilon); + } + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } + + /** {@inheritDoc} */ + @Override + protected Optional prepare(String scopeName) { + betaOneConst = tf.constant(betaOne); + betaTwoConst = tf.constant(betaTwo); + learningRateConst = tf.constant(learningRate); + epsilonConst = tf.constant(epsilon); + + return Optional.empty(); + } + + /** {@inheritDoc} */ + @Override + protected void createSlots(List> variables) { + for (Output v : variables) { + createAdamaxSlot(v.asOutput()); + } + betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE); + Assign betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne)); + ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit); + } + + /** + * Create the first and second moment slots + * + * @param v the variable + * @param the datatype of the variable + */ + private void createAdamaxSlot(Output v) { + Operand firstMomentInitializer = + tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType())); + createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer); + Operand secondMomentInitializer = + tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType())); + createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer); + } + + /** {@inheritDoc} */ + @Override + protected Op applyDense(Output gradient, Output variable) { + Variable firstMomentSlot = getSlot(variable, FIRST_MOMENT).get(); + Variable secondMomentSlot = getSlot(variable, SECOND_MOMENT).get(); + return ApplyAdaMax.create( + scope, + (Operand) variable, + (Operand) firstMomentSlot, + (Operand) secondMomentSlot, + (Operand) tf.dtypes.cast(betaOnePower, gradient.dataType()), + (Operand) tf.dtypes.cast(learningRateConst, gradient.dataType()), + (Operand) tf.dtypes.cast(betaOneConst, gradient.dataType()), + (Operand) tf.dtypes.cast(betaTwoConst, gradient.dataType()), + (Operand) tf.dtypes.cast(epsilonConst, gradient.dataType()), + (Operand) gradient); + } + + /** {@inheritDoc} */ + @Override + protected Op finish(List updateOperations, String name) { + updateOperations.add(tf.assign(betaOnePower, tf.math.mul(betaOnePower, betaOneConst))); + return super.finish(updateOperations, name); + } + + /** {@inheritDoc} */ + @Override + public String getOptimizerName() { + return "Adamax"; + } + + /** + * Initialize the Optimizer from a config object based on which constructor is called. + * + * @param learningRate The learning rate. Defaults to 0.001. + * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9. + * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999. + * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the + * Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm + * 1 of the paper. Defaults to 1e-7. + */ + protected void initConfig(float learningRate, float betaOne, float betaTwo, float epsilon) { + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(EPSILON_KEY, epsilon); + config.put(BETA_ONE_KEY, betaOne); + config.put(BETA_TWO_KEY, betaTwo); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Ftrl.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Ftrl.java new file mode 100644 index 00000000000..aec7af8d6c9 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Ftrl.java @@ -0,0 +1,360 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.tensorflow.Operand; +import org.tensorflow.Output; +import org.tensorflow.Session; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Placeholder; +import org.tensorflow.op.core.Variable; +import org.tensorflow.op.train.ApplyFtrl; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.family.TType; + +/** Ftrl Optimizer that implements the FTRL algorithm. */ +public class Ftrl extends org.tensorflow.framework.optimizers.Optimizer + implements OptimizerInterface { + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String LEARNING_RATE_POWER_KEY = "learning_rate_power"; + public static final String INITIAL_ACCUM_VALUE_KEY = "initial_accumulator_value"; + public static final String L1STRENGTH_KEY = "l1_regularization_strength"; + public static final String L2STRENGTH_KEY = "l2_regularization_strength"; + public static final String L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY = + "l2_shrinkage_regularization_strength"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; + public static final float LEARNING_RATE_POWER_DEFAULT = -0.5F; + public static final float INITIAL_ACCUM_VALUE_DEFAULT = 0.1F; + public static final float L1STRENGTH_DEFAULT = 0.0F; + public static final float L2STRENGTH_DEFAULT = 0.0F; + public static final float L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT = 0.0F; + + public static final String ACCUMULATOR = "gradient_accumulator"; + public static final String LINEAR_ACCUMULATOR = "linear_accumulator"; + + private final String name; + private float learningRate; + private final float learningRatePower; + private final float initialAccumulatorValue; + private final float l1RegularizationStrength; + private final float l2RegularizationStrength; + private final float l2ShrinkageRegularizationStrength; + + private Map config = new HashMap<>(); + + private boolean useLocking = true; + + /** + * Create a Ftrl Optimizer + * + * @param tf the TensorFlow Ops + */ + public Ftrl(Ops tf) { + this( + tf, + LEARNING_RATE_DEFAULT, + LEARNING_RATE_POWER_DEFAULT, + INITIAL_ACCUM_VALUE_DEFAULT, + L1STRENGTH_DEFAULT, + L2STRENGTH_DEFAULT, + L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT); + } + + /** + * Create a Ftrl Optimizer + * + * @param tf the TensorFlow Ops + * @param name the Optmizer name + */ + public Ftrl(Ops tf, String name) { + this( + tf, + name, + LEARNING_RATE_DEFAULT, + LEARNING_RATE_POWER_DEFAULT, + INITIAL_ACCUM_VALUE_DEFAULT, + L1STRENGTH_DEFAULT, + L2STRENGTH_DEFAULT, + L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT); + } + + /** + * Create a Ftrl Optimizer + * + * @param tf the TensorFlow Ops + * @param learningRate the learning rate + */ + public Ftrl(Ops tf, float learningRate) { + this( + tf, + learningRate, + LEARNING_RATE_POWER_DEFAULT, + INITIAL_ACCUM_VALUE_DEFAULT, + L1STRENGTH_DEFAULT, + L2STRENGTH_DEFAULT, + L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT); + } + + /** + * Create a Ftrl Optimizer + * + * @param tf the TensorFlow Ops + * @param name the Optmizer name + * @param learningRate the learning rate + */ + public Ftrl(Ops tf, String name, float learningRate) { + this( + tf, + name, + learningRate, + LEARNING_RATE_POWER_DEFAULT, + INITIAL_ACCUM_VALUE_DEFAULT, + L1STRENGTH_DEFAULT, + L2STRENGTH_DEFAULT, + L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT); + } + + /** + * Create a Ftrl Optimizer + * + * @param tf the TensorFlow Ops + * @param learningRate the learning rate + * @param learningRatePower + * @param initialAccumulatorValue + * @param l1Strength + * @param l2Strength + * @param l2ShrinkageRegularizationStrength + */ + public Ftrl( + Ops tf, + float learningRate, + float learningRatePower, + float initialAccumulatorValue, + float l1Strength, + float l2Strength, + float l2ShrinkageRegularizationStrength) { + super(assertGraph(tf)); + this.name = getOptimizerName(); + this.learningRate = learningRate; + this.learningRatePower = learningRatePower; + this.initialAccumulatorValue = initialAccumulatorValue; + this.l1RegularizationStrength = l1Strength; + this.l2RegularizationStrength = l2Strength; + this.l2ShrinkageRegularizationStrength = l2ShrinkageRegularizationStrength; + validateParams(); + initConfig(); + } + + /** + * Create a Ftrl Optimizer + * + * @param tf the TensorFlow Ops + * @param name the Optmizer name + * @param learningRate the learning rate + * @param learningRatePower + * @param initialAccumulatorValue + * @param l1Strength + * @param l2Strength + * @param l2ShrinkageRegularizationStrength + */ + public Ftrl( + Ops tf, + String name, + float learningRate, + float learningRatePower, + float initialAccumulatorValue, + float l1Strength, + float l2Strength, + float l2ShrinkageRegularizationStrength) { + super(assertGraph(tf), name); + this.name = name; + this.learningRate = learningRate; + this.learningRatePower = learningRatePower; + this.initialAccumulatorValue = initialAccumulatorValue; + this.l1RegularizationStrength = l1Strength; + this.l2RegularizationStrength = l2Strength; + this.l2ShrinkageRegularizationStrength = l2ShrinkageRegularizationStrength; + validateParams(); + initConfig(); + } + + + + /** + * Create a Ftrl Optmizer + * + * @param tf the TensorFlow Ops + * @param config a config object to initialize + * @return a new Frtl Optimizer + */ + public static Ftrl create(Ops tf, Map config) { + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float learningRatePower = + (float) config.getOrDefault(LEARNING_RATE_POWER_KEY, LEARNING_RATE_POWER_DEFAULT); + float initialAccumulatorValue = + (float) config.getOrDefault(INITIAL_ACCUM_VALUE_KEY, INITIAL_ACCUM_VALUE_DEFAULT); + float l1RegularizationStrength = + (float) config.getOrDefault(L1STRENGTH_KEY, L1STRENGTH_DEFAULT); + float l2RegularizationStrength = + (float) config.getOrDefault(L2STRENGTH_KEY, L2STRENGTH_DEFAULT); + float l2ShrinkageRegularizationStrength = + (float) + config.getOrDefault( + L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY, + L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT); + + if (name == null) { + return new Ftrl( + tf, + learningRate, + learningRatePower, + initialAccumulatorValue, + l1RegularizationStrength, + l2RegularizationStrength, + l2ShrinkageRegularizationStrength); + } else { + return new Ftrl( + tf, + name, + learningRate, + learningRatePower, + initialAccumulatorValue, + l1RegularizationStrength, + l2RegularizationStrength, + l2ShrinkageRegularizationStrength); + } + } + + /** Initialize the Config object from the current settings */ + protected void initConfig() { + config.put(NAME_KEY, this.name); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(LEARNING_RATE_POWER_KEY, learningRatePower); + config.put(INITIAL_ACCUM_VALUE_KEY, initialAccumulatorValue); + config.put(L1STRENGTH_KEY, l1RegularizationStrength); + config.put(L2STRENGTH_KEY, l2RegularizationStrength); + config.put(L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY, l2ShrinkageRegularizationStrength); + } + + /** Validate all the settings of the Frtl Optmizer */ + private void validateParams() { + if (this.initialAccumulatorValue < 0.0F) { + throw new IllegalArgumentException( + String.format( + "initialAccumulatorValue %f needs to be positive or zero", + this.initialAccumulatorValue)); + } + if (this.learningRatePower > 0.0F) { + throw new IllegalArgumentException( + String.format( + "learningRatePower %f needs to be negative or zero", this.learningRatePower)); + } + if (this.l1RegularizationStrength < 0.0F) { + throw new IllegalArgumentException( + String.format( + "'l1RegularizationStrength %f needs to be positive or zero", + this.l1RegularizationStrength)); + } + if (this.l2RegularizationStrength < 0.0F) { + throw new IllegalArgumentException( + String.format( + "'l2RegularizationStrength %f needs to be positive or zero", + this.l2RegularizationStrength)); + } + if (this.l2ShrinkageRegularizationStrength < 0.0F) { + throw new IllegalArgumentException( + String.format( + "'l2ShrinkageRegularizationStrength %f needs to be positive or zero", + this.l2RegularizationStrength)); + } + } + + /** {@inheritDoc} */ + @Override + protected void createSlots(List> variables) { + for (Output v : variables) { + createFtrlSlot(v); + } + } + + /** + * Create a slot variables for the accumulators + * + * @param v the variable + * @param the data type of the variable + */ + private void createFtrlSlot(Output v) { + Operand initializer = + tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType())); + createSlot(v.asOutput(), ACCUMULATOR, initializer); + Operand linearInitializer = + tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType())); + createSlot(v.asOutput(), LINEAR_ACCUMULATOR, linearInitializer); + } + + /** {@inheritDoc} */ + @Override + protected Op applyDense(Output gradient, Output variable) { + Variable accumSlot = getSlot(variable, ACCUMULATOR).get(); + Variable linearSlot = getSlot(variable, LINEAR_ACCUMULATOR).get(); + ApplyFtrl.Options options = ApplyFtrl.useLocking(useLocking); + return this.tf.train.applyFtrl( + variable, + accumSlot, // accum + linearSlot, // linear + gradient, // gradient + tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), // lr + tf.dtypes.cast(tf.constant(l1RegularizationStrength), gradient.dataType()), // l1 + tf.dtypes.cast(tf.constant(l2RegularizationStrength), gradient.dataType()), // l2 + tf.dtypes.cast( + tf.constant(l2ShrinkageRegularizationStrength), gradient.dataType()), // l2Shrinkage + tf.dtypes.cast(tf.constant(learningRatePower), gradient.dataType()), // lrPower + options); + } + + /** {@inheritDoc} */ + @Override + public String getOptimizerName() { + return "Ftrl"; + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Nadam.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Nadam.java new file mode 100644 index 00000000000..4772c247ef8 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Nadam.java @@ -0,0 +1,402 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Optional; +import org.tensorflow.Graph; +import org.tensorflow.Operand; +import org.tensorflow.Output; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.Scope; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.family.TType; + +/** Nadam Optimizer that implements the NAdam algorithm. */ +public class Nadam extends org.tensorflow.framework.optimizers.Optimizer + implements OptimizerInterface { + + public static final String FIRST_MOMENT = "m"; + public static final String SECOND_MOMENT = "v"; + public static final String MOMENTUM = "momentum"; + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String EPSILON_KEY = "epsilon"; + public static final String BETA_ONE_KEY = "beta_1"; + public static final String BETA_TWO_KEY = "beta_2"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; + public static final float EPSILON_DEFAULT = 1e-07F; + public static final float BETA_ONE_DEFAULT = 0.9F; + public static final float BETA_TWO_DEFAULT = 0.999F; + + private Scope scope; + private final Map config = new HashMap<>(); + + private float learningRate; + private final float betaOne; + private final float betaTwo; + private final float epsilon; + private final float decayBase = 0.96F; + private final float decay = 0.004F; + + private long iterations = 0; + + private Constant learningRateConst; + private Constant betaOneConst; + private Constant betaTwoConst; + private Constant localStepConst; + private Constant nextStepConst; + + private Constant decayBaseConst; + private Constant decayConst; + private Constant epsilonConst; + + private Variable betaOnePower; + private Variable betaTwoPower; + private Variable momentum; + + private Operand m_t; + private Operand m_t_1; + private Operand m_schedule_new; + private Operand m_schedule_next; + private Operand one_minus_beta_1; + private Operand one_minus_beta_2; + private Operand one_minus_m_t; + private Operand one_minus_m_schedule_new; + private Operand one_minus_m_schedule_next; + private Operand v_t_prime_denominator; + + /** + * Create an Optimizer that implements the NAdam algorithm. + * + * @param tf the TensorFlow Ops + */ + public Nadam(Ops tf) { + this(tf, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the NAdam algorithm. + * + * @param tf the TensorFlow Ops + * @param name name for the operations created when applying gradients. Defaults to "Nadam". + */ + public Nadam(Ops tf, String name) { + this(tf, name, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the NAdam algorithm. + * + * @param tf the TensorFlow Ops + * @param learningRate The learning rate. + */ + public Nadam(Ops tf, float learningRate) { + this(tf, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the NAdam algorithm. + * + * @param tf the TensorFlow Ops + * @param name name for the operations created when applying gradients. Defaults to "Adamax". + * @param learningRate The learning rate. + */ + public Nadam(Ops tf, String name, float learningRate) { + this(tf, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT); + } + + /** + * Create an Optimizer that implements the NAdam algorithm. + * + * @param tf the TensorFlow Ops + * @param learningRate The learning rate. + * @param betaOne The exponential decay rate for the 1st moment estimates. + * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm. + * @param epsilon A small constant for numerical stability. + */ + public Nadam(Ops tf, float learningRate, float betaOne, float betaTwo, float epsilon) { + super(assertGraph(tf)); + this.learningRate = learningRate; + this.betaOne = betaOne; + this.betaTwo = betaTwo; + this.epsilon = epsilon; + this.scope = tf.scope(); + initConfig(learningRate, betaOne, betaTwo, epsilon); + } + + /** + * Create an Optimizer that implements the NAdam algorithm. + * + * @param tf the TensorFlow Ops + * @param name name for the operations created when applying gradients. + * @param learningRate The learning rate. + * @param betaOne The exponential decay rate for the 1st moment estimates. + * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm. + * @param epsilon A small constant for numerical stability. + */ + public Nadam( + Ops tf, String name, float learningRate, float betaOne, float betaTwo, float epsilon) { + super(assertGraph(tf), name); + this.learningRate = learningRate; + this.betaOne = betaOne; + this.betaTwo = betaTwo; + this.epsilon = epsilon; + this.scope = tf.scope(); + + initConfig(learningRate, betaOne, betaTwo, epsilon); + } + + /** + * Create an Optimizer that implements the NAdam algorithm. + * + * @param tf the TensorFlow Ops + * @param config a config object to initialize + */ + public static Nadam create(Ops tf, Map config) { + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT); + float betaOne = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float betaTwo = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + if (name == null) { + return new Nadam(tf, learningRate, betaOne, betaTwo, epsilon); + } else { + return new Nadam(tf, name, learningRate, betaOne, betaTwo, epsilon); + } + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } + + /** {@inheritDoc} */ + @Override + protected void createSlots(List> variables) { + for (Output v : variables) { + createNadamSlot(v.asOutput()); + } + betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE); + Assign betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne)); + ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit); + + betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.DTYPE); + Assign betaTwoPowerInit = tf.assign(betaTwoPower, tf.constant(betaTwo)); + ((Graph) tf.scope().env()).addInitializer(betaTwoPowerInit); + + momentum = tf.withName("momentum").variable(Shape.scalar(), TFloat32.DTYPE); + Assign momentumInit = tf.assign(momentum, tf.constant(1.0F)); + ((Graph) tf.scope().env()).addInitializer(momentumInit); + } + + /** + * Create slots for first and second momements and momentum + * @param v the variable + * @param the data type or the Variable + */ + private void createNadamSlot(Output v) { + Operand firstMomentInitializer = + tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType())); + createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer); + Operand secondMomentInitializer = + tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType())); + createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer); + + Operand momentumInitializer = + tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.dataType())); + createSlot(v.asOutput(), MOMENTUM, momentumInitializer); + } + + /** {@inheritDoc} */ + @Override + protected Optional prepare(String scopeName) { + Constant one = tf.constant(1.0F); + Constant point5 = tf.constant(0.5F); + + learningRateConst = tf.constant(learningRate); + betaOneConst = tf.constant(betaOne); + betaTwoConst = tf.constant(betaTwo); + localStepConst = tf.constant(this.iterations + 1); + nextStepConst = tf.constant(this.iterations + 2); + decayConst = tf.constant(decay); + decayBaseConst = tf.constant(this.decayBase); + epsilonConst = tf.constant(this.epsilon); + + // m_t = beta_1_t * (1. - 0.5 * ( math_ops.pow(decay_base, self._initial_decay * local_step))) + m_t = + tf.math.mul( + betaOneConst, + tf.math.sub( + one, + tf.math.mul( + point5, + tf.math.pow( + decayBaseConst, + tf.math.mul(decayConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE)))))); + // m_t_1 = beta_1_t * (1. - 0.5 * ( math_ops.pow(decay_base, self._initial_decay * next_step))) + m_t_1 = + tf.math.mul( + betaOneConst, + tf.math.sub( + one, + tf.math.mul( + point5, + tf.math.pow( + decayBaseConst, + tf.math.mul(decayConst, tf.dtypes.cast(nextStepConst, TFloat32.DTYPE)))))); + + // m_schedule_new = math_ops.cast(self._m_cache_read, var_dtype) * m_t + m_schedule_new = tf.math.mul(momentum, m_t); + // if var_dtype is self._m_cache.dtype: + // m_schedule_new = array_ops.identity(state_ops.assign( + // self._m_cache, m_schedule_new, use_locking=self._use_locking)) + m_schedule_new = tf.identity(tf.assign(momentum, m_schedule_new, Assign.useLocking(true))); + // m_schedule_next = m_schedule_new * m_t_1 + m_schedule_next = tf.math.mul(m_schedule_new, m_t_1); + + // 1 - beta_1_t + one_minus_beta_1 = tf.math.sub(one, betaOneConst); + // 1 - beta_2_t, + one_minus_beta_2 = tf.math.sub(one, betaTwoConst); + // 1. - m_t, + one_minus_m_t = tf.math.sub(one, m_t); + // 1. - m_schedule_new + one_minus_m_schedule_new = tf.math.sub(one, m_schedule_new); + // 1. - m_schedule_next + one_minus_m_schedule_next = tf.math.sub(one, m_schedule_next); + // 1. - math_ops.pow(beta_2_t, local_step) + v_t_prime_denominator = + tf.math.sub(one, tf.math.pow(betaTwoConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE))); + return Optional.empty(); + } + + /** {@inheritDoc} */ + @Override + protected Op applyDense(Output gradient, Output variable) { + Variable m = getSlot(variable, FIRST_MOMENT).get(); // first Moment + Variable v = getSlot(variable, SECOND_MOMENT).get(); // Second Moment + + // g_prime = grad / coefficients['one_minus_m_schedule_new'] + Operand g_prime = tf.math.div((Operand) gradient, one_minus_m_schedule_new); + // m_t = (coefficients['beta_1_t'] * m + coefficients['one_minus_beta_1_t'] * grad) + Operand m_t = + tf.math.add( + tf.math.mul(betaOneConst, (Operand) m), + tf.math.mul(one_minus_beta_1, (Operand) gradient)); + // m_t = state_ops.assign(m, m_t, use_locking=self._use_locking) + // update m + m_t = tf.assign(m, m_t, Assign.useLocking(true)); + + // m_t_prime = m_t / coefficients['one_minus_m_schedule_next'] + Operand m_t_prime = tf.math.div(m_t, one_minus_m_schedule_next); + + // v_t = (coefficients['beta_2_t'] * v + coefficients['one_minus_beta_2_t'] * + // math_ops.square(grad)) + Operand v_t = + tf.math.add( + tf.math.mul(betaTwoConst, (Operand) v), + tf.math.mul(one_minus_beta_2, tf.math.square((Operand) gradient))); + // v_t = state_ops.assign(v, v_t, use_locking=self._use_locking) + // update v + v_t = tf.assign(v, v_t, Assign.useLocking(true)); + + // v_t_prime = v_t / coefficients['v_t_prime_denominator'] + Operand v_t_prime = tf.math.div(v_t, v_t_prime_denominator); + + // m_t_bar = (coefficients['one_minus_m_t'] * g_prime + coefficients['m_t_1'] * m_t_prime) + Operand m_t_bar = + tf.math.add(tf.math.mul(one_minus_m_t, g_prime), tf.math.mul(m_t_1, m_t_prime)); + // var_t = var - coefficients['lr_t'] * m_t_bar / (math_ops.sqrt(v_t_prime) + + // coefficients['epsilon']) + Operand var_t = + tf.math.sub( + variable, + tf.math.div( + tf.math.mul(learningRateConst, m_t_bar), + tf.math.add(tf.math.sqrt(v_t_prime), epsilonConst))); + // assign(var, var_t, use_locking=self._use_locking) + return tf.assign(variable, var_t, Assign.useLocking(true)); + } + + /** + * Gathers up the update operations into a single op that can be used as a run target. + * + *

Adds the betaOne, betaTwo and mu updates to the end of the updates list. + * + * @param updateOperations The update operations. + * @param name The name of the run target. + * @return A NoOp with a control dependency on each update operation. + */ + @Override + protected Op finish(List updateOperations, String name) { + iterations++; // increment the step; + updateOperations.add(tf.assign(betaOnePower, tf.math.mul(betaOnePower, betaOneConst))); + updateOperations.add(tf.assign(betaTwoPower, tf.math.mul(betaTwoPower, betaTwoConst))); + return super.finish(updateOperations, name); + } + + /** {@inheritDoc} */ + @Override + public String getOptimizerName() { + return "Nadam"; + } + + /** + * Sets the config object based on the current state of the Optmizer. + * + * @param learningRate The learning rate. Defaults to 0.001. + * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9. + * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999. + * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the + * Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm + * 1 of the paper. Defaults to 1e-7. + */ + private void initConfig(float learningRate, float betaOne, float betaTwo, float epsilon) { + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(EPSILON_KEY, epsilon); + config.put(BETA_ONE_KEY, betaOne); + config.put(BETA_TWO_KEY, betaTwo); + } + + private float calcM(int iteration) { + return betaOne * (1 - .05F * (float) Math.pow(this.decayBase, this.decay * iteration)); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/OptimizerInterface.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/OptimizerInterface.java new file mode 100644 index 00000000000..9e3223deb80 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/OptimizerInterface.java @@ -0,0 +1,59 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.Map; +import org.tensorflow.Graph; +import org.tensorflow.op.Ops; + +/** The main Interface for Keras Optimizers */ +public interface OptimizerInterface { + + /** The value for the name key in the Config object */ + public static final String NAME_KEY = "name"; + + /** + * Get a TensorFlow Graph from the Ops. + * + * @param tf the TensorFlow Ops + * @return the graph + * @throws java.lang.AssertionError if the TensorFlow Ops does not represent Graph mode + */ + public static Graph assertGraph(Ops tf) { + assert tf.scope().env().isGraph() : "Optimizers can only be used in Graph Mode"; + return (Graph) tf.scope().env(); + } + + /** + * Return the config object used to initialize the Optimizer + * + * @return the config object used to initialize the Optimizer + */ + public Map getConfig(); + + /** + * Return the current learning rate + * + * @return the current learning rate + */ + public float getLearningRate(); + + /** + * Set the learning rate + * + * @param learningRate the learning rate; + */ + public void setLearningRate(float learningRate); +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Optimizers.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Optimizers.java new file mode 100644 index 00000000000..3892e239dad --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Optimizers.java @@ -0,0 +1,124 @@ +/* Copyright 2020 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.keras.optimizers; + +import org.tensorflow.framework.optimizers.Optimizer; +import org.tensorflow.op.Ops; + +import java.lang.reflect.Constructor; +import java.lang.reflect.InvocationTargetException; +import java.util.HashMap; +import java.util.Map; +import java.util.function.Function; +import java.util.logging.Level; +import java.util.logging.Logger; +import java.util.function.Supplier; + +/** + * Functions to get an Optimizer based on String name, an Optimizer class, or lambda function. + * + *

Example: + * + * 

+ *     Adam instance = Optimizers.get(tf, "adam");
+ *     Ftrl instance = Optimizers.get(tf, ltf -> new Ftrl(ltf, 0.1f);
+ *
+ */ +public class Optimizers { + + static Map> map = + new HashMap>() { + { + put("adadelta", tf -> new AdaDelta(tf)); + put("adagrad", tf -> new AdaGrad(tf)); + put("adagrad-da", tf -> new AdaGradDA(tf)); + put("adam", tf -> new Adam(tf)); + put("adamax", tf -> new Adamax(tf)); + put("ftrl", tf -> new Ftrl(tf)); + put("nadam", tf -> new Nadam(tf)); + put("rmsprop", tf -> new RMSProp(tf)); + put("sgd", tf -> new SGD(tf)); + } + }; + + /** + * Get an Optimizer + * + * @param optimizerFunction either a String that identifies the Optimizer, an Optimizer class, or + * an Optimizer object. + * @return the Optimizer object or null if not found. + */ + public static Optimizer get(Ops tf, Object optimizerFunction) { + return get(tf, optimizerFunction, null); + } + + /** + * Get an Initializer + * + * @param si a lamda function + * @return the Intializer object + */ + public static Optimizer get(Ops tf, Function func) { + return func.apply(tf); + } + + /** + * Get an Initializer + * + * @param optimizerFunction + * @param custom_functions a map of Initializer lambdas that will be queried if the Optimizer is + * not found in the standard keys + * @return the Optimizer object + */ + public static Optimizer get( + Ops tf, Object optimizerFunction, Map> custom_functions) { + if (optimizerFunction != null) { + if (optimizerFunction instanceof String) { + String s = + optimizerFunction + .toString(); // do this for Java 8 rather than Pattern Matching for instanceof + Function function = map.get(s); + if (function == null && custom_functions != null) { + function = custom_functions.get(s); + } + return function != null ? function.apply(tf) : null; + } else if (optimizerFunction instanceof Class) { + Class c = (Class) optimizerFunction; // do this for Java 8 rather than Pattern Matching for + // instanceof + try { + Constructor ctor = c.getConstructor(Ops.class); + return (Optimizer) ctor.newInstance(tf); + } catch (NoSuchMethodException + | InstantiationException + | IllegalAccessException + | IllegalArgumentException + | InvocationTargetException ex) { + Logger.getLogger(Optimizers.class.getName()).log(Level.SEVERE, null, ex); + } + } else if (optimizerFunction instanceof Optimizer) { + return (Optimizer) optimizerFunction; + } else if (optimizerFunction instanceof Function) { + return ((Function) optimizerFunction).apply(tf); + } else if (optimizerFunction instanceof Supplier) { + return ((Supplier) optimizerFunction).get(); + } + } else { + return null; + } + + throw new IllegalArgumentException( + "optimizerFunction must be a symbolic name, Optimizer, Function, Supplier or a Class object"); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/RMSProp.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/RMSProp.java new file mode 100644 index 00000000000..c66c6bdd388 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/RMSProp.java @@ -0,0 +1,201 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.Map; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.op.Ops; + +/** RMSProp Optimizer that implements the RMSProp algorithm. */ +public class RMSProp extends org.tensorflow.framework.optimizers.RMSProp + implements OptimizerInterface { + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String DECAY_KEY = "decay"; + public static final String MOMENTUM_KEY = "momentum"; + public static final String EPSILON_KEY = "epsilon"; + public static final String CENTERED_KEY = "centered"; + + public static final float LEARNING_RATE_DEFAULT = 0.001F; + public static final float DECAY_DEFAULT = 0.9F; + public static final float MOMENTUM_DEFAULT = 0.0F; + public static final float EPSILON_DEFAULT = 1e-07F; + public static final boolean CENTERED_DEFAULT = false; + + private Map config = new HashMap<>(); + private float learningRate; + + /** + * Create an RMSProp Optimizer with the following defaults, name="RMSProp", learning_rate=0.001, + * decay=0.9, momentum=0.0, epsilon=1e-07, centered=false + * + * @param tf the TensorFlow Ops + */ + public RMSProp(Ops tf) { + this( + tf, + LEARNING_RATE_DEFAULT, + DECAY_DEFAULT, + MOMENTUM_DEFAULT, + EPSILON_DEFAULT, + CENTERED_DEFAULT); + } + + /** + * Create an RMSProp Optimizer with the following defaults, name="RMSProp", decay=0.9, + * momentum=0.0, epsilon=1e-07, centered=false + * + * @param tf the TensorFlow Ops + * @param learningRate The learning rate. + */ + public RMSProp(Ops tf, float learningRate) { + this(tf, learningRate, DECAY_DEFAULT, MOMENTUM_DEFAULT, EPSILON_DEFAULT, CENTERED_DEFAULT); + } + + /** + * Create an RMSProp Optimizer with the following defaults, decay=0.9, momentum=0.0, + * epsilon=1e-07, centered=false + * + * @param tf the TensorFlow Ops + * @param name prefix for the operations created when applying gradients. Defaults to "RMSProp" + * @param learningRate The learning rate. + */ + public RMSProp(Ops tf, String name, float learningRate) { + this( + tf, name, learningRate, DECAY_DEFAULT, MOMENTUM_DEFAULT, EPSILON_DEFAULT, CENTERED_DEFAULT); + } + + /** + * Create an RMSProp Optimizer + * + * @param tf the TensorFlow Ops + * @param learningRate The learning rate. Defaults to 0.001. + * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9. + * @param momentum hyperparameter that accelerates descent in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + * @param epsilon A small constant for numerical stability. + * @param centered If True, gradients are normalized by the estimated variance of the gradient; if + * False, by the uncentered second moment. + */ + public RMSProp( + Ops tf, float learningRate, float decay, float momentum, float epsilon, boolean centered) { + super(assertGraph(tf), learningRate, decay, momentum, epsilon, centered); + initConfig(learningRate, decay, momentum, epsilon, centered); + } + + /** + * Create an RMSProp Optimizer + * + * @param tf the TensorFlow Ops + * @param name prefix for the operations created when applying gradients. Defaults to "RMSProp" + * @param learningRate The learning rate. Defaults to 0.001. + * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9. + * @param momentum hyperparameter that accelerates descent in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + * @param epsilon A small constant for numerical stability. + * @param centered If True, gradients are normalized by the estimated variance of the gradient; if + * False, by the uncentered second moment. + */ + public RMSProp( + Ops tf, + String name, + float learningRate, + float decay, + float momentum, + float epsilon, + boolean centered) { + super(assertGraph(tf), name, learningRate, decay, momentum, epsilon, centered); + initConfig(learningRate, decay, momentum, epsilon, centered); + } + + /** + * Create a RMSProp Optimizer using a configuration + * + * @param tf the TensorFlow Ops + * @param config a config object to initialize the Optimizer, the config object has keys for + * "name", "learning_rate", "decay", "momentum", "epsilon" and "centered". If a key is missing + * the default value is used. + * @return the RMSProp optimizer + */ + public static RMSProp fromConfig(Ops tf, Map config) { + return create(tf, config); + } + + /** + * Create a RMSProp Optimizer using a configuration + * + * @param tf the TensorFlow Ops + * @param config a config object to initialize the Optimizer, the config object has keys for + * "name", "learning_rate", "decay", "momentum", "epsilon" and "centered". If a key is missing + * the default value is used. + * @return the RMSProp optimizer + */ + public static RMSProp create(Ops tf, Map config) { + + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float decay = (float) config.getOrDefault(DECAY_KEY, DECAY_DEFAULT); + float momentum = (float) config.getOrDefault(MOMENTUM_KEY, MOMENTUM_DEFAULT); + float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT); + boolean centered = (boolean) config.getOrDefault(CENTERED_KEY, CENTERED_DEFAULT); + if (name == null) { + return new RMSProp(tf, learningRate, decay, momentum, epsilon, centered); + } else { + return new RMSProp(tf, name, learningRate, decay, momentum, epsilon, centered); + } + } + + /** + * Initialize the configuration based on which constructor is called. + * + * @param learningRate The learning rate. Defaults to 0.001. + * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9. + * @param momentum hyperparameter that accelerates descent in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + * @param epsilon A small constant for numerical stability. + * @param centered If True, gradients are normalized by the estimated variance of the gradient; if + * False, by the uncentered second moment. + */ + private void initConfig( + float learningRate, float decay, float momentum, float epsilon, boolean centered) { + this.learningRate = learningRate; + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(DECAY_KEY, decay); + config.put(MOMENTUM_KEY, momentum); + config.put(EPSILON_KEY, epsilon); + config.put(CENTERED_KEY, centered); + } + + /** {@inheritDoc} */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/SGD.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/SGD.java new file mode 100644 index 00000000000..2faf777b4ad --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/SGD.java @@ -0,0 +1,199 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the ); +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 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.keras.optimizers; + +import java.util.HashMap; +import java.util.Map; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph; +import org.tensorflow.op.Ops; + +/** Stochastic Gradient Descent and momentum optimizer. */ +public class SGD extends org.tensorflow.framework.optimizers.Momentum + implements OptimizerInterface { + + public static final String LEARNING_RATE_KEY = "learning_rate"; + public static final String MOMENTUM_KEY = "momentum"; + public static final String NESTEROV_KEY = "nesterov"; + + public static final float LEARNING_RATE_DEFAULT = 0.01F; + public static final float MOMENTUM_DEFAULT = 0.0F; + public static final boolean NESTEROV_DEFAULT = false; + + private Map config = new HashMap<>(); + private float learningRate; + + /** + * Create a Stochastic Gradient Descent optimizer using defaults: name="SGD", learning_rate=0.01, + * momentum=0.0, and nesterov=false + * + * @param tf the TensorFlow Ops + */ + public SGD(Ops tf) { + this(tf, LEARNING_RATE_DEFAULT, MOMENTUM_DEFAULT, NESTEROV_DEFAULT); + } + + /** + * Create a Stochastic gradient descent optimizer using defaults: name="SGD", momentum=0.0, and + * nesterov=false + * + * @param tf the TensorFlow Ops + * @param learningRate The learning rate. Defaults to 0.01. + */ + public SGD(Ops tf, float learningRate) { + this(tf, learningRate, MOMENTUM_DEFAULT, NESTEROV_DEFAULT); + } + + /** + * Create a Stochastic gradient descent optimizer using defaults: name="SGD", and nesterov=false + * + * @param tf the TensorFlow Ops + * @param learningRate The learning rate. Defaults to 0.01. + * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + */ + public SGD(Ops tf, float learningRate, float momentum) { + this(tf, learningRate, momentum, NESTEROV_DEFAULT); + } + + /** + * Create a Stochastic gradient descent optimizer using defaults: momentum=0.0, and nesterov=false + * + * @param tf the TensorFlow Ops + * @param name prefix for the operations created when applying gradients + * @param learningRate The learning rate. Defaults to 0.01. + */ + public SGD(Ops tf, String name, float learningRate) { + this(tf, name, learningRate, MOMENTUM_DEFAULT, NESTEROV_DEFAULT); + } + + /** + * create a Stochastic gradient descent optimizer using defaults: momentum=0.0, and nesterov=false + * + * @param tf the TensorFlow Ops + * @param name prefix for the operations created when applying gradients + * @param learningRate The learning rate. Defaults to 0.01. + * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + */ + public SGD(Ops tf, String name, float learningRate, float momentum) { + this(tf, name, learningRate, momentum, NESTEROV_DEFAULT); + } + + /** + * Create a Stochastic gradient descent optimizer + * + * @param tf the TensorFlow Ops + * @param learningRate The learning rate. Defaults to 0.01. + * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + * @param useNesterov Whether to apply Nesterov momentum. Defaults to `false`. + */ + public SGD(Ops tf, float learningRate, float momentum, boolean useNesterov) { + super(assertGraph(tf), learningRate, momentum, useNesterov); + assert momentum >= 0.0F && momentum <= 1.0F : "\"momentum\" must be between [0, 1]."; + initConfig(learningRate, momentum, useNesterov); + } + + /** + * Create a Stochastic gradient descent optimizer + * + * @param tf the TensorFlow Ops + * @param name prefix for the operations created when applying gradients + * @param learningRate The learning rate. Defaults to 0.01. + * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + * @param useNesterov Whether to apply Nesterov momentum. Defaults to `false`. + */ + public SGD(Ops tf, String name, float learningRate, float momentum, boolean useNesterov) { + super(assertGraph(tf), name, learningRate, momentum, useNesterov); + assert momentum >= 0.0F && momentum <= 1.0F : "\"momentum\" must be between [0, 1]."; + initConfig(learningRate, momentum, useNesterov); + } + + /** + * Create a Stochastic gradient descent optimizer + * + * @param tf the TensorFlow Ops + * @param config a config object to initialize, the config object has keys for "name", + * "learning_rate", "momentum", and "nesterov". If a key is missing the default value is used. + * @return the Stochastic gradient descent optimizer + */ + public static SGD fromConfig(Ops tf, Map config) { + return create(tf, config); + } + + /** + * Create a Stochastic gradient descent optimizer + * + * @param tf the TensorFlow Ops + * @param config a config object to initialize, the config object has keys for "name", + * "learning_rate", "momentum", and "nesterov". If a key is missing the default value is used. + * @return the Stochastic gradient descent optimizer + */ + public static SGD create(Ops tf, Map config) { + + String name = (String) config.get(NAME_KEY); + float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + float momentum = (float) config.getOrDefault(MOMENTUM_KEY, MOMENTUM_DEFAULT); + boolean nesterov = (boolean) config.getOrDefault(NESTEROV_KEY, NESTEROV_DEFAULT); + if (name == null) { + return new SGD(tf, learningRate, momentum, nesterov); + } else { + return new SGD(tf, name, learningRate, momentum, nesterov); + } + } + + /** + * Initialize the configuration ased on which constructor is called. + * + * @param learningRate learningRate The learning rate. Defaults to 0.01. + * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens + * oscillations. Must be between [0, 1]. + * @param useNesterov Whether to apply Nesterov momentum. Defaults to `false`. + */ + private void initConfig(float learningRate, float momentum, boolean useNesterov) { + this.learningRate = learningRate; + config.put(NAME_KEY, this.getOptimizerName()); + config.put(LEARNING_RATE_KEY, learningRate); + config.put(MOMENTUM_KEY, momentum); + config.put(NESTEROV_KEY, useNesterov); + } + + /** { @inheritDoc } */ + @Override + public Map getConfig() { + return config; + } + + /** {@inheritDoc} */ + @Override + public float getLearningRate() { + return this.learningRate; + } + + /** {@inheritDoc} */ + @Override + public void setLearningRate(float learningRate) { + this.learningRate = learningRate; + } + + // overide the momentum name to return "SGD" + /** {@inheritDoc} */ + @Override + public String getOptimizerName() { + return "SGD"; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ND.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ND.java new file mode 100644 index 00000000000..f04ed7bcd70 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ND.java @@ -0,0 +1,717 @@ +/* Copyright 2020 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.keras.utils; + +import java.util.Arrays; +import java.util.concurrent.atomic.AtomicBoolean; +import java.util.concurrent.atomic.AtomicInteger; +import java.util.concurrent.atomic.AtomicReference; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.NdArray; +import org.tensorflow.ndarray.NdArrays; +import org.tensorflow.ndarray.Shape; + +// TODO used in the Callbacks, this should be a part of NDArray? +/** NDArray math Utilities */ +public class ND { + + /** + * Returns a string representation of the contents of the specified array. + * + *

The string representation consists of a list of the array's elements, enclosed in square + * brackets ("[]"). Adjacent elements are separated by the characters ", " (a comma followed by a + * space). Elements are converted to strings as by String.valueOf(int). Returns "null" if a is + * null. + * + * @param array the array to convert. + * @return the String representaion of the contents of the specified array + */ + public static String toString(NdArray array) { + if (array == null) return "null"; + StringBuilder sb = new StringBuilder(); + sb.append("["); + AtomicBoolean first = new AtomicBoolean(true); + array + .elements(0) + .forEachIndexed( + (idx, v) -> { + if (!first.get()) { + sb.append(", "); + } else { + first.set(false); + } + Object f = v.getObject(); + if (v.rank() == 0) { + sb.append(f); + } else { + sb.append(toString(v)); + } + }); + sb.append("]"); + return sb.toString(); + } + + /** + * Transforms a flat index into coordinates based on shape. + * + * @param shape the shape + * @param index the index + * @return the coordinates + */ + private static long[] getCoordinates(Shape shape, long index) { + long[] coordinates = new long[shape.numDimensions()]; + + int numDims = shape.numDimensions(); + int i = numDims - 1; + for (; i >= 0; i--) { + long size = shape.size(i); + long mod = index % size; + coordinates[i] = mod; + index -= mod; + } + return coordinates; + } + + /** + * Gets the square root of an array. + * + * @param a the array + * @return the square root of the array. + */ + public static FloatNdArray sqrt(FloatNdArray a) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.sqrt(v.getFloat()), idx); + }); + return result; + } + + /** + * Gets the square of an array. + * + * @param a the array + * @return the square of the array. + */ + public static FloatNdArray square(FloatNdArray a) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(v.getFloat() * v.getFloat(), idx); + }); + return result; + } + + /** + * Adds two arrays + * + * @param a the array + * @param b the array + * @return the resulting array from the add operation + */ + public static FloatNdArray add(FloatNdArray a, FloatNdArray b) { + assert (a.shape().size() == b.shape().size()); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(v.getFloat() + b.getFloat(idx), idx); + }); + return result; + } + + /** + * Adds an array with a scalar value + * + * @param a the array + * @param scalar the scalar value + * @return the resulting array from the add operation + */ + public static FloatNdArray add(FloatNdArray a, float scalar) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(v.getFloat() + scalar, idx); + }); + return result; + } + + /** + * Adds an array with a scalar value + * + * @param scalar the scalar value + * @param a the array + * @return the resulting array from the add operation + */ + public static FloatNdArray add(float scalar, FloatNdArray a) { + return add(a, scalar); + } + + /** + * subtracts one array from the other + * + * @param a the minuend array + * @param b the subtrahend array + * @return the resulting array from the subtraction operation + */ + public static FloatNdArray sub(FloatNdArray a, FloatNdArray b) { + assert (a.shape().size() == b.shape().size()); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(v.getFloat() - b.getFloat(idx), idx); + }); + return result; + } + + /** + * subtracte scalar from an array + * + * @param a the minuend array + * @param scalar the subtrahend value + * @return the resulting array from the subtraction operation + */ + public static FloatNdArray sub(FloatNdArray a, float scalar) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(v.getFloat() - scalar, idx); + }); + return result; + } + + /** + * subtract an array from a scalar + * + * @param scalar the minuend value + * @param a the subtrahend array + * @return the resulting array from the subtraction operation + */ + public static FloatNdArray sub(float scalar, FloatNdArray a) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(scalar - v.getFloat(), idx); + }); + return result; + } + + /** + * Multiply 2 arrays + * + * @param a the first array + * @param b the second array + * @return the resulting array from the muliply operation + */ + public static FloatNdArray mul(FloatNdArray a, FloatNdArray b) { + assert a.shape().equals(b.shape()) + : String.format( + "ValueError: operands do not have same shapes %s %s ", a.shape(), b.shape()); + boolean sameSize = a.shape().size() == b.shape().size(); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + if (sameSize) { + result.setFloat(v.getFloat() * b.getFloat(idx), idx); + } else { + float value = v.getFloat() * b.getFloat(idx[0], 0L); + result.setFloat(value, idx); + } + }); + return result; + } + + /** + * Multiply an array with a scalar value + * + * @param a the array + * @param scalar the scalar value + * @return the resulting array from the Multiply operation + */ + public static FloatNdArray mul(FloatNdArray a, float scalar) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + if (a.shape().isScalar()) { + a.scalars().forEach(f -> result.setFloat(f.getFloat() * scalar)); + } else { + a.scalars().forEachIndexed((idx, f) -> result.setFloat(f.getFloat() * scalar, idx)); + } + + return result; + } + + /** + * Multiply a scalar value with an array + * + * @param scalar the scalar value + * @param a the array + * @return the resulting array from the Multiply operation + */ + public static FloatNdArray mul(float scalar, FloatNdArray a) { + return mul(a, scalar); + } + + /** + * Divide two arrays + * + * @param a the dividend array + * @param b the divisor array + * @return the resulting array from the Divide operation + */ + public static FloatNdArray div(FloatNdArray a, FloatNdArray b) { + assert (a.shape().size() == b.shape().size()); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(v.getFloat() / b.getFloat(idx), idx); + }); + return result; + } + + /** + * Divide an array by a scalar + * + * @param a the dividend array + * @param scalar the scalar divisor + * @return the resulting array from the Divide operation + */ + public static FloatNdArray div(FloatNdArray a, float scalar) { + assert (scalar != 0); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat(v.getFloat() / scalar, idx); + }); + return result; + } + + /** + * Divide a scalar by an array + * + * @param scalar the scalar dividend + * @param a the divisor array + * @return the resulting array from the Divide operation + */ + public static FloatNdArray div(float scalar, FloatNdArray a) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + float value = v.getFloat() == 0.0F ? Float.NaN : scalar / v.getFloat(); + result.setFloat(value, idx); + }); + return result; + } + + /** + * Raise the first array by the power of the second array + * + * @param a the first array + * @param b the second array + * @return the array result of the power operation + */ + public static FloatNdArray pow(FloatNdArray a, FloatNdArray b) { + assert (a.shape().size() == b.shape().size()); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.pow(v.getFloat(), b.getFloat(idx)), idx); + }); + return result; + } + + /** + * Raise the first array by the power of the scalar value + * + * @param a the first array + * @param scalar the scalar value + * @return the array result of the power operation + */ + public static FloatNdArray pow(FloatNdArray a, float scalar) { + assert (scalar != 0); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.pow(v.getFloat(), scalar), idx); + }); + return result; + } + + /** + * Raise the scalar value by the power of the array + * + * @param scalar the scalar value + * @param a the first array + * @return the array result of the power operation + */ + public static FloatNdArray pow(float scalar, FloatNdArray a) { + assert (scalar != 0); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.pow(scalar, v.getFloat()), idx); + }); + return result; + } + + /** + * Flatten an array to 1D + * + * @param a the array to flatten + * @return the flattened array + */ + public static float[] flatten(FloatNdArray a) { + float[] result = new float[(int) a.shape().size()]; + int nDims = a.shape().numDimensions(); + AtomicInteger counter = new AtomicInteger(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result[counter.getAndAdd(1)] = v.getFloat(); + }); + return result; + } + + /** + * Get the maximum value of the array + * + * @param a the array + * @return the maximum value of the array + */ + public static float max(FloatNdArray a) { + AtomicReference maximum = new AtomicReference<>(Float.MIN_VALUE); + a.scalars().forEach(f -> maximum.set(Math.max(maximum.get(), f.getFloat()))); + return maximum.get(); + } + + /** + * Get the minimum value of the array + * + * @param a the array + * @return the minimum value of the array + */ + public static float min(FloatNdArray a) { + AtomicReference minimum = new AtomicReference<>(Float.MAX_VALUE); + a.scalars().forEach(f -> minimum.set(Math.min(minimum.get(), f.getFloat()))); + return minimum.get(); + } + + /** + * Get the maximum value of comparing the arrays + * + * @param a the first array + * @param a the second array + * @return the resulting array with the maximum values between each element of the arrays. + * @throws java.lang.AssertionError if the two arrays are not the same size. + */ + public static FloatNdArray max(FloatNdArray a, FloatNdArray b) { + assert (a.shape().size() == b.shape().size()); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.max(v.getFloat(), b.getFloat(idx)), idx); + }); + return result; + } + + /** + * Get the maximum value of comparing each item of the array to scalar + * + * @param a the array + * @param scalar the scalar value + * @return the resulting array with the maximum values between each element of the array and the + * scalar value + */ + public static FloatNdArray max(FloatNdArray a, float scalar) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.max(v.getFloat(), scalar), idx); + }); + return result; + } + + /** + * Get the maximum value of comparing each item of the array to scalar + * + * @param scalar the scalar value + * @param a the array + * @return the resulting array with the maximum values between each element of the array and the + * scalar value + */ + public static FloatNdArray max(float scalar, FloatNdArray a) { + return max(a, scalar); + } + + /** + * Get the minimum value of comparing the arrays + * + * @param a the first array + * @param a the second array + * @return the resulting array with the minimum values between each element of the arrays. + * @throws java.lang.AssertionError if the two arrays are not the same size. + */ + public static FloatNdArray min(FloatNdArray a, FloatNdArray b) { + assert (a.shape().size() == b.shape().size()); + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.min(v.getFloat(), b.getFloat(idx)), idx); + }); + return result; + } + + /** + * Get the minimum value of comparing each item of the array to scalar + * + * @param a the array + * @param scalar the scalar value + * @return the resulting array with the minimum values between each element of the array and the + * scalar value + */ + public static FloatNdArray min(FloatNdArray a, float scalar) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + int nDims = a.shape().numDimensions(); + a.elements(nDims - 1) + .forEachIndexed( + (idx, v) -> { + result.setFloat((float) Math.min(v.getFloat(), scalar), idx); + }); + return result; + } + + /** + * Get the minimum value of comparing each item of the array to scalar + * + * @param scalar the scalar value + * @param a the array + * @return the resulting array with the minimum values between each element of the array and the + * scalar value + */ + public static FloatNdArray min(float scalar, FloatNdArray a) { + return min(a, scalar); + } + + /** + * Get the absolute value of each member of the array + * + * @param a the array + * @return the array with the absolute value of each item. + */ + public static FloatNdArray abs(FloatNdArray a) { + FloatNdArray result = NdArrays.ofFloats(a.shape()); + a.scalars().forEachIndexed((idx, f) -> result.setFloat((float) Math.abs(f.getFloat()), idx)); + return result; + } + + /** + * Sum all elements of an array + * + * @param a the array + * @return an a array with one element containing the sum. + */ + public static FloatNdArray sum(FloatNdArray a) { + AtomicReference sum = new AtomicReference<>(0.f); + a.scalars().forEach(f -> sum.set(sum.get() + f.getFloat())); + return NdArrays.scalarOf(sum.get()); + } + + /** + * Sum all elements of an array based on the specified axis + * + * @param a the array + * @param axis the axis to sum + * @return an a array the sum over the axis less the diemsnion + */ + public static FloatNdArray sum(FloatNdArray a, int axis) { + return sum(a, axis, false); + } + + /** + * Sum all elements of an array based on the specified axis + * + * @param a the array + * @param axis the axis to sum + * @param keepDims indicates whether the dimensions over the sum should be kept or not. + * @return an a array the sum over the axis + */ + public static FloatNdArray sum(FloatNdArray a, int axis, boolean keepDims) { + Shape shape = a.shape(); + int nDims = shape.numDimensions(); + int xis = nDims - 1 - axis; + long totalSize = shape.size(); + long axisSize = shape.size(xis); + final float[] sums = new float[(int) axisSize]; + + a.scalars() + .forEachIndexed( + (idx, f) -> { + sums[(int) idx[xis]] += f.getFloat(); + }); + + if (keepDims) { + long[] newDims = shape.asArray(); + newDims[axis] = 1; + final AtomicInteger counter = new AtomicInteger(); + FloatNdArray arrayK = NdArrays.ofFloats(Shape.of(newDims)); + arrayK + .elements(newDims.length - 1) + .forEachIndexed( + (idx, v) -> { + v.setFloat(sums[counter.getAndAdd(1)]); + }); + return arrayK; + } else { + return NdArrays.vectorOf(sums); + } + } + + /** + * Sum all elements of an array based on the specified axis + * + * @param a the array + * @param axes the axis to sum + * @param keepDims indicates whether the dimensions over the sum should be kept or not. + * @return an a array the sum over the axis + */ + public static FloatNdArray sum(FloatNdArray a, Integer[] axes, boolean keepDims) { + Shape shape = a.shape(); + if (axes == null) { + FloatNdArray result = sum(a); + if (keepDims) { + float scalar = result.getFloat(0); + long[] dims = {1, 1}; + Shape bShape = Shape.of(dims); + FloatNdArray resultK = NdArrays.ofFloats(bShape); + resultK.setFloat(scalar, 0, 0); + return resultK; + } + return result; + } else if (axes.length == 1) { + return sum(a, axes[0], keepDims); + } else { + // TODO + throw new UnsupportedOperationException("Multi Axis Not implemented Yet"); + } + } + + /** + * Calculate the l2 norm of the array + * + * @param x the array + * @return the l2 norm of the array + */ + public static FloatNdArray l2_norm(FloatNdArray x) { + return l2_norm(x, -1); + } + + /** + * Calculate the l2 norm of the array + * + * @param x the array + * @param axis the axis to calculate over + * @return the l2 norm of the array + */ + public static FloatNdArray l2_norm(FloatNdArray x, int axis) { + float epsilon = 1e-12F; + FloatNdArray square_sum = ND.sum(ND.square(x), axis, true); + FloatNdArray x_inv_norm = ND.div(1, ND.sqrt(ND.max(square_sum, epsilon))); + return ND.mul(x, x_inv_norm); + } + + /** + * Print the array to System.out. + * + * @param a the array + */ + public static void print(FloatNdArray a) { + System.out.println("Shape: " + a.shape()); + if (a.shape().isScalar()) { + a.scalars().forEach(f -> System.out.printf("Scalar: == %f\n", f.getFloat())); + } else { + a.elements(a.shape().numDimensions() - 1) + .forEachIndexed( + (idx, v) -> { + System.out.printf("%s == %f\n", Arrays.toString(idx), v.getFloat()); + }); + } + System.out.println(); + } + + /** + * Print the array to System.out. + * + * @param header a string to print before the print of the array + * @param a the array + */ + public static void print(String header, FloatNdArray a) { + System.out.print(header); + System.out.print(" : "); + + print(a); + } + + /** + * Convert a float array to an NdArray with the provided shape. + * + * @param y the float array + * @param shape the shape for the NdArray + * @return a float array to an NdArray with the provided shape. + */ + public static FloatNdArray create(float[] y, Shape shape) { + FloatNdArray result = NdArrays.ofFloats(shape); + AtomicInteger index = new AtomicInteger(); + result + .elements(shape.numDimensions() - 1) + .forEachIndexed( + (idx, v) -> { + v.setFloat(y[index.getAndAdd(1)]); + }); + return result; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java new file mode 100644 index 00000000000..ef2f20e648a --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java @@ -0,0 +1,81 @@ +/* Copyright 2020 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.keras.utils; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.regex.Matcher; +import java.util.regex.Pattern; + +/** Utility that handles Python style placholder formats, used in Callbacks */ +public class PlaceholderStringFormat { + private static final Pattern PYTHON_MATCH = Pattern.compile("\\{(\\w+):([\\w\\.]+)\\}"); + + /** + * Convert a Python style placeholder file path format to file path + * + * @param filename the placeholder file path format + * @param epoch the epoch number to place into the filename format + * @param logs a Dictionary of log values that are replaced into the filename format + * @return the resulting filename after applying all placeholders. + */ + public static String convertFilePath(String filename, int epoch, Map logs) { + List vars = new ArrayList<>(); + Map valMap = new HashMap<>(); + String format = getFilePath(filename, vars); + List objects = new ArrayList<>(); + vars.forEach( + key -> { + if (key.equals("epoch")) objects.add(epoch); + else objects.add((Number) logs.get(key)); + }); + return String.format(format, objects.toArray(new Number[objects.size()])); + } + + /** + * Get the variable identifiers from the placeholder filename string + * + * @param filename the filename name in Placeholder format. + * @param vars the list of variables from the caller, with added variables parsed from the + * filename + * @return a string in String.format style + */ + private static String getFilePath(String filename, List vars) { + Matcher m = PYTHON_MATCH.matcher(filename); + StringBuilder sb = new StringBuilder(); + int beginIndex = 0; + Map indexMap = new HashMap<>(); + int lastIndex = 1; + while (m.find()) { + int start = m.start(0); + int end = m.end(0); + String variable = m.group(1); + vars.add(variable); + String format = m.group(2); + Integer index = indexMap.get(variable); + if (index == null) { + indexMap.put(variable, lastIndex); + index = lastIndex++; + } + sb.append(filename.substring(beginIndex, start)); + sb.append('%').append(index).append('$').append(format); + beginIndex = end; + } + sb.append(filename.substring(beginIndex)); + return sb.toString(); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java new file mode 100644 index 00000000000..9a21c50893f --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java @@ -0,0 +1,152 @@ +/* Copyright 2020 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.keras.utils; + +import org.tensorflow.DataType; +import org.tensorflow.Tensor; +import org.tensorflow.types.TFloat16; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TFloat64; +import org.tensorflow.types.TInt32; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.TUint8; +import org.tensorflow.types.TBfloat16; +import org.tensorflow.types.TBool; +import org.tensorflow.types.TString; + +/** + * Utility to print Tensor values + */ +public class PrintUtils { + + /** + * Print a tensor's values + * @param tensor the tensor to print + */ + public static void print(Tensor tensor) { + switch(tensor.dataType().name()) { + case "BFLOAT16": + printTBfloat16(tensor); + break; + case "FLOAT16": + printTFloat16(tensor); + break; + case "FLOAT": + printTFloat32(tensor); + break; + case "DOUBLE": + printTFloat64(tensor); + break; + case "INT32": + printTInt32(tensor); + break; + case "INT64": + printTInt64(tensor); + break; + case "UINT8": + printTUint8(tensor); + break; + case "BOOL": + printTBool(tensor); + break; + case "STRING": + printTString(tensor); + break; + default: + break; + } + + } + + /** + * Print a boolean Tensot + * @param t the tensor to print + */ + public static void printTBool(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(s.getBoolean() + ", ")); + System.out.println(); + } + + /** + * Print a String Tensot + * @param t the tensor to print + */ + public static void printTString(Tensor t) { + t.data().scalars().forEach(s -> System.out.print("\"" + s.getObject() + "\", ")); + System.out.println(); + } + + /** + * Print a TBfloat16 Tensor + * @param t the tensor to print + */ + public static void printTBfloat16(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(s.getFloat() + ", ")); + System.out.println(); + } + + /** + * Print a uint8 Tensor + * @param t the tensor to print + */ + public static void printTUint8(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(String.format("0x%x",s.getByte()) + ", ")); + System.out.println(); + } + + /** + * Print an int32 Tensor + * @param t the tensor to print + */ + public static void printTInt32(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(s.getInt() + ", ")); + System.out.println(); + } + + /** + * Print an int64 Tensor + * @param t the tensor to print + */ + public static void printTInt64(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(s.getLong() + ", ")); + System.out.println(); + } + + /** + * Print a Float16 tensor. + * @param t the tensor to print + */ + public static void printTFloat16(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(s.getFloat() + "F, ")); + System.out.println(); + } + + /** + * Print a Float32 tensor. + * @param t the tensor to print + */ + public static void printTFloat32(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(s.getFloat() + "F, ")); + System.out.println(); + } + /** + * Print a Float64 tensor. + * @param t the tensor to print + */ + public static void printTFloat64(Tensor t) { + t.data().scalars().forEach(s -> System.out.print(s.getDouble() + ", ")); + System.out.println(); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java new file mode 100644 index 00000000000..9dd3de4e1a2 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java @@ -0,0 +1,311 @@ +/* Copyright 2020 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.keras.utils; + +import java.io.Console; +import java.util.ArrayList; +import java.util.Collections; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Map.Entry; + +/** + * Display a progess bar either to the Console or System.out. + * + * @author jbclarke + */ +public class ProgressBar { + private final static double MICRO_SECONDS = 1E-3; + private final static long MILLI_SECOND = 1l; + private final static long SECOND = 1000L; + private final static long MINUTE = 60L * SECOND; + private final static long HOUR = 60L * MINUTE; + + private Integer target; + private int width; + private boolean verbose; + private long interval; + private List statefulMetrics; + private String unit; + + private int totalWidth; + private int seenSoFar; + private final Map values = new HashMap<>(); + private final List valuesOrder = new ArrayList<>(); + + private final long start = System.currentTimeMillis(); + private long lastUpdate = 0; + + // will be null if console is not present + private final Console console = System.console(); + + /** + * Create a ProgressBar + */ + public ProgressBar() { + this(null, 30, true, 50, "step", null ); + + } + + /** + * Create a ProgressBar + * + * @param target Total number of steps expected, null if unknown. + */ + public ProgressBar(Integer target) { + this(target, 30, true, 50, "step", null ); + + } + + /** + * Create a ProgressBar + * + * @param target Total number of steps expected, null if unknown. + * @param verbose Verbosity mode + * @param unit Display name for step counts (usually "step" or "sample"). + * @param statefulMetrics + */ + public ProgressBar(Integer target, boolean verbose, String unit, List statefulMetrics) { + this(target, 30, verbose, 50, unit, statefulMetrics ); + + } + + + + /** + * Create a ProgressBar + * + * @param target Total number of steps expected, null if unknown. + * @param width Progress bar width on screen. + * @param verbose Verbosity mode + * @param interval Minimum visual progress update interval (in milliseconds). + * @param unit Display name for step counts (usually "step" or "sample"). + * @param statefulMetrics + */ + public ProgressBar(Integer target, int width, boolean verbose, long interval, String unit, List statefulMetrics) { + this.target = target; + this.width = width; + this.verbose = verbose; + this.interval = interval; + this.unit = unit; + this.statefulMetrics = statefulMetrics == null ? Collections.EMPTY_LIST : statefulMetrics; + } + + /** + * Updates the progress bar. + * + * @param current Index of current step. + * @param values List of Pairs: `(name, value_for_last_step)`. If `name` is in + * `statefulMetrics`, `value_for_last_step` will be displayed as-is. + * Else, an average of the metric over time will be displayed. + */ + public void update(Integer current, List> values) { + update(current, values, null); + } + + /** + * Updates the progress bar. + * + * @param current Index of current step. + * @param values List of Entry: `(name, value_for_last_step)`. If `name` is in + * `statefulMetrics`, `value_for_last_step` will be displayed as-is. + * Else, an average of the metric over time will be displayed. + * @param finalize Whether this is the last update for the progress bar. If + * `None`, defaults to `current >= self.target`. + */ + public void update(Integer current, List> values, Boolean finalize) { + if(finalize == null) { + if(this.getTarget() == null) { + finalize = false; + }else { + finalize = current >= this.getTarget(); + } + } + values = values == null ? Collections.EMPTY_LIST : values; + + values.forEach(e -> { + if(!this.valuesOrder.contains(e.getKey())) { + this.valuesOrder.add(e.getKey()); + } + if(!this.statefulMetrics.contains(e.getKey())) { + int valueBase = Math.max(current - this.seenSoFar, 1); + if(!this.values.containsKey(e.getKey())) { + this.values.put(e.getKey(), new Number[] { e.getValue().doubleValue() * valueBase, valueBase}); + }else { + Number[] n = this.values.get(e.getKey()); + n[0] = n[0].doubleValue() + e.getValue().doubleValue() * valueBase; + n[1] = n[1].doubleValue() + valueBase; + } + }else { + this.values.put(e.getKey(),new Number[] { e.getValue().doubleValue(), 1}); + } + + }); + + this.seenSoFar = current; + long now = System.currentTimeMillis(); + + StringBuilder info = new StringBuilder(String.format(" - %.0fs", (double)(now - this.start)/(double)SECOND)); + + if(this.verbose) { + if(now - this.lastUpdate < this.interval && !finalize) { + return; + } + } + int prevTotalWidth = this.totalWidth; + if (this.console != null) { + for(int i = 0; i < prevTotalWidth; i++) { + this.console.printf("\b"); + } + this.console.printf("\r"); + } else { + System.out.println(); + } + StringBuilder bar = new StringBuilder(); + if(this.getTarget() != null) { + int numDigits = (int)Math.log10(this.getTarget()) + 1; + bar.append(String.format("%" + numDigits + "d/%d [", current, this.getTarget())); + double prog = (double)current / this.getTarget(); + int progWidth = (int)(this.width * prog); + if(progWidth >= 0) { + for(int i = 0; i < progWidth-1; i++) + bar.append('='); + if(current < this.getTarget()) + bar.append('>'); + else + bar.append('='); + for(int i = 0; i < this.width - progWidth; i++) + bar.append('.'); + bar.append(']'); + } + }else { + bar.append(String.format("%7d/Unknown", current)); + } + this.totalWidth = bar.length(); + if(this.console != null) { + this.console.printf(bar.toString()); + }else { + System.out.print(bar.toString()); + } + // in millis + double timePerUnit = current != null ? (double)(now - this.start) / current: 0.0; + if(this.getTarget() == null || finalize) { + if(timePerUnit >= SECOND || timePerUnit == 0.0) { // seconds + info.append(String.format(" %.0fs/%s", timePerUnit/SECOND, this.unit)); + }else if(timePerUnit >= 1) { // milliseconds + info.append(String.format(" %.0fms/%s", timePerUnit, this.unit)); + }else { // microseconds + info.append(String.format(" %.0fus/%s", timePerUnit*SECOND, this.unit)); + } + }else { + double eta = timePerUnit * (this.getTarget() - current); + String etaFormat; + if(eta >= HOUR) { // greater than an hour + etaFormat = String.format("%d:%02d:%02d", // hh:mm:ss + (int) (eta / HOUR), + (int) (eta / HOUR / MINUTE), + (int) (eta % MINUTE)/SECOND); + }else if(eta >= MINUTE) { + etaFormat = String.format("%d:%02d", // mm:ss + (int) (eta / MINUTE), + (int) (eta % MINUTE)/SECOND); + }else { + etaFormat = String.format("%ds", (int)(eta/SECOND)); + } + info.append(" - ETA: ").append(etaFormat); + } + + this.valuesOrder.forEach(key -> { + info.append(String.format(" - %s:", key)); + Number[] val = this.values.get(key); + double avg = val[0].doubleValue() / Math.max(1.0, val[1].doubleValue()); + if(Math.abs(avg) > 1e-3) + info.append(String.format(" %.4f", avg)); + else + info.append(String.format(" %.4e", avg)); + }); + this.totalWidth += info.length(); + if(prevTotalWidth > this.totalWidth) + for(int i = 0; i < prevTotalWidth - this.totalWidth; i++) + info.append(' '); + if(finalize) { + info.append('\n'); + } + + if(this.console != null) { + console.printf(info.toString()); + console.flush(); + }else { + System.out.print(info.toString()); + System.out.flush(); + } + this.lastUpdate = now; + } + + /** + * updates the progress bar by one unit + */ + public void increment() { + add(1); + } + + /** + * updates the progress bar by one unit + * + * @param values List of Entry: `(name, value_for_last_step)`. If `name` is in + * `statefulMetrics`, `value_for_last_step` will be displayed as-is. + * Else, an average of the metric over time will be displayed. + */ + public void increment(List> values) { + add(1, values); + } + + /** + * update the progress bar + * + * @param n the number of units to add to the current number + */ + public void add(int n) { + add(n, null); + } + + /** + * update the progress bar + * + * @param n the number of units to add to the current number + * @param values List of Entry: `(name, value_for_last_step)`. If `name` is in + * `statefulMetrics`, `value_for_last_step` will be displayed as-is. + * Else, an average of the metric over time will be displayed. + */ + public void add(int n, List> values) { + this.update(this.seenSoFar + n, values); + } + + /** + * @return the target + */ + public Integer getTarget() { + return target; + } + + /** + * @param target the target to set + */ + public void setTarget(Integer target) { + this.target = target; + } +} + diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java new file mode 100644 index 00000000000..4fa69d0e537 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java @@ -0,0 +1,110 @@ +/* Copyright 2020 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.keras.utils; + +import java.util.ArrayList; +import java.util.List; +import org.tensorflow.Operand; +import org.tensorflow.Tensor; +import org.tensorflow.ndarray.NdArray; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.types.TInt64; + +/** + * + * @author Jim Clarke + */ +public class ShapeUtils { + + /** + * Convert shape operand back to a Shape object + * + * @param dims the Operand containing the shape values + * @return + */ + public static Shape getShape(Operand dims) { + // TODO is there a better way? + final List dimList = new ArrayList<>(); + dims.data().scalars().forEach(s -> dimList.add(s.getLong())); + long[] longDims = new long[dimList.size()]; + for (int i = 0; i < dimList.size(); i++) { + longDims[i] = dimList.get(i); + } + return Shape.of(longDims); + } + + /** + * get the shape for the data within a Tensor + * + * @param tensor the tensor + * @return the Shape of the tensor's data; + */ + public static Shape getShape(Tensor tensor) { + NdArray data = (NdArray) tensor.data(); + return data.shape(); + + } + + public static boolean isCompatibleWith(Shape a, Shape b) { + if (!isUnknownShape(a) && !isUnknownShape(b)) { + if (a.numDimensions() != b.numDimensions()) { + return false; + } + for (int i = 0; i < a.numDimensions(); i++) { + if (a.size(i) != Shape.UNKNOWN_SIZE + && b.size(i) != Shape.UNKNOWN_SIZE + && b.size(i) != a.size(i)) { + return false; + } + } + } + return true; + } + + public static boolean isUnknownShape(Shape a) { + return a.size() == 0; + } + + /** + * Reshapes the shape by eliminating trailing Dimensions. + * + * @param oldShape + * @param axis + * @return the new shape + */ + public static Shape squeeze(Shape oldShape, int axis) { + axis %= oldShape.numDimensions(); + if (axis < 0) { + axis = oldShape.numDimensions() + axis; + } + long[] array = oldShape.asArray(); + long[] newArray = new long[axis]; + for (int i = 0; i < axis - 1; i++) { + newArray[i] = array[i]; + } + long sum = array[axis - 1]; + for (int i = axis; i < array.length; i++) { + sum *= array[i]; + } + newArray[axis - 1] = sum; + return Shape.of(newArray); + } + + public static boolean isCompatible(long dim, long otherDim) { + return dim == Shape.UNKNOWN_SIZE + || otherDim == Shape.UNKNOWN_SIZE + || dim == otherDim; + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java new file mode 100644 index 00000000000..3dff11c513e --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java @@ -0,0 +1,107 @@ +/* Copyright 2020 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.keras.utils; + +import java.util.function.Supplier; +import org.tensorflow.Operand; +import org.tensorflow.op.Ops; +import org.tensorflow.types.TBool; + +/** Implements a select Operation using Lambdas */ +public class SmartCond { + + /** + * Creates a select operation + * + * @param pred the predicate (boolean) used to select + * @param then_fn the function to execute if the predicate is true + * @param else_fn the function to execute if the predicate is false + * @return the result of the select on the condition + */ + public static Operand select(Boolean pred, Supplier then_fn, Supplier else_fn) { + assert pred != null : "pred must not be null"; + assert then_fn != null : "then_fn must not be null"; + assert else_fn != null : "else_fn must not be null"; + return pred ? then_fn.get() : else_fn.get(); + } + + /** + * Creates a select operation + * + * @param pred the predicate ( true == 1) used to select + * @param then_fn the function to execute if the predicate is true + * @param else_fn the function to execute if the predicate is false + * @return the result of the select on the condition + */ + public static Operand select(Number pred, Supplier then_fn, Supplier else_fn) { + assert pred != null : "pred must not be null"; + assert then_fn != null : "then_fn must not be null"; + assert else_fn != null : "else_fn must not be null"; + return pred.intValue() == 1 ? then_fn.get() : else_fn.get(); + } + + /** + * Creates a select operation + * + * @param pred the predicate ( true if the string argument is not null and is equal, ignoring + * case, to the string "true") used to select + * @param then_fn the function to execute if the predicate is true + * @param else_fn the function to execute if the predicate is false + * @return the result of the select on the condition + */ + public static Operand select(String pred, Supplier then_fn, Supplier else_fn) { + assert pred != null : "pred must not be null"; + assert then_fn != null : "then_fn must not be null"; + assert else_fn != null : "else_fn must not be null"; + return Boolean.valueOf(pred) ? then_fn.get() : else_fn.get(); + } + + /** + * Create a Select operation + * + * @param tf the tensorFlow Ops + * @param pred the operand that evaluates to true or false + * @param then_fn the function to execute if the predicate is true + * @param else_fn the function to execute if the predicate is false + * @return a Select Operation if in graph mode, else return the result of the select + */ + public static Operand select( + Ops tf, Operand pred, Supplier then_fn, Supplier else_fn) { + assert pred != null : "pred must not be null"; + assert then_fn != null : "then_fn must not be null"; + assert else_fn != null : "else_fn must not be null"; + if (tf.scope().env().isEager()) { + return pred.asOutput().data().getBoolean() ? then_fn.get() : else_fn.get(); + } else { // TODO, maybe some day handle Supplier in the c interface + return tf.select(pred, then_fn.get(), else_fn.get()); + } + } + + /** + * Creates a slect operation + * + * @param tf the tensorFlow Ops + * @param pred the operand that evaluates to true or false + * @param then_fn the function to execute if the predicate is true + * @param else_fn the function to execute if the predicate is false + * @return the Select opertion + */ + public static Operand select(Ops tf, Operand pred, Operand true_op, Operand false_op) { + assert pred != null : "pred must not be null"; + assert true_op != null : "true_op must not be null"; + assert false_op != null : "false_op must not be null"; + return tf.select(pred, true_op, false_op); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java new file mode 100644 index 00000000000..b2e63fe1cff --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java @@ -0,0 +1,92 @@ +/* Copyright 2020 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.keras.utils; + +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; +import org.tensorflow.Operand; + +/** + * Utility class that handles sybmolic shapes so that the shapes can be resolved during runtime and + * stay consistent across operands. + * + *

The same symbols accros variaous shapes should have the same dimension values. + * + *

shape1 = Shape("N","L") + * + *

shape2 = Shape("L", "T") + * + *

For exmple, for Symbol "L" + * shape1.size(2) == shape2.size(1) + * + *

Example: + * + * 

+ * List symbols = new ArrayList<>(); symbols.add(new SymbolicShape(yTrue, "N", "L"));
+ * if (this.isMultiLabel()) { symbols.add(new SymbolicShape(this.truePositives, "T", "L"));
+ * symbols.add(new SymbolicShape(this.falsePositives, "T", "L")); symbols.add(new
+ * SymbolicShape(this.trueNegatives, "T", "L")); symbols.add(new SymbolicShape(this.falseNegatives,
+ * "T", "L")); } if (this.getLabelWeights() != null) { symbols.add(new
+ * SymbolicShape(this.getLabelWeights(), "L", "")); }
+ * updateOperations.addAll(Metrics.assert_shapes(tf, symbols, "Number of labels is not
+ * consistent."));
+ *
+ */ +public class SymbolicShape { + + private Operand operand; + private List symbols = new ArrayList<>(); + + /** + * Create a SymbolicShape for an Operand. + * + * @param operand the Operand + * @param symbols the symbols + */ + public SymbolicShape(Operand operand, String... symbols) { + this.operand = operand; + this.symbols.addAll(Arrays.asList(symbols)); + } + + /** @return the operand */ + public Operand getOperand() { + return operand; + } + + /** @param operand the operand to set */ + public void setOperand(Operand operand) { + this.operand = operand; + } + + /** @return the symbols */ + public List getSymbols() { + return symbols; + } + + /** @param symbols the symbols to set */ + public void setSymbols(List symbols) { + this.symbols = symbols; + } + + /** + * Get the rank of the symbol list + * + * @return the rank of the symbol list + */ + public int rank() { + return this.symbols.size(); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java new file mode 100644 index 00000000000..e7c9acf1c5e --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java @@ -0,0 +1,58 @@ +/* Copyright 2020 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.keras.utils; + +import java.util.HashMap; +import java.util.Map; + +/** + * Utility class that contains a dictionary of Symbols. The map is updated with symbols and their + * dimension values. Used in creating matching shapes that depend on other shapes' dimensions. + */ +public class SymbolicShapeDict { + + /** Dictionary containing the sybmols and their associated dimensions sizes. */ + private final Map map = new HashMap<>(); + + /** + * Add a symbol with its associated dimensions size. + * + * @param symbol the symbol name + * @param size the shape dimension to associate with the symbol + */ + public void put(String symbol, Long size) { + this.map.put(symbol, size); + } + + /** + * Get the dimention size for a symbol + * + * @param symbol the symbol name + * @return the dimension size for the symbol or null if not found. + */ + public Long get(String symbol) { + return this.map.get(symbol); + } + + /** + * Determine if the symbol is contained in the dictionary. + * + * @param symbol the symbol name + * @return true, if the dictionary contains the symbol. + */ + public boolean contains(String symbol) { + return map.containsKey(symbol); + } +} diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java new file mode 100644 index 00000000000..a2629ef07b1 --- /dev/null +++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java @@ -0,0 +1,98 @@ +/* Copyright 2020 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.keras.utils; + +import org.tensorflow.DataType; +import org.tensorflow.types.TBfloat16; +import org.tensorflow.types.TBool; +import org.tensorflow.types.TFloat16; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TFloat64; +import org.tensorflow.types.TInt32; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.TString; +import org.tensorflow.types.TUint8; + + +/** + * + * @author Jim Clarke + */ +public class TypeUtils { + + //TODO + public static boolean isComplex(DataType dtype) { + return false; + } + + public static boolean isFloating(DataType dtype) { + switch(dtype.name()) { + case "BFLOAT16": + case "FLOAT16": + case "FLOAT": + case "DOUBLE": + return true; + default: return false; + } + } + public static boolean isInteger(DataType dtype) { + switch(dtype.name()) { + case "INT32": + case "INT64": + case "UINT8": + return true; + default: return false; + } + } + + public static boolean isNumeric(DataType dtype) { + return isFloating(dtype) || isInteger(dtype); + } + + public static boolean isBoolean(DataType dtype) { + return dtype.name().equals("BOOL"); + } + + public static boolean isString(DataType dtype) { + return dtype.name().equals("STRING"); + } + + public static DataType of(String name) { + switch(name) { + case "BFLOAT16": + return TBfloat16.DTYPE; + case "FLOAT16": + return TFloat16.DTYPE; + case "FLOAT": + return TFloat32.DTYPE; + case "DOUBLE": + return TFloat64.DTYPE; + case "UINT8": + return TUint8.DTYPE; + case "INT32": + return TInt32.DTYPE; + case "INT64": + return TInt64.DTYPE; + case "BOOL": + return TBool.DTYPE; + case "STRING": + return TString.DTYPE; + default: + throw new IllegalArgumentException(String.format("%s is an unknown DataType", name)); + + } + } + +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java new file mode 100644 index 00000000000..8a7c8af9fae --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java @@ -0,0 +1,226 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import static org.tensorflow.framework.optimizers.AdaDelta.ACCUMULATOR; +import static org.tensorflow.framework.optimizers.AdaDelta.ACCUMULATOR_UPDATE; +import org.tensorflow.framework.optimizers.Optimizer.GradAndVar; +import static org.tensorflow.keras.optimizers.AdaDelta.EPSILON_DEFAULT; +import static org.tensorflow.keras.optimizers.AdaDelta.EPSILON_KEY; +import static org.tensorflow.keras.optimizers.AdaDelta.LEARNING_RATE_DEFAULT; +import static org.tensorflow.keras.optimizers.AdaDelta.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.AdaDelta.RHO_DEFAULT; +import static org.tensorflow.keras.optimizers.AdaDelta.RHO_RATE_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for AdaDelta Optimizer */ +public class AdaDeltaTest { + + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + + private int index; + + public AdaDeltaTest() { + } + + @BeforeAll + public static void setUpClass() { + } + + @AfterAll + public static void tearDownClass() { + } + + @BeforeEach + public void setUp() { + } + + @AfterEach + public void tearDown() { + } + + /** + * Test of create method, of class AdaDelta. + */ + @Test + public void testCreate() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "AdaDelta"); + config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + config.put(RHO_RATE_KEY, RHO_DEFAULT); + config.put(EPSILON_KEY, EPSILON_DEFAULT); + AdaDelta expResult = new AdaDelta(tf); + AdaDelta result = AdaDelta.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + @Test + public void testConstructAdadeltaWithLR() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + AdaDelta opt = new AdaDelta(tf, 1.0F, 0.9F, 1.F); + AdaDelta opt2 = new AdaDelta(tf, 0.1F, 0.9F, 1.F); + AdaDelta opt3 = new AdaDelta(tf, 0.1F, 0.9F, 1e-8F); + String format = "AdaDelta{learningRate=%s, rho=%s, epsilon=%s}"; + String optExpected = String.format(format, 1.0F, 0.9F, 1.F); + String opt2Expected = String.format(format, 0.1F, 0.9F, 1.F); + String opt3Expected = String.format(format, 0.1F, 0.9F, 1e-8F); + + String optString = opt.toString(); + String opt2String = opt2.toString(); + String opt3String = opt3.toString(); + + assertEquals(optExpected, optString); + assertEquals(opt2Expected, opt2String); + assertEquals(opt3Expected, opt3String); + } + + } + + @Test + public void testConstructAdadeltaWithEpsilonValues() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + AdaDelta opt = new AdaDelta(tf); + Map config = opt.getConfig(); + assertEquals(EPSILON_DEFAULT, (float) config.get(EPSILON_KEY)); + + opt = new AdaDelta(tf, LEARNING_RATE_DEFAULT, RHO_DEFAULT, 1e-8F); + config = opt.getConfig(); + assertEquals(1e-8F, (float) config.get(EPSILON_KEY)); + } + } + + @Test + public void testBasic() { + int num_updates = 4; // # number of ADADELTA steps to perform + float[] grads = {0.2F, 0.1F, 0.01F}; + float[] lrs = {1.0F, 0.5F, 0.1F}; + for (float grad : grads) { + for (float lr : lrs) { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] fgrads = {grad, grad}; + Shape shape = Shape.of(var0_init.length); + Variable var0 = tf.withName("var0").variable(shape, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant cgrads = tf.constant(fgrads); + + float accum = 0.0F; + float accum_update = 0.0F; + float rho = 0.95F; + float epsilon = 1e-8F; + float epsilon1 = 1e-5F; + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new GradAndVar<>(cgrads.asOutput(), var0.asOutput())); + gradsAndVars.add(new GradAndVar<>(cgrads.asOutput(), var1.asOutput())); + + /* get the Optimizer */ + AdaDelta adaDelta = new AdaDelta(tf, lr, rho, epsilon); + + /** + * apply gradients + */ + Op adadelta_update = adaDelta.applyGradients(gradsAndVars, "AdaDeltaTest"); + + /* Create and validae the shapes of the slota */ + Variable[] slots = new Variable[2]; + Variable[] slotUpdates = new Variable[2]; + + slots[0] = adaDelta.getSlot(var0.asOutput(), ACCUMULATOR).get(); + assertEquals(slots[0].asOutput().shape(), var0.asOutput().shape()); + + slotUpdates[0] = adaDelta.getSlot(var0.asOutput(), ACCUMULATOR_UPDATE).get(); + assertEquals(slotUpdates[0].asOutput().shape(), var0.asOutput().shape()); + + slots[1] = adaDelta.getSlot(var1.asOutput(), ACCUMULATOR).get(); + assertEquals(slots[1].asOutput().shape(), var1.asOutput().shape()); + + slotUpdates[1] = adaDelta.getSlot(var1.asOutput(), ACCUMULATOR_UPDATE).get(); + assertEquals(slotUpdates[1].asOutput().shape(), var1.asOutput().shape()); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** + * initialize the accumulators + */ + session.run(tf.init()); + + /** + * make sure the variables were initialized properly + */ + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + float[] updates = new float[num_updates]; + float tot_update = 0; + for (int step = 0; step < num_updates; step++) { + session.run(adadelta_update); + accum = accum * rho + (float) Math.pow(grad, 2) * (1.0F - rho); + updates[step] = ((float) Math.sqrt(accum_update + epsilon) + * (float) (1 / Math.sqrt(accum + epsilon)) * grad); + accum_update = (accum_update * rho + ((float) Math.pow(updates[step], 2) * (1.0F - rho))); + tot_update += updates[step] * lr; + + for (int i = 0; i < 2; i++) { + session.evaluate(accum, slots[i]); + session.evaluate(accum_update, slotUpdates[i]); + } + + Float[] var0_initUpdate = {var0_init[0] - tot_update, var0_init[1] - tot_update}; + Float[] var1_initUpdate = {var1_init[0] - tot_update, var1_init[1] - tot_update}; + + session.evaluate(var0_initUpdate, var0); + session.evaluate(var1_initUpdate, var1); + + } + + } + } + } + } + +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java new file mode 100644 index 00000000000..3931db4da97 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java @@ -0,0 +1,126 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.keras.optimizers.AdaGradDA.INITIAL_ACCUM_KEY; +import static org.tensorflow.keras.optimizers.AdaGradDA.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for AdaGradDA Optimizer */ +public class AdaGradDATest { + + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + + int index; + + public AdaGradDATest() {} + + @BeforeAll + public static void setUpClass() {} + + @AfterAll + public static void tearDownClass() {} + + @BeforeEach + public void setUp() {} + + @AfterEach + public void tearDown() {} + + /** Test of create method, of class AdaGradDA. */ + @Test + public void testCreate() { + try (TestSession testSession = TestSession.createTestSession(tf_mode)) { + Ops tf = testSession.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "AdaDelta"); + config.put(LEARNING_RATE_KEY, 2.0F); + config.put(INITIAL_ACCUM_KEY, 0.1F); + AdaGradDA expResult = new AdaGradDA(tf, 2.0F, 0.1F, 0.0F, 0.0F); + AdaGradDA result = AdaGradDA.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + @Test + public void testBasic() { + float[] var0_init = {0.0F, 0.0F}; + float[] var1_init = {0.0F, 0.0F}; + float[] grads0_init = {0.1F, 0.2F}; + float[] grads1_init = {0.01F, 0.02F}; + float epsilon = 1e-8F; + float epsilon1 = 1e-5F; + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + /* initialize the local variables */ + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + float learningRate = 3.0F; + + AdaGrad instance = new AdaGrad(tf, learningRate); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op ada_update = instance.applyGradients(gradsAndVars, "AdGradDATest"); + + /** initialize the accumulators */ + session.run(tf.init()); + + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + session.run(ada_update); + float[] expected0 = {-0.904534F, -1.603567F}; + session.evaluate(expected0, var0); + float[] expected1 = {-0.094821f, -0.189358f}; + session.evaluate(expected1, var1); + } + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java new file mode 100644 index 00000000000..28c45c4c8c3 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java @@ -0,0 +1,170 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import static org.tensorflow.framework.optimizers.AdaGrad.ACCUMULATOR; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.keras.optimizers.AdaGrad.INITIAL_ACCUM_KEY; +import static org.tensorflow.keras.optimizers.AdaGrad.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import org.tensorflow.keras.utils.ND; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.NdArrays; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for AdaGrad Optimizer */ +public class AdaGradTest { + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + int index; + + public AdaGradTest() {} + + @BeforeAll + public static void setUpClass() {} + + @AfterAll + public static void tearDownClass() {} + + @BeforeEach + public void setUp() {} + + @AfterEach + public void tearDown() {} + + /** Test of create method, of class AdaGrad. */ + @Test + public void testCreate() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "AdaDelta"); + config.put(LEARNING_RATE_KEY, 2.0F); + config.put(INITIAL_ACCUM_KEY, 0.1F); + AdaGrad expResult = new AdaGrad(tf, 2.0F, 0.1F); + AdaGrad result = AdaGrad.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + @Test + public void testBasic() { + int numSteps = 3; + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] grads0_init = {0.1F, 0.1F}; + float[] grads1_init = {0.01F, 0.01F}; + float epsilon = 1e-8F; + float epsilon1 = 1e-5F; + float[] accum0 = {0.1f, 0.1f}; + float[] accum1 = {0.1f, 0.1f}; + + FloatNdArray var0_np = NdArrays.vectorOf(var0_init); + FloatNdArray var1_np = NdArrays.vectorOf(var1_init); + FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init); + FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init); + FloatNdArray accum0_np = NdArrays.vectorOf(accum0); + FloatNdArray accum1_np = NdArrays.vectorOf(accum1); + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + float learningRate = 3.0F; + + AdaGrad instance = new AdaGrad(tf, learningRate); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op ada_update = instance.applyGradients(gradsAndVars, "AdGradTest"); + + Variable[] accumulatorSlots = new Variable[2]; + accumulatorSlots[0] = instance.getSlot(var0.asOutput(), ACCUMULATOR).get(); + assertEquals(accumulatorSlots[0].asOutput().shape(), var0.asOutput().shape()); + + accumulatorSlots[1] = instance.getSlot(var1.asOutput(), ACCUMULATOR).get(); + assertEquals(accumulatorSlots[1].asOutput().shape(), var1.asOutput().shape()); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + /** make sure the variables were initialized properly */ + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + for (int step = 0; step < numSteps; step++) { + session.run(ada_update); + + accum0_np = caclulateAccum(accum0_np, grads0_np); + var0_np = calculate(var0_np, accum0_np, grads0_np, learningRate); + session.evaluate(var0_np, var0); + + accum1_np = caclulateAccum(accum1_np, grads1_np); + var1_np = calculate(var1_np, accum1_np, grads1_np, learningRate); + session.evaluate(var1_np, var1); + } + } + } + + private FloatNdArray caclulateAccum(FloatNdArray accum, FloatNdArray grads) { + // accum + g_t * g_t + FloatNdArray squareG = ND.square(grads); + FloatNdArray result = ND.add(accum, squareG); + return result; + } + + private FloatNdArray calculate( + FloatNdArray param, FloatNdArray accum, FloatNdArray grads, float learningRate) { + // param - lr * g_t / (np.sqrt(accum_t) + epsilon) + FloatNdArray divisor = ND.add(ND.sqrt(accum), 1e-07f); + FloatNdArray dividend = ND.mul(learningRate, grads); + FloatNdArray quotient = ND.div(dividend, divisor); + FloatNdArray result = ND.sub(param, quotient); + return result; + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java new file mode 100644 index 00000000000..6f1d13d83d6 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java @@ -0,0 +1,263 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.Tensor; +import static org.tensorflow.framework.optimizers.Adam.FIRST_MOMENT; +import static org.tensorflow.framework.optimizers.Adam.SECOND_MOMENT; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.keras.optimizers.Adam.BETA_ONE_DEFAULT; +import static org.tensorflow.keras.optimizers.Adam.BETA_ONE_KEY; +import static org.tensorflow.keras.optimizers.Adam.BETA_TWO_DEFAULT; +import static org.tensorflow.keras.optimizers.Adam.BETA_TWO_KEY; +import static org.tensorflow.keras.optimizers.Adam.EPSILON_DEFAULT; +import static org.tensorflow.keras.optimizers.Adam.EPSILON_KEY; +import static org.tensorflow.keras.optimizers.Adam.LEARNING_RATE_DEFAULT; +import static org.tensorflow.keras.optimizers.Adam.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import org.tensorflow.keras.utils.ND; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.NdArrays; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for Adam Optimizer */ +public class AdamTest { + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + + int index; + + public AdamTest() {} + + @BeforeAll + public static void setUpClass() {} + + @AfterAll + public static void tearDownClass() {} + + @BeforeEach + public void setUp() {} + + @AfterEach + public void tearDown() {} + + /** Test of create method, of class Adam. */ + @Test + public void testCreate() { + try (TestSession testSession = TestSession.createTestSession(tf_mode)) { + Ops tf = testSession.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "AdaDelta"); + config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + config.put(BETA_ONE_KEY, BETA_ONE_DEFAULT); + config.put(BETA_TWO_KEY, BETA_TWO_DEFAULT); + config.put(EPSILON_KEY, EPSILON_DEFAULT); + AdaDelta expResult = new AdaDelta(tf); + AdaDelta result = AdaDelta.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + @Test + public void testBasic() { + float m0 = 0.0F; + float v0 = 0.0F; + float m1 = 0.0F; + float v1 = 0.0F; + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] grads0_init = {0.1F, 0.1F}; + float[] grads1_init = {0.01F, 0.01F}; + FloatNdArray var0_np = NdArrays.vectorOf(var0_init); + FloatNdArray var1_np = NdArrays.vectorOf(var1_init); + FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init); + FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init); + + float epsilon1 = 1e-3F; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + session.setEpsilon(epsilon1); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + float learningRate = 0.001F; + float beta1 = 0.9F; + float beta2 = 0.999F; + float epsilon = 1e-8F; + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Adam instance = new Adam(tf, learningRate); + + Op update = instance.applyGradients(gradsAndVars, "AdamTest"); + + /* Create and validae the shapes of the slota */ + Variable[] firstMomentSlots = new Variable[2]; + Variable[] secondMomentSlots = new Variable[2]; + + firstMomentSlots[0] = instance.getSlot(var0.asOutput(), FIRST_MOMENT).get(); + assertEquals(firstMomentSlots[0].asOutput().shape(), var0.asOutput().shape()); + + secondMomentSlots[0] = instance.getSlot(var0.asOutput(), SECOND_MOMENT).get(); + assertEquals(secondMomentSlots[0].asOutput().shape(), var0.asOutput().shape()); + + firstMomentSlots[1] = instance.getSlot(var1.asOutput(), FIRST_MOMENT).get(); + assertEquals(firstMomentSlots[1].asOutput().shape(), var1.asOutput().shape()); + + secondMomentSlots[1] = instance.getSlot(var1.asOutput(), SECOND_MOMENT).get(); + assertEquals(secondMomentSlots[1].asOutput().shape(), var1.asOutput().shape()); + + /** initialize the accumulators */ + session.run(tf.init()); + + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + FloatNdArray m0_np = NdArrays.ofFloats(shape1); + FloatNdArray v0_np = NdArrays.ofFloats(shape1); + FloatNdArray m1_np = NdArrays.ofFloats(shape1); + FloatNdArray v1_np = NdArrays.ofFloats(shape1); + + for (int step = 0; step < 3; step++) { + + // Test powers + final float[] powers = { + (float) Math.pow(beta1, step + 1), (float) Math.pow(beta2, step + 1) + }; + + try (Tensor result = + session + .getGraphSession() + .runner() + .fetch("beta1_power") + .run() + .get(0) + .expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(powers[0], f.getFloat(), epsilon1); + }); + } + try (Tensor result = + session + .getGraphSession() + .runner() + .fetch("beta2_power") + .run() + .get(0) + .expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(powers[1], f.getFloat(), epsilon1); + }); + } + session.run(update); + + float lr_t = + learningRate + * (float) Math.sqrt(1 - (float) Math.pow(beta2, (step + 1))) + / (1 - (float) Math.pow(beta1, (step + 1))); + + m0_np = calculateM(m0_np, grads0_np, beta1); + v0_np = calculateV(v0_np, grads0_np, beta2); + var0_np = calculateParam(var0_np, lr_t, m0_np, v0_np, 1e-7F); + + m1_np = calculateM(m1_np, grads1_np, beta1); + v1_np = calculateV(v1_np, grads1_np, beta2); + var1_np = calculateParam(var1_np, lr_t, m1_np, v1_np, 1e-7F); + + // evaluate var 0 and var1 + session.evaluate(var0_np, var0); + session.evaluate(var1_np, var1); + + // first moment + session.evaluate(m0_np, firstMomentSlots[0]); + session.evaluate(m1_np, firstMomentSlots[1]); + + // second moment + session.evaluate(v0_np, secondMomentSlots[0]); + session.evaluate(v1_np, secondMomentSlots[1]); + } + } + } + + private FloatNdArray calculateM(FloatNdArray m, FloatNdArray g_t, float beta) { + // m_t = beta1 * m + (1 - beta1) * g_t + return ND.add(ND.mul(m, beta), ND.mul(g_t, (1 - beta))); + } + + private FloatNdArray calculateV(FloatNdArray v, FloatNdArray g_t, float beta) { + // beta2 * v + (1 - beta2) * g_t * g_t + FloatNdArray mul1 = ND.mul(v, beta); + FloatNdArray squareG = ND.square(g_t); + FloatNdArray mul2 = ND.mul((1 - beta), squareG); + FloatNdArray add = ND.add(mul1, mul2); + return add; + + // return ND.add(ND.mul(v, beta), + // ND.mul((1-beta), ND.square(g_t))); + } + + private FloatNdArray calculateParam( + FloatNdArray param, float lr_t, FloatNdArray m, FloatNdArray v, float epsilon) { + // param - lr_t * m_t / (np.sqrt(v_t) + epsilon) + FloatNdArray sqrt = ND.sqrt(v); + FloatNdArray divisor = ND.add(sqrt, epsilon); + FloatNdArray dividend = ND.mul(lr_t, m); + FloatNdArray quotient = ND.div(dividend, divisor); + FloatNdArray result = ND.sub(param, quotient); + return result; + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java new file mode 100644 index 00000000000..1d3dc9e76bf --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java @@ -0,0 +1,242 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.Tensor; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.keras.optimizers.Adamax.BETA_ONE_DEFAULT; +import static org.tensorflow.keras.optimizers.Adamax.BETA_ONE_KEY; +import static org.tensorflow.keras.optimizers.Adamax.BETA_TWO_DEFAULT; +import static org.tensorflow.keras.optimizers.Adamax.BETA_TWO_KEY; +import static org.tensorflow.keras.optimizers.Adamax.EPSILON_DEFAULT; +import static org.tensorflow.keras.optimizers.Adamax.EPSILON_KEY; +import static org.tensorflow.keras.optimizers.Adamax.FIRST_MOMENT; +import static org.tensorflow.keras.optimizers.Adamax.LEARNING_RATE_DEFAULT; +import static org.tensorflow.keras.optimizers.Adamax.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.Adamax.SECOND_MOMENT; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import org.tensorflow.keras.utils.ND; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.NdArrays; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for Adamax Optimizer */ +public class AdamaxTest { + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + + private static final int VAR = 0; + private static final int M = 1; + private static final int V = 2; + + int index; + + public AdamaxTest() {} + + @BeforeAll + public static void setUpClass() {} + + @AfterAll + public static void tearDownClass() {} + + @BeforeEach + public void setUp() {} + + @AfterEach + public void tearDown() {} + + /** Test of create method, of class Adamax. */ + @Test + public void testCreate() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "AdaDelta"); + config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + config.put(BETA_ONE_KEY, BETA_ONE_DEFAULT); + config.put(BETA_TWO_KEY, BETA_TWO_DEFAULT); + config.put(EPSILON_KEY, EPSILON_DEFAULT); + AdaDelta expResult = new AdaDelta(tf); + AdaDelta result = AdaDelta.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + /** Test of getOptimizerName method, of class Adamax. */ + @Test + public void testGetOptimizerName() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Adamax instance = new Adamax(tf); + String expResult = "Adamax"; + String result = instance.getOptimizerName(); + assertEquals(expResult, result); + } + } + + /** Test of applyDense method, of class Adamax. */ + @Test + public void testBasic() { + + int numSteps = 3; + + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] grads0_init = {0.1F, 0.1F}; + float[] grads1_init = {0.01F, 0.01F}; + + float[] zeros = {0.0F, 0.0F}; + FloatNdArray m0 = NdArrays.vectorOf(zeros); + FloatNdArray v0 = NdArrays.vectorOf(zeros); + FloatNdArray m1 = NdArrays.vectorOf(zeros); + FloatNdArray v1 = NdArrays.vectorOf(zeros); + FloatNdArray var0_np = NdArrays.vectorOf(var0_init); + FloatNdArray var1_np = NdArrays.vectorOf(var1_init); + FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init); + FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init); + + float epsilon = 1e-6f; + float epsilon1 = 1e-3F; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + Adamax instance = new Adamax(tf); + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op update = instance.applyGradients(gradsAndVars, "AdamTest"); + + /* Create and validae the shapes of the slota */ + Variable[] firstMomentSlots = new Variable[2]; + Variable[] secondMomentSlots = new Variable[2]; + + firstMomentSlots[0] = instance.getSlot(var0.asOutput(), FIRST_MOMENT).get(); + assertEquals(firstMomentSlots[0].asOutput().shape(), var0.asOutput().shape()); + + secondMomentSlots[0] = instance.getSlot(var0.asOutput(), SECOND_MOMENT).get(); + assertEquals(secondMomentSlots[0].asOutput().shape(), var0.asOutput().shape()); + + firstMomentSlots[1] = instance.getSlot(var1.asOutput(), FIRST_MOMENT).get(); + assertEquals(firstMomentSlots[1].asOutput().shape(), var1.asOutput().shape()); + + secondMomentSlots[1] = instance.getSlot(var1.asOutput(), SECOND_MOMENT).get(); + assertEquals(secondMomentSlots[1].asOutput().shape(), var1.asOutput().shape()); + + /** initialize the accumulators */ + session.run(tf.init()); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + session.setEpsilon(epsilon1); + for (int step = 0; step < numSteps; step++) { + // Test powers + final float beta1_power = (float) Math.pow(BETA_ONE_DEFAULT, step + 1); + + try (Tensor result = + session + .getGraphSession() + .runner() + .fetch("beta1_power") + .run() + .get(0) + .expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(beta1_power, f.getFloat(), epsilon1); + }); + } + session.run(update); + + FloatNdArray[] resultNP = calculate(var0_np, grads0_np, step, m0, v0); + var0_np = resultNP[VAR]; + m0 = resultNP[M]; + v0 = resultNP[V]; + + resultNP = calculate(var1_np, grads1_np, step, m1, v1); + var1_np = resultNP[VAR]; + m1 = resultNP[M]; + v1 = resultNP[V]; + + // evaluate var0 and var1 + + session.evaluate(var0_np, var0); + session.evaluate(var1_np, var1); + } + } + } + + private FloatNdArray[] calculate( + FloatNdArray var_np, FloatNdArray grads_np, int step, FloatNdArray m, FloatNdArray v) { + float alpha = 0.001F; + float beta1 = BETA_ONE_DEFAULT; + float beta2 = BETA_TWO_DEFAULT; + float espilon = 1e-8F; + + float oneMinusBeta1 = 1.F - beta1; + float oneMinusBeta1Pow = 1.F - (float) Math.pow(beta1, step + 1); + float alpha1 = alpha / oneMinusBeta1Pow; + + // beta1 * m + (1 - beta1) * g_t; + m = ND.add(ND.mul(beta1, m), ND.mul(oneMinusBeta1, grads_np)); + // np.maximum(beta2 * v, np.abs(g_t)) + v = ND.max(ND.mul(beta2, v), ND.abs(grads_np)); + // param_t = param - (alpha / (1 - beta1**(t + 1))) * (m_t / (v_t + epsilon)) + var_np = ND.sub(var_np, ND.mul(alpha1, ND.div(m, ND.add(v, espilon)))); + + FloatNdArray[] result = new FloatNdArray[3]; + result[VAR] = var_np; + result[M] = m; + result[V] = v; + return result; + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java new file mode 100644 index 00000000000..d61197348af --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java @@ -0,0 +1,352 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.keras.optimizers.Ftrl.INITIAL_ACCUM_VALUE_KEY; +import static org.tensorflow.keras.optimizers.Ftrl.L1STRENGTH_KEY; +import static org.tensorflow.keras.optimizers.Ftrl.L2STRENGTH_KEY; +import static org.tensorflow.keras.optimizers.Ftrl.L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY; +import static org.tensorflow.keras.optimizers.Ftrl.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.Ftrl.LEARNING_RATE_POWER_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for Ftrl Optimizer */ +public class FtrlTest { + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + int index; + + public FtrlTest() {} + + @BeforeAll + public static void setUpClass() {} + + @AfterAll + public static void tearDownClass() {} + + @BeforeEach + public void setUp() {} + + @AfterEach + public void tearDown() {} + + /** Test of initConfig method, of class Ftrl. */ + @Test + public void testInitConfig() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "Ftrl"); + config.put(LEARNING_RATE_KEY, 2.0F); + config.put(LEARNING_RATE_POWER_KEY, -0.5F); + config.put(INITIAL_ACCUM_VALUE_KEY, 0.1F); + config.put(L1STRENGTH_KEY, 0.0F); + config.put(L2STRENGTH_KEY, 0.0F); + config.put(L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY, 0.0F); + Ftrl expResult = new Ftrl(tf, 2.0F); + Ftrl result = Ftrl.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + /** Test of getOptimizerName method, of class Ftrl. */ + @Test + public void testGetOptimizerName() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Ftrl instance = new Ftrl(tf); + String expResult = "Ftrl"; + String result = instance.getOptimizerName(); + assertEquals(expResult, result); + } + } + + @Test + public void testFtrlWithL1_L2_L2Shrinkage() { + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {4.0F, 3.0F}; + float[] grads0_init = {0.1F, 0.2F}; + float[] grads1_init = {0.01F, 0.02F}; + float epsilon = 1e-8F; + float epsilon1 = 1e-5F; + + int numSteps = 10; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + float learningRate = 3.0F; + + Ftrl instance = + new Ftrl( + tf, + learningRate, + -0.5F, // learningRatePower + 0.1F, // initial_accumulator_value + 0.001F, // l1_regularization_strength + 2.0F, // l2_regularization_strength + 0.1F // l2_shrinkage_regularization_strength + ); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest"); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + for (int i = 0; i < numSteps; i++) { + session.run(ftrl_update); + } + + float[] expectedVar0 = {-0.22578995F, -0.44345796F}; + session.evaluate(expectedVar0, var0); + float[] expectedVar1 = {-0.14378493F, -0.13229476F}; + session.evaluate(expectedVar1, var1); + } + } + + @Test + public void testFtrlWithL1() { + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {4.0F, 3.0F}; + float[] grads0_init = {0.1F, 0.2F}; + float[] grads1_init = {0.01F, 0.02F}; + float epsilon = 1e-8F; + float epsilon1 = 1e-5F; + + int numSteps = 10; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + float learningRate = 3.0F; + + Ftrl instance = + new Ftrl( + tf, + learningRate, + Ftrl.LEARNING_RATE_POWER_DEFAULT, // learningRatePower + 0.1F, // initial_accumulator_value + 0.001F, // l1_regularization_strength + 0.0F, // l2_regularization_strength + Ftrl + .L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT // l2_shrinkage_regularization_strength + ); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest"); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + for (int i = 0; i < numSteps; i++) { + session.run(ftrl_update); + } + + float[] expectedVar0 = {-7.66718769F, -10.91273689F}; + session.evaluate(expectedVar0, var0); + + float[] expectedVar1 = {-0.93460727F, -1.86147261F}; + session.evaluate(expectedVar1, var1); + } + } + + @Test + public void testFtrlWithL1_L2() { + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {4.0F, 3.0F}; + float[] grads0_init = {0.1F, 0.2F}; + float[] grads1_init = {0.01F, 0.02F}; + float epsilon = 1e-8F; + float epsilon1 = 1e-5F; + + int numSteps = 10; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + float learningRate = 3.0F; + + Ftrl instance = + new Ftrl( + tf, + learningRate, + Ftrl.LEARNING_RATE_POWER_DEFAULT, // learningRatePower + 0.1F, // initial_accumulator_value + 0.001F, // l1_regularization_strength + 2.0F, // l2_regularization_strength + Ftrl + .L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT // l2_shrinkage_regularization_strength + ); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest"); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + for (int i = 0; i < numSteps; i++) { + session.run(ftrl_update); + } + + float[] expectedVar0 = {-0.24059935F, -0.46829352F}; + session.evaluate(expectedVar0, var0); + + float[] expectedVar1 = {-0.02406147F, -0.04830509F}; + session.evaluate(expectedVar1, var1); + } + } + + @Test + public void doTestFtrlwithoutRegularization() { + float[] var0_init = {0.0F, 0.0F}; + float[] var1_init = {0.0F, 0.0F}; + float[] grads0_init = {0.1F, 0.2F}; + float[] grads1_init = {0.01F, 0.02F}; + float epsilon = 1e-8F; + float epsilon1 = 1e-5F; + + int numSteps = 3; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + float learningRate = 3.0F; + + Ftrl instance = new Ftrl(tf, learningRate); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest"); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + for (int i = 0; i < numSteps; i++) { + session.run(ftrl_update); + } + + float[] expectedVar0 = {-2.60260963F, -4.29698515F}; + float[] expectedVar1 = {-0.28432083F, -0.56694895F}; + + session.evaluate(expectedVar0, var0); + session.evaluate(expectedVar1, var1); + } + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java new file mode 100644 index 00000000000..2b8bce40471 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java @@ -0,0 +1,286 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.Tensor; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.keras.optimizers.Adamax.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.Nadam.BETA_ONE_DEFAULT; +import static org.tensorflow.keras.optimizers.Nadam.BETA_ONE_KEY; +import static org.tensorflow.keras.optimizers.Nadam.BETA_TWO_DEFAULT; +import static org.tensorflow.keras.optimizers.Nadam.BETA_TWO_KEY; +import static org.tensorflow.keras.optimizers.Nadam.EPSILON_DEFAULT; +import static org.tensorflow.keras.optimizers.Nadam.EPSILON_KEY; +import static org.tensorflow.keras.optimizers.Nadam.FIRST_MOMENT; +import static org.tensorflow.keras.optimizers.Nadam.LEARNING_RATE_DEFAULT; +import static org.tensorflow.keras.optimizers.Nadam.SECOND_MOMENT; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import org.tensorflow.keras.utils.ND; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.NdArrays; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for Nadam Optimizer */ +public class NadamTest { + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + + private static final int VAR = 0; + private static final int M = 1; + private static final int V = 2; + + int index = 0; + float momentum = 1; + + public NadamTest() {} + + @BeforeAll + public static void setUpClass() {} + + @AfterAll + public static void tearDownClass() {} + + @BeforeEach + public void setUp() {} + + @AfterEach + public void tearDown() {} + + /** Test of create method, of class Nadam. */ + @Test + public void testCreate() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "AdaDelta"); + config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT); + config.put(BETA_ONE_KEY, BETA_ONE_DEFAULT); + config.put(BETA_TWO_KEY, BETA_TWO_DEFAULT); + config.put(EPSILON_KEY, EPSILON_DEFAULT); + AdaDelta expResult = new AdaDelta(tf); + AdaDelta result = AdaDelta.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + /** Test of getOptimizerName method, of class Nadam. */ + @Test + public void testGetOptimizerName() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Nadam instance = new Nadam(tf); + String expResult = "Nadam"; + String result = instance.getOptimizerName(); + assertEquals(expResult, result); + } + } + + /** Test of applyDense method, of class Nadam. */ + @Test + public void testBasic() { + + int numSteps = 3; + + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] grads0_init = {0.1F, 0.1F}; + float[] grads1_init = {0.01F, 0.01F}; + + float[] zeros = {0.0F, 0.0F}; + float[] ones = {1.0F, 1.0F}; + FloatNdArray m0 = NdArrays.vectorOf(zeros); + FloatNdArray v0 = NdArrays.vectorOf(zeros); + FloatNdArray m1 = NdArrays.vectorOf(zeros); + FloatNdArray v1 = NdArrays.vectorOf(zeros); + FloatNdArray mcache = NdArrays.vectorOf(ones); + FloatNdArray var0_np = NdArrays.vectorOf(var0_init); + FloatNdArray var1_np = NdArrays.vectorOf(var1_init); + FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init); + FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init); + + float epsilon = 1e-6f; + float epsilon1 = 1e-3F; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + Nadam instance = new Nadam(tf); + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op update = instance.applyGradients(gradsAndVars, "AdamTest"); + + /* Create and validae the shapes of the slota */ + Variable[] firstMomentSlots = new Variable[2]; + Variable[] secondMomentSlots = new Variable[2]; + + firstMomentSlots[0] = instance.getSlot(var0.asOutput(), FIRST_MOMENT).get(); + assertEquals(firstMomentSlots[0].asOutput().shape(), var0.asOutput().shape()); + + secondMomentSlots[0] = instance.getSlot(var0.asOutput(), SECOND_MOMENT).get(); + assertEquals(secondMomentSlots[0].asOutput().shape(), var0.asOutput().shape()); + + firstMomentSlots[1] = instance.getSlot(var1.asOutput(), FIRST_MOMENT).get(); + assertEquals(firstMomentSlots[1].asOutput().shape(), var1.asOutput().shape()); + + secondMomentSlots[1] = instance.getSlot(var1.asOutput(), SECOND_MOMENT).get(); + assertEquals(secondMomentSlots[1].asOutput().shape(), var1.asOutput().shape()); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + session.setEpsilon(epsilon1); + + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + try (Tensor result = + session + .getGraphSession() + .runner() + .fetch("momentum") + .run() + .get(0) + .expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(1F, f.getFloat(), epsilon1); + }); + } + momentum = 1F; + + for (int step = 0; step < numSteps; step++) { + + session.run(update); + + float mut = + Nadam.BETA_ONE_DEFAULT * (1F - 0.5F * (float) Math.pow(0.96F, (0.004F * (step + 1)))); + momentum = momentum * mut; + + try (Tensor result = + session + .getGraphSession() + .runner() + .fetch("momentum") + .run() + .get(0) + .expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(momentum, f.getFloat(), epsilon1); + }); + } + mcache = ND.mul(mcache, momentum); + FloatNdArray[] resultsNP = nadam_update_numpy(var0_np, grads0_np, step, m0, v0, mcache); + var0_np = resultsNP[VAR]; + m0 = resultsNP[M]; + v0 = resultsNP[V]; + + resultsNP = nadam_update_numpy(var1_np, grads1_np, step, m1, v1, mcache); + var1_np = resultsNP[VAR]; + m1 = resultsNP[M]; + v1 = resultsNP[V]; + + // evaluate m0 and m1 + session.evaluate(m0, firstMomentSlots[0]); + session.evaluate(m1, firstMomentSlots[1]); + + // evaluate v0 and v1 + session.evaluate(v0, secondMomentSlots[0]); + session.evaluate(v1, secondMomentSlots[1]); + + // evaluate var0 and var1 + session.evaluate(var0_np, var0); + session.evaluate(var1_np, var1); + } + } + } + + private FloatNdArray update_m_cache(FloatNdArray mcache, int t) { + float mu_t = 0.9F * (1.0F - 0.5F * (float) Math.pow(0.96, (0.004 * (t + 1)))); + return ND.mul(mu_t, mcache); + } + + private FloatNdArray[] nadam_update_numpy( + FloatNdArray var_np, + FloatNdArray grads_np, + int t, + FloatNdArray m, + FloatNdArray v, + FloatNdArray m_cache) { + + float alpha = 0.001F; + float beta1 = 0.9F; + float beta2 = 0.999F; + float epsilon = 1e-8F; + float mu_t = beta1 * (1F - 0.5F * (float) Math.pow(0.96, 0.004 * (t + 1))); + float mu_t_1 = beta1 * (1F - 0.5F * (float) Math.pow(0.96, (0.004 * (t + 2)))); + FloatNdArray m_cache_t_1 = ND.mul(m_cache, mu_t_1); + FloatNdArray g_prime_t = ND.div(grads_np, ND.sub(1.0F, m_cache)); + FloatNdArray m_t = ND.add(ND.mul(beta1, m), ND.mul((1 - beta1), grads_np)); + FloatNdArray v_t = ND.add(ND.mul(beta2, v), ND.mul((1 - beta2), ND.square(grads_np))); + + FloatNdArray m_prime_t = ND.div(m_t, ND.sub(1.F, m_cache_t_1)); + FloatNdArray v_prime_t = ND.div(v_t, 1.F - (float) Math.pow(beta2, t + 1)); + FloatNdArray m_bar_t = ND.add(ND.mul((1 - mu_t), g_prime_t), ND.mul(mu_t_1, m_prime_t)); + FloatNdArray param_t = + ND.sub(var_np, ND.div(ND.mul(alpha, m_bar_t), ND.add(ND.sqrt(v_prime_t), epsilon))); + + FloatNdArray[] results = new FloatNdArray[3]; + results[VAR] = param_t; + results[M] = m_t; + results[V] = v_t; + return results; + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java new file mode 100644 index 00000000000..b8fb4f40ee9 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java @@ -0,0 +1,307 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.framework.optimizers.RMSProp.MG; +import static org.tensorflow.framework.optimizers.RMSProp.MOMENTUM; +import static org.tensorflow.framework.optimizers.RMSProp.RMS; +import static org.tensorflow.keras.optimizers.Ftrl.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import static org.tensorflow.keras.optimizers.RMSProp.CENTERED_DEFAULT; +import static org.tensorflow.keras.optimizers.RMSProp.CENTERED_KEY; +import static org.tensorflow.keras.optimizers.RMSProp.DECAY_DEFAULT; +import static org.tensorflow.keras.optimizers.RMSProp.DECAY_KEY; +import static org.tensorflow.keras.optimizers.RMSProp.EPSILON_DEFAULT; +import static org.tensorflow.keras.optimizers.RMSProp.EPSILON_KEY; +import static org.tensorflow.keras.optimizers.RMSProp.MOMENTUM_DEFAULT; +import static org.tensorflow.keras.optimizers.RMSProp.MOMENTUM_KEY; +import org.tensorflow.keras.utils.ND; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.NdArrays; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for RMSProp Optimizer */ +public class RMSPropTest { + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + + final int VAR_T = 0; + final int MG_T = 1; + final int RMS_T = 2; + final int MOM_T = 3; + + int index; + + public RMSPropTest() { + } + + @BeforeAll + public static void setUpClass() { + } + + @AfterAll + public static void tearDownClass() { + } + + @BeforeEach + public void setUp() { + } + + @AfterEach + public void tearDown() { + } + + /** + * Test of create method, of class RMSProp. + */ + @Test + public void testCreate() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "Ftrl"); + config.put(LEARNING_RATE_KEY, 2.0F); + config.put(DECAY_KEY, DECAY_DEFAULT); + config.put(MOMENTUM_KEY, MOMENTUM_DEFAULT); + config.put(EPSILON_KEY, EPSILON_DEFAULT); + config.put(CENTERED_KEY, CENTERED_DEFAULT); + Ftrl expResult = new Ftrl(tf, 2.0F); + Ftrl result = Ftrl.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + Object[][] _test_param_values = { + // learning_rate, rho (decay), momentum, epsilon, centered + {0.05F, 0.9F, 0.0F, 1e-3F, true}, + {0.05F, 0.9F, 0.0F, 1e-3F, false}, + {0.1F, 0.9F, 0.0F, 1e-3F, true}, + {0.01F, 0.9F, 0.0F, 1e-5F, true}, + {0.01F, 0.9F, 0.9F, 1e-5F, true} + }; + + @Test + public void testDense() { + + int numSteps = 3; + + for (int run = 0; run < _test_param_values.length; run++) { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + session.setEpsilon(1e-2f); + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] grads0_init = {0.1F, 0.2F}; + float[] grads1_init = {0.01F, 0.2F}; + final float epsilon1 = 1e-2F; + + FloatNdArray var0_np = NdArrays.vectorOf(var0_init); + FloatNdArray var1_np = NdArrays.vectorOf(var1_init); + FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init); + FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + // learning_rate, rho (decay), momentum, epsilon, centered + float learningRate = (float) (float) _test_param_values[run][0]; + float decay = (float) _test_param_values[run][1]; + float momentum = (float) _test_param_values[run][2]; + float epsilon = (float) _test_param_values[run][3]; + boolean centered = (boolean) _test_param_values[run][4]; + + RMSProp instance = new RMSProp(tf, + learningRate, + decay, + momentum, + epsilon, + centered); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + Op update = instance.applyGradients(gradsAndVars, "RMSPropTest"); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** + * initialize the accumulators + */ + session.run(tf.init()); + + /** + * make sure the variables were initialized properly + */ + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + Variable mg0 = centered ? instance.getSlot(var0.asOutput(), MG).get() : null; + Variable mg1 = centered ? instance.getSlot(var1.asOutput(), MG).get() : null; + Variable mom0 = momentum > 0.F ? instance.getSlot(var0.asOutput(), MOMENTUM).get() : null; + Variable mom1 = momentum > 0.F ? instance.getSlot(var1.asOutput(), MOMENTUM).get() : null; + Variable rms0 = instance.getSlot(var0.asOutput(), RMS).get(); + Variable rms1 = instance.getSlot(var1.asOutput(), RMS).get(); + + float[] zeros = {0.0F, 0.0F}; + float[] ones = {1.0F, 1.0F}; // temp to match RMSProp + FloatNdArray mg0_np = NdArrays.vectorOf(zeros); + FloatNdArray mg1_np = NdArrays.vectorOf(zeros); + FloatNdArray rms0_np = NdArrays.vectorOf(ones); + FloatNdArray rms1_np = NdArrays.vectorOf(ones); + FloatNdArray mom0_np = NdArrays.vectorOf(zeros); + FloatNdArray mom1_np = NdArrays.vectorOf(zeros); + + + + for (int i = 0; i < numSteps; i++) { + session.run(update); + FloatNdArray[] result0 = calc(var0_np, grads0_np, mg0_np, rms0_np, + mom0_np, learningRate, decay, momentum, epsilon, centered); + var0_np = result0[VAR_T]; + mg0_np = result0[MG_T]; + rms0_np = result0[RMS_T]; + mom0_np = result0[MOM_T]; + + FloatNdArray[] result1 = calc(var1_np, grads1_np, mg1_np, rms1_np, + mom1_np, learningRate, decay, momentum, epsilon, centered); + + var1_np = result1[VAR_T]; + mg1_np = result1[MG_T]; + rms1_np = result1[RMS_T]; + mom1_np = result1[MOM_T]; + + if (centered) { + session.evaluate(mg0_np, mg0); + session.evaluate(mg0_np, mg0); + } + if (momentum > 0.F) { + session.evaluate(mom0_np, mom0); + session.evaluate(mom1_np, mom1); + } + + /* TODO the values returned from rms slot, do not match what I see in the python test */ + session.evaluate(rms0_np, rms0); + session.evaluate(rms1_np, rms1); + + session.evaluate(var0_np, var0); + session.evaluate(var1_np, var1); + } + } + } + } + + FloatNdArray[] calc(FloatNdArray var_np, FloatNdArray grad_np, FloatNdArray mg_np, + FloatNdArray rms_np, FloatNdArray mom, float lr, float decay, float momentum, + float epsilon, boolean centered) { + + FloatNdArray[] result = new FloatNdArray[4]; // var_t, mg_t, rms_t, mom_t + result[RMS_T] = calcRMS(rms_np, grad_np, decay); // RMS + + FloatNdArray denom_t; + if (centered) { + result[MG_T] = calcMG(mg_np, grad_np, decay); + //rms_t - mg_t * mg_t + denom_t = ND.sub(result[RMS_T], ND.square(result[MG_T])); + } else { + result[MG_T] = mg_np; + denom_t = rms_np; + } + if (momentum > 0.F) { + //momentum * mom + lr * g / (np.sqrt(denom_t + epsilon)) + result[MOM_T] = calcMom(momentum, mom, lr, grad_np, denom_t, epsilon); + //var_t = var - mom_t + result[VAR_T] = ND.sub(var_np, result[MOM_T]); + } else { + result[MOM_T] = mom; + result[VAR_T] = calcVar(var_np, grad_np, lr, denom_t, epsilon); + } + + + return result; + + } + + private FloatNdArray calcRMS(FloatNdArray rms_np, FloatNdArray grad_np, float decay) { + //rms * rho + (1 - rho) * g * g + FloatNdArray rms_rho = ND.mul(rms_np, decay); + FloatNdArray squareG = ND.square(grad_np); + float oneRHO = 1.0F - decay; + FloatNdArray decayG2 = ND.mul(oneRHO, squareG); + FloatNdArray result = ND.add(rms_rho, decayG2); + return result; + } + + private FloatNdArray calcMG(FloatNdArray mg_np, FloatNdArray grad_np, float decay) { + //mg_t = mg * rho + (1 - rho) * g + FloatNdArray mg_rho = ND.mul(mg_np, decay); + float oneRHO = 1.0F - decay; + FloatNdArray decayG = ND.mul(oneRHO, grad_np); + FloatNdArray result = ND.add(mg_rho, decayG); + return result; + + } + + private FloatNdArray calcMom(float momentum, FloatNdArray mom, float lr, + FloatNdArray grad_np, FloatNdArray denom_t, float epsilon) { + // momentum * mom + lr * g / (np.sqrt(denom_t + epsilon)) + FloatNdArray moMo = ND.mul(momentum, mom); + FloatNdArray dividend = ND.mul(lr, grad_np); + FloatNdArray divisor = ND.sqrt(ND.add(denom_t, epsilon)); + FloatNdArray quotient = ND.div(dividend, divisor); + FloatNdArray result = ND.add(moMo, quotient); + return result; + + } + + private FloatNdArray calcVar(FloatNdArray var_np, FloatNdArray grad_np, float lr, + FloatNdArray denom_t, float epsilon) { + // var - lr * g / (np.sqrt(denom_t) + epsilon) + FloatNdArray dividend = ND.mul(lr, grad_np); + FloatNdArray divisor = ND.add(ND.sqrt(denom_t), epsilon); + FloatNdArray quotient = ND.div(dividend, divisor); + FloatNdArray result = ND.sub(var_np, quotient); + return result; + + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java new file mode 100644 index 00000000000..7e12b957f84 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java @@ -0,0 +1,227 @@ +/* Copyright 2020 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.keras.optimizers; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import static org.tensorflow.framework.optimizers.Momentum.MOMENTUM; +import org.tensorflow.framework.optimizers.Optimizer; +import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY; +import static org.tensorflow.keras.optimizers.SGD.LEARNING_RATE_KEY; +import static org.tensorflow.keras.optimizers.SGD.MOMENTUM_DEFAULT; +import static org.tensorflow.keras.optimizers.SGD.MOMENTUM_KEY; +import static org.tensorflow.keras.optimizers.SGD.NESTEROV_DEFAULT; +import static org.tensorflow.keras.optimizers.SGD.NESTEROV_KEY; +import org.tensorflow.keras.utils.TestSession; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Assign; +import org.tensorflow.op.core.Constant; +import org.tensorflow.op.core.Variable; +import org.tensorflow.types.TFloat32; + +/** Test cases for SGD Optimizer */ +public class SGDTest { + + private TestSession.Mode tf_mode = TestSession.Mode.GRAPH; + + int index; + + public SGDTest() {} + + @BeforeAll + public static void setUpClass() {} + + @AfterAll + public static void tearDownClass() {} + + @BeforeEach + public void setUp() {} + + @AfterEach + public void tearDown() {} + + /** Test of create method, of class SGD. */ + @Test + public void testCreate() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + Map config = new HashMap<>(); + config.put(NAME_KEY, "Ftrl"); + config.put(LEARNING_RATE_KEY, 2.0F); + config.put(MOMENTUM_KEY, MOMENTUM_DEFAULT); + config.put(NESTEROV_KEY, NESTEROV_DEFAULT); + SGD expResult = new SGD(tf, 2.0F); + SGD result = SGD.create(tf, config); + assertEquals(expResult.getConfig(), result.getConfig()); + } + } + + /** Test of getOptimizerName method, of class SGD. */ + @Test + public void testGetOptimizerName() { + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + SGD instance = new SGD(tf); + String expResult = "SGD"; + String result = instance.getOptimizerName(); + assertEquals(expResult, result); + } + } + + @Test + public void testBasic() { + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] grads0_init = {0.1F, 0.1F}; + float[] grads1_init = {0.01F, 0.01F}; + float learningRate = 3.0F; + + float epsilon = 1e-6F; + float epsilon1 = 1e-2F; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + SGD instance = new SGD(tf, learningRate); + Op update = instance.applyGradients(gradsAndVars, "SGDTest"); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + /** make sure the variables were initialized properly */ + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + session.run(update); // 1 step + + float[] expectedVar0 = {1.0F - 3.0F * 0.1F, 2.0F - 3.0F * 0.1F}; + float[] expectedVar1 = {3.0F - 3.0F * 0.01F, 4.0F - 3.0F * 0.01F}; + session.evaluate(expectedVar0, var0); + session.evaluate(expectedVar1, var1); + } + } + + @Test + public void testMomentum() { + float[] var0_init = {1.0F, 2.0F}; + float[] var1_init = {3.0F, 4.0F}; + float[] grads0_init = {0.1F, 0.1F}; + float[] grads1_init = {0.01F, 0.01F}; + + float learningRate = 2.0F; + float momentum = 0.9F; + + float epsilon = 1e-6F; + float epsilon1 = 1e-2F; + + try (TestSession session = TestSession.createTestSession(tf_mode)) { + Ops tf = session.getTF(); + + Shape shape0 = Shape.of(var0_init.length); + Shape shape1 = Shape.of(var1_init.length); + Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE); + Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE); + + Assign var0Initializer = tf.assign(var0, tf.constant(var0_init)); + Assign var1Initializer = tf.assign(var1, tf.constant(var1_init)); + + Constant grads0 = tf.constant(grads0_init); + Constant grads1 = tf.constant(grads1_init); + + /* build the GradsAnvVars */ + List gradsAndVars = new ArrayList<>(); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput())); + gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput())); + + SGD instance = new SGD(tf, learningRate, momentum); + Op update = instance.applyGradients(gradsAndVars, "SGDTest"); + + Variable momentumSlot0 = instance.getSlot(var0.asOutput(), MOMENTUM).get(); + assertEquals(momentumSlot0.asOutput().shape(), var0.asOutput().shape()); + Variable momentumSlot1 = instance.getSlot(var1.asOutput(), MOMENTUM).get(); + assertEquals(momentumSlot1.asOutput().shape(), var1.asOutput().shape()); + + /* initialize the local variables */ + session.run(var0Initializer); + session.run(var1Initializer); + + /** initialize the accumulators */ + session.run(tf.init()); + + /** make sure the variables were initialized properly */ + session.evaluate(var0_init, var0); + session.evaluate(var1_init, var1); + + session.run(update); // 1 step + + float[] expectedMomentum0 = {0.1F, 0.1F}; + float[] expectedMomentum1 = {0.01F, 0.01F}; + session.evaluate(expectedMomentum0, momentumSlot0); + session.evaluate(expectedMomentum1, momentumSlot1); + + float[] expectedVar0 = {1.0F - (0.1F * 2.0F), 2.0F - (0.1F * 2.0F)}; + float[] expectedVar1 = {3.0F - (0.01F * 2.0F), 4.0F - (0.01F * 2.0F)}; + session.evaluate(expectedVar0, var0); + session.evaluate(expectedVar1, var1); + + session.run(update); // step 2 + + float[] expectedMomentum0_2 = {(0.9f * 0.1f + 0.1f), (0.9f * 0.1f + 0.1f)}; + float[] expectedMomentum1_2 = {(0.9f * 0.01f + 0.01f), (0.9f * 0.01f + 0.01f)}; + session.evaluate(expectedMomentum0_2, momentumSlot0); + session.evaluate(expectedMomentum1_2, momentumSlot1); + + float[] expectedVar0_2 = { + 1.0F - (0.1F * 2.0F) - ((0.9F * 0.1F + 0.1F) * 2.0F), + 2.0F - (0.1F * 2.0F) - ((0.9F * 0.1F + 0.1F) * 2.0F) + }; + float[] expectedVar1_2 = { + 2.98F - ((0.9F * 0.01F + 0.01F) * 2.0F), 3.98F - ((0.9F * 0.01F + 0.01F) * 2.0F) + }; + session.evaluate(expectedVar0_2, var0); + session.evaluate(expectedVar1_2, var1); + } + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java new file mode 100644 index 00000000000..3bc8091811a --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java @@ -0,0 +1,747 @@ +/* Copyright 2020 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.keras.utils; + +import java.io.PrintWriter; +import java.util.concurrent.atomic.AtomicInteger; +import java.util.concurrent.atomic.AtomicLong; +import java.util.function.Predicate; +import static org.junit.jupiter.api.Assertions.assertEquals; +import static org.junit.jupiter.api.Assertions.assertTrue; +import static org.junit.jupiter.api.Assertions.fail; +import org.tensorflow.DataType; +import org.tensorflow.EagerSession; +import org.tensorflow.Operand; +import org.tensorflow.Output; +import org.tensorflow.Session; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Ops; +import org.tensorflow.types.TBool; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TFloat64; +import org.tensorflow.types.TInt32; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.TString; +import org.tensorflow.types.family.TNumber; +import org.tensorflow.types.family.TType; + +/** Eaager Mode Test Session */ +public class EagerTestSession extends TestSession { + + private final EagerSession session; + private final Ops tf; + + /** Create an Eager mode test session. */ + public EagerTestSession() { + this.session = EagerSession.create(); + this.tf = Ops.create(session).withName("test"); + } + + /** {@inheritDoc} */ + @Override + public Ops getTF() { + return tf; + } + + /** + * Get the TensorFlow EagerSession instance + * @return the TensorFlow EagerSession instance + */ + public EagerSession getSession() { + return session; + } + + /** {@inheritDoc} */ + @Override + public void close() { + session.close(); + } + + /** {@inheritDoc} */ + @Override + public boolean isEager() { + return true; + } + + /** {@inheritDoc} */ + @Override + public Session getGraphSession() { + return null; + } + + /** {@inheritDoc} */ + @Override + public EagerSession getEagerSession() { + return this.session; + } + + /** {@inheritDoc} */ + @Override + public void evaluate(double expected, Operand input) { + DataType dtype = input.asOutput().dataType(); + if (dtype == TFloat32.DTYPE) { + Operand o = (Operand) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals(expected, f.getFloat(), epsilon); + }); + } else if (dtype == TFloat64.DTYPE) { + Operand o = (Operand) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals((double) expected, f.getDouble(), epsilon); + }); + } else if (dtype == TInt32.DTYPE) { + Operand o = (Operand) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals((int) expected, f.getInt()); + }); + } else if (dtype == TInt64.DTYPE) { + Operand o = (Operand) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals((long) expected, f.getLong()); + }); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Number[] expected, Output input) { + int size = input.shape().size() == 0 ? 1 : (int) input.shape().size(); + assertEquals( + expected.length, + size, + () -> String.format("expected length (%d) != to input length (%d)", expected.length, size)); + DataType dtype = input.dataType(); + if (dtype == TFloat32.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon); + }); + } else if (dtype == TFloat64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals( + expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon); + }); + } else if (dtype == TInt32.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt()); + }); + } else if (dtype == TInt64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong()); + }); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(FloatNdArray expected, Output input) { + DataType dtype = input.dataType(); + if (dtype == TFloat32.DTYPE) { + Output o = (Output) input; + AtomicLong index = new AtomicLong(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals(expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon); + }); + } else if (dtype == TFloat64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals( + (double) expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon); + }); + } else if (dtype == TInt32.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt()); + }); + } else if (dtype == TInt64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } + index.set(0); + o.data() + .scalars() + .forEach( + f -> { + assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong()); + }); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Output input, Predicate predicate) { + AtomicInteger index = new AtomicInteger(); + DataType dtype = input.asOutput().dataType(); + boolean isScalar = input.shape().equals(Shape.scalar()); + if (dtype == TFloat32.DTYPE) { + Output o = (Output) input; + if (debug) { + if (isScalar) { + System.out.printf( + "0). %b <==> %f\n", predicate.test(o.data().getFloat()), o.data().getFloat()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %f\n", + index.getAndIncrement(), predicate.test(f.getFloat()), f.getFloat()); + }); + } + } + index.set(0); + if (isScalar) { + assertTrue(predicate.test(o.data().getFloat())); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(o.data().getFloat())); + }); + } + } else if (dtype == TFloat64.DTYPE) { + Output o = (Output) input; + if (debug) { + if (isScalar) { + System.out.printf( + "0). %b <==> %f\n", predicate.test(o.data().getDouble()), o.data().getDouble()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %f\n", + index.getAndIncrement(), predicate.test(f.getDouble()), f.getDouble()); + }); + } + } + index.set(0); + if (isScalar) { + assertTrue(predicate.test(o.data().getDouble())); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(o.data().getDouble())); + }); + } + } else if (dtype == TInt32.DTYPE) { + Output o = (Output) input; + if (debug) { + if (isScalar) { + System.out.printf( + "0). %b <==> %d\n", predicate.test(o.data().getInt()), o.data().getInt()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %d\n", + index.getAndIncrement(), predicate.test(f.getInt()), f.getInt()); + }); + } + } + index.set(0); + if (isScalar) { + assertTrue(predicate.test(o.data().getInt())); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(o.data().getInt())); + }); + } + } else if (dtype == TInt64.DTYPE) { + Output o = (Output) input; + if (debug) { + if (isScalar) { + System.out.printf( + "0). %b <==> %d\n", predicate.test(o.data().getLong()), o.data().getLong()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %d\n", + index.getAndIncrement(), predicate.test(f.getLong()), f.getLong()); + }); + } + } + index.set(0); + if (isScalar) { + assertTrue(predicate.test(o.data().getLong())); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(o.data().getLong())); + }); + } + } else { + fail("Unexpected DataType: " + dtype); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(String[] expected, Output input) { + int size = input.shape().size() == 0 ? 1 : (int) input.shape().size(); + assertEquals( + expected.length, + size, + () -> String.format("expected length (%d) != to input length (%d)", expected.length, size)); + AtomicInteger index = new AtomicInteger(); + if (debug) { + input + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject()); + }); + } + index.set(0); + input + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()], f.getObject()); + }); + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Boolean[] expected, Output input) { + int size = input.shape().size() == 0 ? 1 : (int) input.shape().size(); + assertEquals( + expected.length, + size, + () -> String.format("expected size (%d) != to input length (%d)", expected.length, size)); + AtomicInteger index = new AtomicInteger(); + if (debug) { + input + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()); + }); + } + index.set(0); + input + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()], f.getBoolean()); + }); + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Output expected, Output input) { + assert input.shape().equals(expected.shape()) + : String.format( + "expected shape (%s) != to input shape (%ds)", + expected.shape().toString(), input.shape().toString()); + DataType dtype = input.asOutput().dataType(); + boolean isScalar = input.shape().equals(Shape.scalar()); + if (dtype == TFloat32.DTYPE) { + Output x = (Output) expected; + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + if (isScalar) { + System.out.printf("0). %f <==> %f\n", x.data().getFloat(), o.data().getFloat()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %f <==> %f\n", + index.getAndIncrement(), x.data().getFloat(idx), f.getFloat()); + }); + } + } + index.set(0); + if (isScalar) { + assertEquals(x.data().getFloat(), o.data().getFloat(), epsilon); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> assertEquals(x.data().getFloat(idx), f.getFloat(), epsilon)); + } + } else if (dtype == TFloat64.DTYPE) { + Output x = (Output) expected; + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + if (isScalar) { + System.out.printf("0). %f <==> %f\n", x.data().getDouble(), o.data().getDouble()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %f <==> %f\n", + index.getAndIncrement(), x.data().getDouble(idx), f.getDouble()); + }); + } + } + index.set(0); + if (isScalar) { + assertEquals(x.data().getDouble(), o.data().getDouble(), epsilon); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> assertEquals(x.data().getDouble(idx), f.getDouble(), epsilon)); + } + } else if (dtype == TInt32.DTYPE) { + Output x = (Output) expected; + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + if (isScalar) { + System.out.printf("0). %d <==> %d\n", x.data().getInt(), o.data().getInt()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %d <==> %d\n", + index.getAndIncrement(), x.data().getInt(idx), f.getInt()); + }); + } + } + index.set(0); + if (isScalar) { + assertEquals(x.data().getInt(), o.data().getInt()); + } else { + o.data() + .scalars() + .forEachIndexed((idx, f) -> assertEquals(x.data().getInt(idx), f.getInt())); + } + } else if (dtype == TInt64.DTYPE) { + Output x = (Output) expected; + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + if (isScalar) { + System.out.printf("0). %d <==> %d\n", x.data().getLong(), o.data().getLong()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %d <==> %d\n", + index.getAndIncrement(), x.data().getLong(idx), f.getLong()); + }); + } + } + index.set(0); + if (isScalar) { + assertEquals(x.data().getLong(), o.data().getLong()); + } else { + o.data() + .scalars() + .forEachIndexed((idx, f) -> assertEquals(x.data().getLong(idx), f.getLong())); + } + } else if (dtype == TString.DTYPE) { + Output x = (Output) expected; + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + if (isScalar) { + System.out.printf("0). %s <==> %s\n", x.data().getObject(), o.data().getObject()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %s <==> %s\n", + index.getAndIncrement(), x.data().getObject(idx), f.getObject()); + }); + } + } + index.set(0); + if (isScalar) { + assertEquals(x.data().getObject(), o.data().getObject()); + } else { + o.data() + .scalars() + .forEachIndexed((idx, f) -> assertEquals(x.data().getObject(idx), f.getObject())); + } + } else if (dtype == TBool.DTYPE) { + Output x = (Output) expected; + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + if (isScalar) { + System.out.printf("0). %b <==> %b\n", x.data().getBoolean(), o.data().getBoolean()); + } else { + o.data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %b\n", + index.getAndIncrement(), x.data().getBoolean(idx), f.getBoolean()); + }); + } + } + index.set(0); + if (isScalar) { + assertEquals(x.data().getBoolean(), o.data().getBoolean()); + } else { + o.data() + .scalars() + .forEachIndexed((idx, f) -> assertEquals(x.data().getBoolean(idx), f.getBoolean())); + } + } + } + + /** {@inheritDoc} */ + @Override + public void print(PrintWriter writer, Output input) { + DataType dtype = input.asOutput().dataType(); + if (dtype == TFloat32.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } else if (dtype == TFloat64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } else if (dtype == TInt32.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } else if (dtype == TInt64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } else if (dtype == TString.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject()); + }); + } else if (dtype == TBool.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + o.data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()); + }); + } else { + writer.println("Unexpected DataType: " + dtype); + } + writer.flush(); + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/GraphTestSession.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/GraphTestSession.java new file mode 100644 index 00000000000..1a22289f4bf --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/GraphTestSession.java @@ -0,0 +1,1066 @@ +/* Copyright 2020 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.keras.utils; + +import java.io.PrintWriter; +import java.util.concurrent.atomic.AtomicInteger; +import java.util.concurrent.atomic.AtomicLong; +import java.util.function.Predicate; +import static org.junit.jupiter.api.Assertions.assertEquals; +import static org.junit.jupiter.api.Assertions.assertTrue; +import static org.junit.jupiter.api.Assertions.fail; +import org.tensorflow.DataType; +import org.tensorflow.EagerSession; +import org.tensorflow.Graph; +import org.tensorflow.Operand; +import org.tensorflow.Output; +import org.tensorflow.Session; +import org.tensorflow.Tensor; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.ndarray.Shape; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.types.TBool; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TFloat64; +import org.tensorflow.types.TInt32; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.TString; +import org.tensorflow.types.family.TNumber; +import org.tensorflow.types.family.TType; + +/** Graph Mode Test Session */ +public class GraphTestSession extends TestSession { + + private final Graph graph; + private final Session session; + private final Ops tf; + + /** Create a Graph mode test session. */ + public GraphTestSession() { + graph = new Graph(); + session = new Session(graph); + tf = Ops.create(graph).withName("test"); + } + + /** {@inheritDoc} */ + @Override + public Ops getTF() { + return tf; + } + + /** Get the Graph object that is represented by this Test Session */ + public Graph getGraph() { + return graph; + } + + + /** + * Get the TensorFlow Session instance + * @return the TensorFlow Session instance + */ + public Session getSession() { + return session; + } + + /** {@inheritDoc} */ + @Override + public void close() { + session.close(); + graph.close(); + } + + /** {@inheritDoc} */ + @Override + public boolean isEager() { + return false; + } + + /** {@inheritDoc} */ + @Override + public Session getGraphSession() { + return this.session; + } + + /** {@inheritDoc} */ + @Override + public EagerSession getEagerSession() { + return null; + } + + /** {@inheritDoc} */ + @Override + public void initialize() { + graph + .initializers() + .forEach( + initializer -> { + session.runner().addTarget(initializer).run(); + }); + } + + /** {@inheritDoc} */ + @Override + public void run(Op op) { + session.run(op); + } + + /** {@inheritDoc} */ + @Override + public void evaluate(double expected, Operand input) { + DataType dtype = input.asOutput().dataType(); + if (dtype == TFloat32.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals((float) expected, f.getFloat(), epsilon); + }); + } + } else if (dtype == TFloat64.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected, f.getDouble(), epsilon); + }); + } + } else if (dtype == TInt32.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals((int) expected, f.getInt()); + }); + } + } else if (dtype == TInt64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals((long) expected, f.getLong()); + }); + } + } else { + fail("Unexpected DataType: " + dtype); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Number[] expected, Output input) { + int size = input.shape().size() == 0 ? 1 : (int) input.shape().size(); + assertEquals( + expected.length, + size, + () -> String.format("expected length (%d) != to input length (%d)", expected.length, size)); + DataType dtype = input.asOutput().dataType(); + if (dtype == TFloat32.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals( + expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon); + }); + } + } else if (dtype == TFloat64.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals( + expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon); + }); + } + } else if (dtype == TInt32.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt()); + }); + } + } else if (dtype == TInt64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong()); + }); + } + } else { + fail("Unexpected DataType: " + dtype); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(FloatNdArray expected, Output input) { + DataType dtype = input.asOutput().dataType(); + if (dtype == TFloat32.DTYPE) { + AtomicLong index = new AtomicLong(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon); + }); + } + } else if (dtype == TFloat64.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals( + (double) expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon); + }); + } + } else if (dtype == TInt32.DTYPE) { + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt()); + }); + } + } else if (dtype == TInt64.DTYPE) { + Output o = (Output) input; + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong()); + }); + } + } else { + fail("Unexpected DataType: " + dtype); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(String[] expected, Output input) { + int size = input.shape().size() == 0 ? 1 : (int) input.shape().size(); + assertEquals( + expected.length, + size, + () -> String.format("expected length (%d) != to input length (%d)", expected.length, size)); + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TString.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TString.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()], f.getObject()); + }); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Boolean[] expected, Output input) { + int size = input.shape().size() == 0 ? 1 : (int) input.shape().size(); + assertEquals( + expected.length, + size, + () -> String.format("expected length (%d) != to input length (%d)", expected.length, size)); + AtomicInteger index = new AtomicInteger(); + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TBool.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + System.out.printf("%d). %b\n", index.getAndIncrement(), f.getObject()); + }); + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TBool.DTYPE)) { + result + .data() + .scalars() + .forEach( + f -> { + assertEquals(expected[index.getAndIncrement()], f.getObject()); + }); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Output expected, Output input) { + assert input.shape().equals(expected.shape()) + : String.format( + "expected shape (%s) != to input shape (%ds)", + expected.shape().toString(), input.shape().toString()); + AtomicInteger index = new AtomicInteger(); + DataType dtype = input.asOutput().dataType(); + boolean isScalar = input.shape().equals(Shape.scalar()); + if (dtype == TFloat32.DTYPE) { + final Output finalExpected = (Output) expected; + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %f <==> %f\n", expectedResult.data().getFloat(), result.data().getFloat()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %f <==> %f\n", + index.getAndIncrement(), + finalExpected.data().getFloat(idx), + f.getFloat()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + if (isScalar) { + assertEquals(expectedResult.data().getFloat(), result.data().getFloat(), epsilon); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertEquals(expectedResult.data().getFloat(idx), f.getFloat(), epsilon); + }); + } + } + } else if (dtype == TFloat64.DTYPE) { + final Output finalExpected = (Output) expected; + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %f <==> %f\n", expectedResult.data().getDouble(), result.data().getDouble()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %f <==> %f\n", + index.getAndIncrement(), + finalExpected.data().getDouble(idx), + f.getDouble()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + if (isScalar) { + assertEquals(expectedResult.data().getDouble(), result.data().getDouble(), epsilon); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertEquals(expectedResult.data().getDouble(idx), f.getDouble(), epsilon); + }); + } + } + } else if (dtype == TInt32.DTYPE) { + final Output finalExpected = (Output) expected; + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %d <==> %d\n", expectedResult.data().getInt(), result.data().getInt()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %d <==> %d\n", + index.getAndIncrement(), finalExpected.data().getInt(idx), f.getInt()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + if (isScalar) { + assertEquals(expectedResult.data().getInt(), result.data().getInt(), epsilon); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertEquals(expectedResult.data().getInt(idx), f.getInt(), epsilon); + }); + } + } + } else if (dtype == TInt64.DTYPE) { + final Output finalExpected = (Output) expected; + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %d <==> %d\n", expectedResult.data().getLong(), result.data().getLong()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %d <==> %d\n", + index.getAndIncrement(), finalExpected.data().getLong(idx), f.getLong()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + if (isScalar) { + assertEquals(expectedResult.data().getLong(), result.data().getLong(), epsilon); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertEquals(expectedResult.data().getLong(idx), f.getLong(), epsilon); + }); + } + } + } else if (dtype == TBool.DTYPE) { + final Output finalExpected = (Output) expected; + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TBool.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TBool.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %b <==> %b\n", expectedResult.data().getBoolean(), result.data().getBoolean()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %b\n", + index.getAndIncrement(), + finalExpected.data().getBoolean(idx), + f.getBoolean()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TBool.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TBool.DTYPE)) { + if (isScalar) { + assertEquals(expectedResult.data().getBoolean(), result.data().getBoolean()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertEquals(expectedResult.data().getBoolean(idx), f.getBoolean()); + }); + } + } + } else if (dtype == TString.DTYPE) { + final Output finalExpected = (Output) expected; + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TString.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TString.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %s <==> %s\n", expectedResult.data().getObject(), result.data().getObject()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %s <==> %s\n", + index.getAndIncrement(), + finalExpected.data().getObject(idx), + f.getObject()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TString.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TString.DTYPE)) { + if (isScalar) { + assertEquals(expectedResult.data().getObject(), result.data().getObject()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertEquals(expectedResult.data().getObject(idx), f.getObject()); + }); + } + } + } else { + fail("Unexpected DataType: " + dtype); + } + } + + /** {@inheritDoc} */ + @Override + public void evaluate(Output input, Predicate predicate) { + AtomicInteger index = new AtomicInteger(); + DataType dtype = input.asOutput().dataType(); + boolean isScalar = input.shape().equals(Shape.scalar()); + if (dtype == TFloat32.DTYPE) { + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %b <==> %f\n", + predicate.test(result.data().getFloat()), result.data().getFloat()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %f\n", + index.getAndIncrement(), predicate.test(f.getFloat()), f.getFloat()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + if (isScalar) { + assertTrue(predicate.test(result.data().getFloat())); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(result.data().getFloat())); + }); + } + } + } else if (dtype == TFloat64.DTYPE) { + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %b <==> %f\n", + predicate.test(result.data().getDouble()), result.data().getDouble()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %f\n", + index.getAndIncrement(), predicate.test(f.getDouble()), f.getDouble()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + if (isScalar) { + assertTrue(predicate.test(result.data().getDouble())); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(result.data().getDouble())); + }); + } + } + } else if (dtype == TInt32.DTYPE) { + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %b <==> %d\n", predicate.test(result.data().getInt()), result.data().getInt()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %d\n", + index.getAndIncrement(), predicate.test(f.getInt()), f.getInt()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + if (isScalar) { + assertTrue(predicate.test(result.data().getInt())); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(result.data().getInt())); + }); + } + } + } else if (dtype == TInt64.DTYPE) { + if (debug) { + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + if (isScalar) { + System.out.printf( + "0). %b <==> %d\n", + predicate.test(result.data().getLong()), result.data().getLong()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + System.out.printf( + "%d). %b <==> %d\n", + index.getAndIncrement(), predicate.test(f.getLong()), f.getLong()); + }); + } + } + } + index.set(0); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE); + Tensor expectedResult = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + if (isScalar) { + assertTrue(predicate.test(result.data().getLong())); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + assertTrue(predicate.test(result.data().getLong())); + }); + } + } + } else { + fail("Unexpected DataType: " + dtype); + } + } + + /** {@inheritDoc} */ + @Override + public void print(PrintWriter writer, Output input) { + boolean isScalar = input.asOutput().shape().size() == 1; + + DataType dtype = input.dataType(); + if (dtype == TFloat32.DTYPE) { + AtomicInteger index = new AtomicInteger(); + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) { + if (isScalar) { + writer.printf("%d). %f\n", index.getAndIncrement(), result.data().getFloat()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + writer.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()); + }); + } + } + } else if (dtype == TFloat64.DTYPE) { + AtomicInteger index = new AtomicInteger(); + + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) { + if (isScalar) { + writer.printf( + "%d). %f\n", index.getAndIncrement(), ((Output) input).data().getDouble()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + writer.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()); + }); + } + } + } else if (dtype == TInt32.DTYPE) { + AtomicInteger index = new AtomicInteger(); + + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) { + if (isScalar) { + writer.printf( + "%d). %f\n", index.getAndIncrement(), ((Output) input).data().getInt()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + writer.printf("%d). %d\n", index.getAndIncrement(), f.getInt()); + }); + } + } + } else if (dtype == TInt64.DTYPE) { + AtomicInteger index = new AtomicInteger(); + + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) { + if (isScalar) { + writer.printf( + "%d). %f\n", index.getAndIncrement(), ((Output) input).data().getLong()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + writer.printf("%d). %d\n", index.getAndIncrement(), f.getLong()); + }); + } + } + } else if (dtype == TBool.DTYPE) { + AtomicInteger index = new AtomicInteger(); + + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TBool.DTYPE)) { + if (isScalar) { + writer.printf( + "%d). %b\n", index.getAndIncrement(), ((Output) input).data().getBoolean()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + writer.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()); + }); + } + } + } else if (dtype == TString.DTYPE) { + AtomicInteger index = new AtomicInteger(); + + try (Tensor result = + this.getGraphSession().runner().fetch(input).run().get(0).expect(TString.DTYPE)) { + if (isScalar) { + writer.printf( + "%d). %s\n", index.getAndIncrement(), ((Output) input).data().getObject()); + } else { + result + .data() + .scalars() + .forEachIndexed( + (idx, f) -> { + writer.printf("%d). %s\n", index.getAndIncrement(), f.getObject()); + }); + } + } + } else { + writer.println("Unexpected DataType: " + dtype); + } + writer.flush(); + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java new file mode 100644 index 00000000000..1aaa4aa7af4 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java @@ -0,0 +1,247 @@ +/* Copyright 2020 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.keras.utils; + +import java.util.function.Supplier; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.Graph; +import org.tensorflow.Operand; +import org.tensorflow.Session; +import org.tensorflow.Tensor; +import org.tensorflow.op.Ops; +import org.tensorflow.op.core.Constant; +import org.tensorflow.types.TBool; + +/** + * + * @author Jim Clarke + */ +public class SmartCondTest { + + public SmartCondTest() { + } + + @BeforeAll + public static void setUpClass() { + } + + @AfterAll + public static void tearDownClass() { + } + + @BeforeEach + public void setUp() { + } + + @AfterEach + public void tearDown() { + } + + /** + * Test of cond method, of class SmartCond. + */ + @Test + public void testCondOp() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + Constant pred = tf.constant(true); + sess.run(pred); + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = true; + Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + + } + } + + @Test + public void testCondOp2() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + Constant pred = tf.constant(true); + sess.run(pred); + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = true; + Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + + } + } + + @Test + public void testCondOpPoint1() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + Operand pred = tf.math.equal(tf.constant(0.1), tf.constant(1.0)); + sess.run(pred); + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = false; + Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + } + } + + @Test + public void testCondOpString() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + Operand pred = tf.math.equal(tf.constant("TRUE"), tf.constant("TRUE")); + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = true; + Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + } + } + + /** + * Test of cond method, of class SmartCond. + */ + @Test + public void testCondBoolean() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + boolean pred = false; + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = false; + Operand resultOp = SmartCond.select(pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + + } + } + + /** + * Test of cond method, of class SmartCond. + */ + @Test + public void testCondInt() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + int pred = 1; + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = true; + Operand resultOp = SmartCond.select(pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + + } + } + + /** + * Test of cond method, of class SmartCond. + */ + @Test + public void testCondFloat1() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + float pred = 1.0F; + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = true; + Operand resultOp = SmartCond.select(pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + + } + } + + /** + * Test of cond method, of class SmartCond. + */ + @Test + public void testCondFloat0_1() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + float pred = 0.1F; + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = false; + Operand resultOp = SmartCond.select(pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + + } + } + + /** + * Test of cond method, of class SmartCond. + */ + @Test + public void testCondString() { + try (Graph graph = new Graph(); Session sess = new Session(graph)) { + Ops tf = Ops.create(graph).withName("test"); + String pred = "true"; + + Supplier true_fn = () -> tf.constant(true); + Supplier false_fn = () -> tf.constant(false); + boolean expResult = true; + Operand resultOp = SmartCond.select(pred, true_fn, false_fn); + boolean actualResult; + try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) { + actualResult = result.data().getBoolean(); + assertEquals(expResult, actualResult); + } + + } + } + +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TestSession.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TestSession.java new file mode 100644 index 00000000000..1e5393aa2af --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TestSession.java @@ -0,0 +1,618 @@ +/* Copyright 2020 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.keras.utils; + +import java.io.OutputStream; +import java.io.OutputStreamWriter; +import java.io.PrintWriter; +import java.io.Writer; +import java.util.function.Predicate; +import static org.junit.jupiter.api.Assertions.assertTrue; +import org.tensorflow.EagerSession; +import org.tensorflow.Operand; +import org.tensorflow.Output; +import org.tensorflow.Session; +import org.tensorflow.ndarray.FloatNdArray; +import org.tensorflow.op.Op; +import org.tensorflow.op.Ops; +import org.tensorflow.types.TBool; +import org.tensorflow.types.TString; +import org.tensorflow.types.family.TNumber; +import org.tensorflow.types.family.TType; + +/** Base class for Test Session */ +public abstract class TestSession implements AutoCloseable { + + protected float epsilon = 1e-5F; + protected boolean debug; + + /** The Test Session mode, either Eager or Graph */ + public enum Mode { + EAGER, + GRAPH; + } + + /** + * Create an Eager Test Session + * + * @return the Eager Test Session + */ + public static TestSession createEagerSession() { + return new EagerTestSession(); + } + + /** + * Create a Graph Test Session + * + * @return the Graph Test Session + */ + public static TestSession createGraphSession() { + return new GraphTestSession(); + } + + /** + * Create a Test Session + * + * @param mode + * @return + */ + public static TestSession createTestSession(Mode mode) { + return mode == Mode.EAGER ? createEagerSession() : createGraphSession(); + } + + /** Initialize the Test Session, default implementation is do nothing. */ + public void initialize() { + // empty + } + + /** + * Run the Operation + * + * @param op the Operation to run + */ + public void run(Op op) { + // empty + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Number expected, Operand input) { + evaluate(new Number[] {expected}, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Number expected, Op input) { + evaluate(new Number[] {expected}, input); + } + + /** + * Evaluate the input against the expected values + * + * @param expected the expected values + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Number[] expected, Op input) { + Output output = input.op().output(0); + evaluate(expected, output); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Number[] expected, Operand input) { + Output output = input.asOutput(); + evaluate(expected, output); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(byte expected, Operand input) { + evaluate((double) expected, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(int expected, Operand input) { + evaluate((double) expected, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(long expected, Operand input) { + evaluate((double) expected, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(float expected, Operand input) { + evaluate((double) expected, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public abstract void evaluate(double expected, Operand input); + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(byte[] expected, Operand input) { + Byte[] iArray = new Byte[expected.length]; + for (int i = 0; i < expected.length; i++) iArray[i] = expected[i]; + evaluate(iArray, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(int[] expected, Operand input) { + Integer[] iArray = new Integer[expected.length]; + for (int i = 0; i < expected.length; i++) iArray[i] = expected[i]; + evaluate(iArray, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(long[] expected, Operand input) { + Long[] iArray = new Long[expected.length]; + for (int i = 0; i < expected.length; i++) iArray[i] = expected[i]; + evaluate(iArray, input); + } + + /** + * Evaluate the input against the expected values + * + * @param expected the expected values + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(float[] expected, Operand input) { + Float[] iArray = new Float[expected.length]; + for (int i = 0; i < expected.length; i++) iArray[i] = expected[i]; + evaluate(iArray, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(double[] expected, Operand input) { + Double[] iArray = new Double[expected.length]; + for (int i = 0; i < expected.length; i++) iArray[i] = expected[i]; + evaluate(iArray, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public abstract void evaluate(Number[] expected, Output input); + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(String expected, Operand input) { + evaluate(new String[] {expected}, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(String expected, Op input) { + evaluate(new String[] {expected}, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(String[] expected, Op input) { + Output output = input.op().output(0); + evaluate(expected, output); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(String[] expected, Operand input) { + Output output = input.asOutput(); + evaluate(expected, output); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public abstract void evaluate(String[] expected, Output input); + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Boolean expected, Operand input) { + evaluate(new Boolean[] {expected}, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Boolean expected, Op input) { + evaluate(new Boolean[] {expected}, input); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Boolean[] expected, Op input) { + Output output = input.op().output(0); + evaluate(expected, output); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Boolean[] expected, Operand input) { + Output output = input.asOutput(); + evaluate(expected, output); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public abstract void evaluate(Boolean[] expected, Output input); + + public void evaluate(Operand expected, Op input) { + Output output = input.op().output(0); + evaluate(expected, output); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(Operand expected, Operand input) { + evaluate(expected.asOutput(), input.asOutput()); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public abstract void evaluate(Output expected, Output input); + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(FloatNdArray expected, Operand input) { + evaluate(expected, input.asOutput()); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public abstract void evaluate(FloatNdArray expected, Output input); + + public void evaluate(Operand input, Predicate predicate) { + evaluate(input.asOutput(), predicate); + } + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public abstract void evaluate(Output input, Predicate predicate); + + /** + * Evaluate the input against the expected value + * + * @param expected the expected value + * @param input the operand to evaluate + * @param the data type of the input + * @throws org.opentest4j.AssertionFailedError + */ + public void evaluate(FloatNdArray input, Predicate predicate) { + input.scalars().forEach(f -> assertTrue(predicate.test(f.getFloat()))); + } + + /** + * Print the input + * + * @param out the output stream + * @param input the operand to print + * @param the data type of the input + */ + public void print(OutputStream out, Operand input) { + print(new PrintWriter(new OutputStreamWriter(out)), input.asOutput()); + } + + /** + * Print the input + * + * @param out the output stream + * @param input the op to print + * @param the data type of the input + */ + public void print(OutputStream out, Op input) { + print(new PrintWriter(new OutputStreamWriter(out)), input.op().output(0)); + } + + /** + * Print the input + * + * @param out the output stream + * @param input the op to print + * @param the data type of the input + */ + public void print(OutputStream out, Output input) { + print(new PrintWriter(new OutputStreamWriter(out)), input); + } + + /** + * Print the input + * + * @param witer the output writer + * @param input the operand to print + * @param the data type of the input + */ + public void print(Writer writer, Operand input) { + print(new PrintWriter(writer), input.asOutput()); + } + + /** + * Print the input + * + * @param witer the output writer + * @param input the op to print + * @param the data type of the input + */ + public void print(Writer writer, Op input) { + print(new PrintWriter(writer), input.op().output(0)); + } + + /** + * Print the input + * + * @param witer the output writer + * @param input the op to print + * @param the data type of the input + */ + public void print(Writer writer, Output input) { + print(new PrintWriter(writer), input); + } + + /** + * Print the input + * + * @param witer the output writer + * @param input the op to print + */ + public abstract void print(PrintWriter writer, Output input); + + /** + * Get the TensorFlow Ops + * + * @return the TensorFlow Ops + */ + public abstract Ops getTF(); + + /** + * Determine if this Test Session represents an Eager Session + * + * @return true, if this Test Session represents an Eager Session + */ + public abstract boolean isEager(); + + /** + * Determine if this Test Session represents a Graph Session + * + * @return true, if this Test Session represents a Graph Session + */ + public boolean isGraph() { + return !isEager(); + } + + /** + * Get the epsilon value for evaluating float values + * + * @return the epsilon value for evaluating float values + */ + public float getEpsilon() { + return this.epsilon; + } + + /** + * Set the epsilon value for evaluating float values + * + * @param epsilon the epsilon value for evaluating float values + */ + public void setEpsilon(float epsilon) { + this.epsilon = epsilon; + } + + /** + * Get the TensorFlow session object associated with this Test Session + * + * @return a TensorFlow session if this is a Graph session, otherwise null + */ + public abstract Session getGraphSession(); + + /** + * Get the TensorFlow eager session object associated with this Test Session + * + * @return a TensorFlow session if this is an eager session, otherwise null + */ + public abstract EagerSession getEagerSession(); + + /** {@inheritDoc} */ + @Override + public abstract void close(); + + /** @return the debug setting */ + public boolean isDebug() { + return debug; + } + + /** + * Set the debug flag + * + * @param debug the setting for debugging + */ + public void setDebug(boolean debug) { + this.debug = debug; + } +} diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java new file mode 100644 index 00000000000..18442961ac5 --- /dev/null +++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java @@ -0,0 +1,234 @@ +/* Copyright 2020 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.keras.utils; + +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import static org.junit.jupiter.api.Assertions.*; +import org.tensorflow.DataType; +import org.tensorflow.types.TBfloat16; +import org.tensorflow.types.TBool; +import org.tensorflow.types.TFloat16; +import org.tensorflow.types.TFloat32; +import org.tensorflow.types.TFloat64; +import org.tensorflow.types.TInt32; +import org.tensorflow.types.TInt64; +import org.tensorflow.types.TString; +import org.tensorflow.types.TUint8; + +/** + * + * @author Jim Clarke + */ +public class TypeUtilTest { + + public TypeUtilTest() { + } + + @BeforeAll + public static void setUpClass() { + } + + @AfterAll + public static void tearDownClass() { + } + + @BeforeEach + public void setUp() { + } + + @AfterEach + public void tearDown() { + } + + /** + * Test of isFloating method, of class TypeUtils. + */ + @Test + public void testIsFloating() { + DataType dtype = TFloat32.DTYPE; + boolean expResult = true; + boolean result = TypeUtils.isFloating(dtype); + assertEquals(expResult, result); + + dtype = TInt32.DTYPE; + expResult = false; + result = TypeUtils.isFloating(dtype); + assertEquals(expResult, result); + + dtype = TString.DTYPE; + expResult = false; + result = TypeUtils.isFloating(dtype); + assertEquals(expResult, result); + } + + /** + * Test of isInteger method, of class TypeUtils. + */ + @Test + public void testIsInteger() { + DataType dtype = TFloat32.DTYPE; + boolean expResult = false; + boolean result = TypeUtils.isInteger(dtype); + assertEquals(expResult, result); + + dtype = TInt32.DTYPE; + expResult = true; + result = TypeUtils.isInteger(dtype); + assertEquals(expResult, result); + + dtype = TString.DTYPE; + expResult = false; + result = TypeUtils.isInteger(dtype); + assertEquals(expResult, result); + } + + /** + * Test of isNumeric method, of class TypeUtils. + */ + @Test + public void testIsNumeric() { + DataType dtype = TFloat16.DTYPE; + boolean expResult = true; + boolean result = TypeUtils.isNumeric(dtype); + assertEquals(expResult, result); + + dtype = TInt64.DTYPE; + expResult = true; + result = TypeUtils.isNumeric(dtype); + assertEquals(expResult, result); + + dtype = TUint8.DTYPE; + expResult = true; + result = TypeUtils.isNumeric(dtype); + assertEquals(expResult, result); + + dtype = TBool.DTYPE; + expResult = false; + result = TypeUtils.isNumeric(dtype); + assertEquals(expResult, result); + + dtype = TString.DTYPE; + expResult = false; + result = TypeUtils.isNumeric(dtype); + assertEquals(expResult, result); + } + + /** + * Test of isBoolean method, of class TypeUtils. + */ + @Test + public void testIsBoolean() { + DataType dtype = TFloat16.DTYPE; + boolean expResult = false; + boolean result = TypeUtils.isBoolean(dtype); + assertEquals(expResult, result); + + dtype = TInt64.DTYPE; + expResult = false; + result = TypeUtils.isBoolean(dtype); + assertEquals(expResult, result); + + dtype = TBool.DTYPE; + expResult = true; + result = TypeUtils.isBoolean(dtype); + assertEquals(expResult, result); + } + + /** + * Test of isString method, of class TypeUtils. + */ + @Test + public void testIsString() { + DataType dtype = TFloat16.DTYPE; + boolean expResult = false; + boolean result = TypeUtils.isString(dtype); + assertEquals(expResult, result); + + dtype = TBool.DTYPE; + expResult = false; + result = TypeUtils.isString(dtype); + assertEquals(expResult, result); + + dtype = TString.DTYPE; + expResult = true; + result = TypeUtils.isString(dtype); + assertEquals(expResult, result); + } + + /** + * Test of of method, of class TypeUtils. + */ + @Test + public void testOf() { + String name = "BFLOAT16"; + DataType expResult = TBfloat16.DTYPE; + DataType result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "FLOAT16"; + expResult = TFloat16.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "FLOAT"; + expResult = TFloat32.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "DOUBLE"; + expResult = TFloat64.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "UINT8"; + expResult = TUint8.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "INT32"; + expResult = TInt32.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "INT64"; + expResult = TInt64.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "BOOL"; + expResult = TBool.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "STRING"; + expResult = TString.DTYPE; + result = TypeUtils.of(name); + assertEquals(expResult, result); + + name = "FOO"; + try { + TypeUtils.of(name); + fail("IllegalArgumentException not thrown."); + } catch (IllegalArgumentException expected) { + + } + + } + +} From 9c113a7e6dfcc98c0e57bede8dcb46de56125320 Mon Sep 17 00:00:00 2001 From: Jim Clarke Date: Thu, 20 Aug 2020 08:12:27 -0400 Subject: [PATCH 02/33] Added static final NAME to replace hardcoded String in the create method. This allows the NAME to be used elsewhere instead of hardcoding the string. --- .../java/org/tensorflow/types/TBfloat16.java | 29 ++++++----- .../main/java/org/tensorflow/types/TBool.java | 13 +++-- .../java/org/tensorflow/types/TFloat16.java | 28 +++++----- .../java/org/tensorflow/types/TFloat32.java | 14 +++-- .../java/org/tensorflow/types/TFloat64.java | 13 +++-- .../java/org/tensorflow/types/TInt32.java | 13 +++-- .../java/org/tensorflow/types/TInt64.java | 13 +++-- .../java/org/tensorflow/types/TString.java | 52 +++++++++---------- .../java/org/tensorflow/types/TUint8.java | 13 +++-- 9 files changed, 92 insertions(+), 96 deletions(-) diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java index 531bedc5e40..faf698a6fe5 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java @@ -36,21 +36,24 @@ * Brain 16-bit float tensor type. * *

This type differs from {@link TFloat16} as it truncates the mantissa of a 32-bit float and - * preserve all exponent bits for faster conversion, while the latter shrink the exponent and have - * a longer mantissa for more precision. + * preserve all exponent bits for faster conversion, while the latter shrink the exponent and have a + * longer mantissa for more precision. * - *

Since there is no floating-point type that fits in 16 bits in Java, a conversion (with potentially - * a precision loss) is required for each 32 bits value written or read on a tensor of this type from - * the JVM. Therefore, if a lot of I/O operations are to be expected on a tensor, performances will be - * improved by working with {@link TFloat32} or {@link TFloat64} data types whenever possible. + *

Since there is no floating-point type that fits in 16 bits in Java, a conversion (with + * potentially a precision loss) is required for each 32 bits value written or read on a tensor of + * this type from the JVM. Therefore, if a lot of I/O operations are to be expected on a tensor, + * performances will be improved by working with {@link TFloat32} or {@link TFloat64} data types + * whenever possible. * - *

Note that some CPUs support the bfloat16 format natively, which can result in faster computation - * compared to {@link TFloat16} when GPUs are not used. + *

Note that some CPUs support the bfloat16 format natively, which can result in faster + * computation compared to {@link TFloat16} when GPUs are not used. */ public interface TBfloat16 extends FloatNdArray, TNumber { + /** readable-name for the data type */ + static final String NAME = "BFLOAT16"; /** Type metadata */ - DataType DTYPE = DataType.create("BFLOAT16", 14, 2, TBfloat16Impl::mapTensor); + DataType DTYPE = DataType.create(NAME, 14, 2, TBfloat16Impl::mapTensor); /** * Allocates a new tensor for storing a single float value. @@ -121,17 +124,15 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) { } } -/** - * Hidden implementation of a {@code TBfloat16} - */ +/** Hidden implementation of a {@code TBfloat16} */ class TBfloat16Impl extends FloatDenseNdArray implements TBfloat16 { static TBfloat16 mapTensor(TF_Tensor nativeTensor, Shape shape) { - return new TBfloat16Impl(DataLayouts.BFLOAT16.applyTo(TensorBuffers.toShorts(nativeTensor)), shape); + return new TBfloat16Impl( + DataLayouts.BFLOAT16.applyTo(TensorBuffers.toShorts(nativeTensor)), shape); } private TBfloat16Impl(FloatDataBuffer buffer, Shape shape) { super(buffer, shape); } } - diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java index 835d0a1be31..bac5fb96f87 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java @@ -36,14 +36,15 @@ * Boolean tensor type. * *

If direct memory mapping is not available in the JVM, tensors of this type might require an - * explicit mapping between Java boolean values and byte buffers using the - * {@link DataLayouts#BOOL BOOL} layout, which may impact I/O - * performances. + * explicit mapping between Java boolean values and byte buffers using the {@link DataLayouts#BOOL + * BOOL} layout, which may impact I/O performances. */ public interface TBool extends BooleanNdArray, TType { + /** readable-name for the data type */ + static final String NAME = "BOOL"; /** Type metadata */ - DataType DTYPE = DataType.create("BOOL", 10, 1, TBoolImpl::mapTensor); + DataType DTYPE = DataType.create(NAME, 10, 1, TBoolImpl::mapTensor); /** * Allocates a new tensor for storing a single boolean value. @@ -114,9 +115,7 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) { } } -/** - * Hidden implementation of a {@code TBool} - */ +/** Hidden implementation of a {@code TBool} */ class TBoolImpl extends BooleanDenseNdArray implements TBool { static TBool mapTensor(TF_Tensor nativeTensor, Shape shape) { diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java index 3f0deb00d0f..6ce463ff2c0 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java @@ -35,19 +35,23 @@ /** * IEEE-754 half-precision 16-bit float tensor type. * - *

Since there is no floating-point type that fits in 16 bits in Java, a conversion (with potentially - * a precision loss) is required for each 32 bits value written or read on a tensor of this type from - * the JVM. Therefore, if a lot of I/O operations are to be expected on a tensor, performances will be - * improved by working with {@link TFloat32} or {@link TFloat64} data types whenever possible. + *

Since there is no floating-point type that fits in 16 bits in Java, a conversion (with + * potentially a precision loss) is required for each 32 bits value written or read on a tensor of + * this type from the JVM. Therefore, if a lot of I/O operations are to be expected on a tensor, + * performances will be improved by working with {@link TFloat32} or {@link TFloat64} data types + * whenever possible. * - *

Also, {@code TFloat16} tensors normally perform better if they are located in GPU memory since most - * CPUs do not support this format natively. For CPU computation on 16-bit floats, the {@link TBfloat16} - * tensor type might be a better option. + *

Also, {@code TFloat16} tensors normally perform better if they are located in GPU memory since + * most CPUs do not support this format natively. For CPU computation on 16-bit floats, the {@link + * TBfloat16} tensor type might be a better option. */ public interface TFloat16 extends FloatNdArray, TNumber { + /** readable-name for the data type */ + static final String NAME = "FLOAT16"; + /** Type metadata */ - DataType DTYPE = DataType.create("FLOAT16", 19, 2, TFloat16Impl::mapTensor); + DataType DTYPE = DataType.create(NAME, 19, 2, TFloat16Impl::mapTensor); /** * Allocates a new tensor for storing a single float value. @@ -118,17 +122,15 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) { } } -/** - * Hidden implementation of a {@code TFloat16} - */ +/** Hidden implementation of a {@code TFloat16} */ class TFloat16Impl extends FloatDenseNdArray implements TFloat16 { static TFloat16 mapTensor(TF_Tensor nativeTensor, Shape shape) { - return new TFloat16Impl(DataLayouts.FLOAT16.applyTo(TensorBuffers.toShorts(nativeTensor)), shape); + return new TFloat16Impl( + DataLayouts.FLOAT16.applyTo(TensorBuffers.toShorts(nativeTensor)), shape); } private TFloat16Impl(FloatDataBuffer buffer, Shape shape) { super(buffer, shape); } } - diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java index 4b06ad2d57e..968b3f2a539 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java @@ -31,13 +31,14 @@ import org.tensorflow.ndarray.impl.dense.FloatDenseNdArray; import org.tensorflow.types.family.TNumber; -/** - * IEEE-754 single-precision 32-bit float tensor type. - */ +/** IEEE-754 single-precision 32-bit float tensor type. */ public interface TFloat32 extends FloatNdArray, TNumber { + /** readable-name for the data type */ + static final String NAME = "FLOAT"; + /** Type metadata */ - DataType DTYPE = DataType.create("FLOAT", 1, 4, TFloat32Impl::mapTensor); + DataType DTYPE = DataType.create(NAME, 1, 4, TFloat32Impl::mapTensor); /** * Allocates a new tensor for storing a single float value. @@ -108,9 +109,7 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) { } } -/** - * Hidden implementation of a {@code TFloat32} - */ +/** Hidden implementation of a {@code TFloat32} */ class TFloat32Impl extends FloatDenseNdArray implements TFloat32 { static TFloat32 mapTensor(TF_Tensor nativeTensor, Shape shape) { @@ -121,4 +120,3 @@ private TFloat32Impl(FloatDataBuffer buffer, Shape shape) { super(buffer, shape); } } - diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java index 0b2109ac374..9cf5fdaaeaa 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java @@ -31,13 +31,14 @@ import org.tensorflow.ndarray.impl.dense.DoubleDenseNdArray; import org.tensorflow.types.family.TNumber; -/** - * IEEE-754 double-precision 64-bit float tensor type. - */ +/** IEEE-754 double-precision 64-bit float tensor type. */ public interface TFloat64 extends DoubleNdArray, TNumber { + /** readable-name for the data type */ + static final String NAME = "DOUBLE"; + /** Type metadata */ - DataType DTYPE = DataType.create("DOUBLE", 2, 8, TFloat64Impl::mapTensor); + DataType DTYPE = DataType.create(NAME, 2, 8, TFloat64Impl::mapTensor); /** * Allocates a new tensor for storing a single double value. @@ -108,9 +109,7 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) { } } -/** - * Hidden implementation of a {@code TFloat64} - */ +/** Hidden implementation of a {@code TFloat64} */ class TFloat64Impl extends DoubleDenseNdArray implements TFloat64 { static TFloat64 mapTensor(TF_Tensor nativeTensor, Shape shape) { diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java index ac0dbec1d42..4a1139ddde2 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java @@ -30,13 +30,14 @@ import org.tensorflow.ndarray.impl.dense.IntDenseNdArray; import org.tensorflow.types.family.TNumber; -/** - * 32-bit signed integer tensor type. - */ +/** 32-bit signed integer tensor type. */ public interface TInt32 extends IntNdArray, TNumber { + /** readable-name for the data type */ + static final String NAME = "INT32"; + /** Type metadata */ - DataType DTYPE = DataType.create("INT32", 3, 4, TInt32Impl::mapTensor); + DataType DTYPE = DataType.create(NAME, 3, 4, TInt32Impl::mapTensor); /** * Allocates a new tensor for storing a single int value. @@ -107,9 +108,7 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) { } } -/** - * Hidden implementation of a {@code TInt32} - */ +/** Hidden implementation of a {@code TInt32} */ class TInt32Impl extends IntDenseNdArray implements TInt32 { static TInt32 mapTensor(TF_Tensor nativeTensor, Shape shape) { diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java index bbe05f9b1ff..04fd4fd7799 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java @@ -31,13 +31,14 @@ import org.tensorflow.ndarray.impl.dense.LongDenseNdArray; import org.tensorflow.types.family.TNumber; -/** - * 64-bit signed integer tensor type. - */ +/** 64-bit signed integer tensor type. */ public interface TInt64 extends LongNdArray, TNumber { + /** readable-name for the data type */ + static final String NAME = "INT64"; + /** Type metadata */ - DataType DTYPE = DataType.create("INT64", 9, 8, TInt64Impl::mapTensor); + DataType DTYPE = DataType.create(NAME, 9, 8, TInt64Impl::mapTensor); /** * Allocates a new tensor for storing a single long value. @@ -108,9 +109,7 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) { } } -/** - * Hidden implementation of a {@code TInt64} - */ +/** Hidden implementation of a {@code TInt64} */ class TInt64Impl extends LongDenseNdArray implements TInt64 { static TInt64 mapTensor(TF_Tensor nativeTensor, Shape shape) { diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java index 90ae4ef9cb8..0f097a16ddb 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java @@ -40,15 +40,16 @@ *

This type can be used to store any arbitrary byte sequence of variable length. * *

Since the size of a tensor is fixed, creating a tensor of this type requires to provide all of - * its values initially, so TensorFlow can compute and allocate the right amount of memory. Then - * the data in the tensor is initialized once and cannot be modified afterwards. + * its values initially, so TensorFlow can compute and allocate the right amount of memory. Then the + * data in the tensor is initialized once and cannot be modified afterwards. */ public interface TString extends NdArray, TType { - /** - * Type metadata - */ - DataType DTYPE = DataType.create("STRING", 7, -1, TStringImpl::mapTensor); + /** readable-name for the data type */ + static final String NAME = "STRING"; + + /** Type metadata */ + DataType DTYPE = DataType.create(NAME, 7, -1, TStringImpl::mapTensor); /** * Allocates a new tensor for storing a string scalar. @@ -96,8 +97,8 @@ static Tensor tensorOf(NdArray src) { *

The tensor will have the same shape as the source array and its data will be copied. The * strings are encoded into bytes using the charset passed in parameter. * - *

If charset is different than default UTF-8, then it must also be provided explicitly - * when reading data from the tensor, using {@link #using(Charset)}:

+ *

If charset is different than default UTF-8, then it must also be provided explicitly when + * reading data from the tensor, using {@link #using(Charset)}: * * 

{@code
    * // Given `originalStrings` an initialized vector of strings
@@ -135,8 +136,8 @@ static Tensor tensorOf(Shape shape, DataBuffer data) {
    * 
The data will be copied from the provided buffer to the tensor after it is allocated. The
    * strings are encoded into bytes using the charset passed in parameter.
    *
-   * 
If charset is different than default UTF-8, then it must also be provided explicitly
-   * when reading data from the tensor, using {@link #using(Charset)}:

+   * 
If charset is different than default UTF-8, then it must also be provided explicitly when
+   * reading data from the tensor, using {@link #using(Charset)}:
    *
    * 
{@code
    * // Given `originalStrings` an initialized buffer of strings
@@ -161,8 +162,8 @@ static Tensor tensorOf(Charset charset, Shape shape, DataBuffer
    *
    * 
The tensor will have the same shape as the source array and its data will be copied.
    *
-   * 
If data must be read as raw bytes as well, the user must specify it explicitly by
-   * invoking {@link #asBytes()} on the returned data:

+   * 
If data must be read as raw bytes as well, the user must specify it explicitly by invoking
+   * {@link #asBytes()} on the returned data:
    *
    * 
{@code
    * byte[] bytes = tensor.data().asBytes().getObject(0);  // returns first sequence of bytes in the tensor
@@ -180,8 +181,8 @@ static Tensor tensorOfBytes(NdArray src) {
    *
    * 
The data will be copied from the provided buffer to the tensor after it has been allocated.
    *
-   * 
If data must be read as raw bytes as well, the user must specify it explicitly by
-   * invoking {@link #asBytes()} on the returned data:

+   * 
If data must be read as raw bytes as well, the user must specify it explicitly by invoking
+   * {@link #asBytes()} on the returned data:
    *
    * 
{@code
    * byte[] bytes = tensor.data().asBytes().getObject(0);  // returns first sequence of bytes in the tensor
@@ -212,15 +213,11 @@ static Tensor tensorOfBytes(Shape shape, DataBuffer data) {
    */
   TString using(Charset charset);
 
-  /**
-   * @return the tensor data as a n-dimensional array of raw byte sequences.
-   */
+  /** @return the tensor data as a n-dimensional array of raw byte sequences. */
   NdArray asBytes();
 }
 
-/**
- * Hidden implementation of a {@code TString}
- */
+/** Hidden implementation of a {@code TString} */
 class TStringImpl extends DenseNdArray implements TString {
 
   @Override
@@ -235,9 +232,11 @@ public NdArray asBytes() {
 
   static  Tensor createTensor(NdArray src, Function getBytes) {
     long size = StringTensorBuffer.computeSize(src, getBytes);
-    return Tensor.of(TString.DTYPE, src.shape(), size, data ->
-        ((TStringImpl)data).tensorBuffer.init(src, getBytes)
-    );
+    return Tensor.of(
+        TString.DTYPE,
+        src.shape(),
+        size,
+        data -> ((TStringImpl) data).tensorBuffer.init(src, getBytes));
   }
 
   static TString mapTensor(TF_Tensor nativeTensor, Shape shape) {
@@ -245,13 +244,14 @@ static TString mapTensor(TF_Tensor nativeTensor, Shape shape) {
     return new TStringImpl(buffer, UTF_8_LAYOUT, shape);
   }
 
-  private static DataLayout, String> UTF_8_LAYOUT = DataLayouts.ofStrings(StandardCharsets.UTF_8);
+  private static DataLayout, String> UTF_8_LAYOUT =
+      DataLayouts.ofStrings(StandardCharsets.UTF_8);
 
   private final StringTensorBuffer tensorBuffer;
 
-  private TStringImpl(StringTensorBuffer buffer, DataLayout, String> layout, Shape shape) {
+  private TStringImpl(
+      StringTensorBuffer buffer, DataLayout, String> layout, Shape shape) {
     super(layout.applyTo(buffer), shape);
     tensorBuffer = buffer;
   }
 }
-
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
index f55959194e5..365f41196fb 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
@@ -31,13 +31,14 @@
 import org.tensorflow.ndarray.impl.dense.ByteDenseNdArray;
 import org.tensorflow.types.family.TNumber;
 
-/**
- * 8-bit unsigned integer tensor type.
- */
+/** 8-bit unsigned integer tensor type. */
 public interface TUint8 extends ByteNdArray, TNumber {
 
+  /** readable-name for the data type */
+  static final String NAME = "UINT8";
+
   /** Type metadata */
-  DataType DTYPE = DataType.create("UINT8", 4, 1, TUint8Impl::mapTensor);
+  DataType DTYPE = DataType.create(NAME, 4, 1, TUint8Impl::mapTensor);
 
   /**
    * Allocates a new tensor for storing a single byte value.
@@ -108,9 +109,7 @@ static Tensor tensorOf(Shape shape, Consumer dataInit) {
   }
 }
 
-/**
- * Hidden implementation of a {@code TUint8}
- */
+/** Hidden implementation of a {@code TUint8} */
 class TUint8Impl extends ByteDenseNdArray implements TUint8 {
 
   static TUint8 mapTensor(TF_Tensor nativeTensor, Shape shape) {

From 824d4872257a5a614a53c7dff579748b819c800e Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 08:14:26 -0400
Subject: [PATCH 03/33] Changed of method to use the DataType NAME attribute
 rather than hardcoding the string. added methods isFloating(), isInteger(),
 isNUmeric(), isBoolean() and isString()

---
 .../main/java/org/tensorflow/DataType.java    | 98 ++++++++++++++++---
 1 file changed, 87 insertions(+), 11 deletions(-)

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataType.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataType.java
index 24bd0826fa8..48940f793dc 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataType.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataType.java
@@ -17,6 +17,15 @@
 
 import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.types.TBfloat16;
+import org.tensorflow.types.TBool;
+import org.tensorflow.types.TFloat16;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.TFloat64;
+import org.tensorflow.types.TInt32;
+import org.tensorflow.types.TInt64;
+import org.tensorflow.types.TUint8;
+import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TType;
 
 /** Represents a type of elements in a {@link Tensor} */
@@ -43,27 +52,96 @@ public interface TensorMapper {
    * @param byteSize size of an element of this type, in bytes, -1 if unknown
    * @param tensorMapper method for mapping tensor memory to elements of this type
    */
-  public static  DataType create(String name, int value, int byteSize, TensorMapper tensorMapper) {
+  public static  DataType create(
+      String name, int value, int byteSize, TensorMapper tensorMapper) {
     return new DataType<>(name, value, byteSize, tensorMapper);
   }
 
   /**
-   * Returns the size of an element of this type, in bytes, or -1 if element size is variable.
+   * Gets the DataType associated with the readable-name for the type
+   * 
The name must match exactly the name used to create the desired DataType

+   *
+   * @param name readable-name for the type
+   * @return the DataType
+   * @throws java.lang.IllegalArgumentException if the name is not a valid data type name
+   * @throws java.lang.NullPointerException if name is null
    */
+  public static DataType of(String name) {
+    switch (name) {
+      case TBfloat16.NAME:
+        return TBfloat16.DTYPE;
+      case TFloat16.NAME:
+        return TFloat16.DTYPE;
+      case TFloat32.NAME:
+        return TFloat32.DTYPE;
+      case TFloat64.NAME:
+        return TFloat64.DTYPE;
+      case TUint8.NAME:
+        return TUint8.DTYPE;
+      case TInt32.NAME:
+        return TInt32.DTYPE;
+      case TInt64.NAME:
+        return TInt64.DTYPE;
+      case TBool.NAME:
+        return TBool.DTYPE;
+      case TString.NAME:
+        return TString.DTYPE;
+      default:
+        throw new IllegalArgumentException(String.format("%s is an unknown DataType", name));
+    }
+  }
+
+  /** Returns true if this data type represents a floating point type */
+  public boolean isFloating() {
+    switch (this.name()) {
+      case TBfloat16.NAME:
+      case TFloat16.NAME:
+      case TFloat32.NAME:
+      case TFloat64.NAME:
+        return true;
+      default:
+        return false;
+    }
+  }
+
+  /** Returns true if this data type represents an integer type */
+  public boolean isInteger() {
+    switch (this.name()) {
+      case TInt32.NAME:
+      case TInt64.NAME:
+      case TUint8.NAME:
+        return true;
+      default:
+        return false;
+    }
+  }
+
+  /** Returns true if this data type represents a numeric type */
+  public boolean isNumeric() {
+    return isFloating() || isInteger();
+  }
+
+  /** Returns true if this data type represents a boolean type */
+  public boolean isBoolean() {
+    return this.name().equals(TBool.NAME);
+  }
+
+  /** Returns true if this data type represents a string type */
+  public boolean isString() {
+    return this.name().equals(TString.NAME);
+  }
+
+  /** Returns the size of an element of this type, in bytes, or -1 if element size is variable. */
   public int byteSize() {
     return byteSize;
   }
 
-  /**
-   * Returns true if this datatype has elements of variable length
-   */
+  /** Returns true if this datatype has elements of variable length */
   public boolean isVariableLength() {
     return byteSize == -1;
   }
 
-  /**
-   * Returns a readable name for this type
-   */
+  /** Returns a readable name for this type */
   public String name() {
     return name;
   }
@@ -73,9 +151,7 @@ public String toString() {
     return name + " (" + nativeCode + ")";
   }
 
-  /**
-   * Returns the numeric code for this datatype, as recognized by the native library (C API)
-   */
+  /** Returns the numeric code for this datatype, as recognized by the native library (C API) */
   int nativeCode() {
     return nativeCode;
   }

From 07a83a5aef5a25f385aa762e3bb929e22c8052e3 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 08:17:40 -0400
Subject: [PATCH 04/33] Added method WriteFieldWithInitializer to output a
 "final static String OP_NAME" to each generated operation.

---
 .../src/bazel/op_generator/op_generator.cc       |  7 +++++++
 .../src/bazel/op_generator/source_writer.cc      | 16 ++++++++++++++++
 .../src/bazel/op_generator/source_writer.h       |  5 ++++-
 3 files changed, 27 insertions(+), 1 deletion(-)

diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
index f0fb802d548..03db4be125b 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
@@ -509,6 +509,13 @@ void GenerateOp(const OpSpec& op, const EndpointSpec& endpoint,
     RenderInterfaceImpl(op, mode, &writer);
   }
   writer.EndLine();
+
+  Variable nameVariable = Variable::Create("OP_NAME", Type::Class("String")); 
+  Javadoc name_javadoc = Javadoc::Create("The name of this op, as known by TensorFlow core engine");
+  string quoted_string = "\"" + op.graph_op_name() + "\"";
+  writer.WriteFieldWithInitializer(nameVariable, PUBLIC|STATIC|FINAL, &name_javadoc, quoted_string );
+  writer.EndLine();
+
   for (const ArgumentSpec& output : op.outputs()) {
     writer.WriteField(output.var(), PRIVATE);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc
index 63191c080ac..8598b1d945d 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc
@@ -238,6 +238,22 @@ SourceWriter& SourceWriter::WriteField(const Variable& field, int modifiers,
   return *this;
 }
 
+SourceWriter& SourceWriter::WriteFieldWithInitializer(const Variable& field,
+	int modifiers, const Javadoc* javadoc, const string& initializer) {
+  // If present, write field javadoc only as one brief line
+  if (javadoc != nullptr && !javadoc->brief().empty()) {
+    Append("/** ").Append(javadoc->brief()).Append(" */").EndLine();
+  }
+  WriteModifiers(modifiers);
+  if (!initializer.empty())
+    AppendType(field.type()).Append(" ").Append(field.name()).
+                            Append(" = ").Append(initializer).Append(";");
+  else
+    AppendType(field.type()).Append(" ").Append(field.name()).Append(";");
+  EndLine();
+  return *this;
+}
+
 SourceWriter& SourceWriter::WriteModifiers(int modifiers) {
   if (modifiers & PUBLIC) {
     Append("public ");
diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h
index 73f487bb46c..097887083e7 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h
@@ -153,6 +153,9 @@ class SourceWriter {
   SourceWriter& WriteField(const Variable& field, int modifiers,
                            const Javadoc* javadoc = nullptr);
 
+  SourceWriter& WriteFieldWithInitializer(const Variable& field,
+        int modifiers, const Javadoc* javadoc = nullptr, const string& initializer = nullptr);
+
  protected:
   virtual void DoAppend(const StringPiece& str) = 0;
 
@@ -161,7 +164,7 @@ class SourceWriter {
   class TypeVisitor {
    public:
     virtual ~TypeVisitor() = default;
-    void Visit(const Type& type);
+    void Visit(const Type& type);	
 
    protected:
     virtual void DoVisit(const Type& type) = 0;

From 3d26831bab64cc4fdd2340403cafa229f0fb7099 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 09:52:13 -0400
Subject: [PATCH 05/33] Added tf.nn.softmaxCrossEntropyWitLogits() and
 tf.nn.raw.softmaxCrossEntropyWitLogits() Added
 tf.nn.sparesSoftmaxCrossEntropyWithLogits() and
 tf.nn.raw.sparesSoftmaxCrossEntropyWithLogits()

Added tf.nn.sigmoidCrossEntropyWithLogits()
---
 ...pi_def_SoftmaxCrossEntropyWithLogits.pbtxt |   2 +-
 ..._SparseSoftmaxCrossEntropyWithLogits.pbtxt |   2 +-
 .../main/java/org/tensorflow/op/core/NN.java  | 379 ++++++++++++++++++
 3 files changed, 381 insertions(+), 2 deletions(-)
 create mode 100644 tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java

diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SoftmaxCrossEntropyWithLogits.pbtxt b/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SoftmaxCrossEntropyWithLogits.pbtxt
index e064562c0f2..5dba2164cd6 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SoftmaxCrossEntropyWithLogits.pbtxt
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SoftmaxCrossEntropyWithLogits.pbtxt
@@ -1,6 +1,6 @@
 op {
   graph_op_name: "SoftmaxCrossEntropyWithLogits"
   endpoint {
-    name: "nn.SoftmaxCrossEntropyWithLogits"
+    name: "nn.raw.SoftmaxCrossEntropyWithLogits"
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SparseSoftmaxCrossEntropyWithLogits.pbtxt b/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SparseSoftmaxCrossEntropyWithLogits.pbtxt
index 7627d5f6074..cf80ff77565 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SparseSoftmaxCrossEntropyWithLogits.pbtxt
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/api_def/api_def_SparseSoftmaxCrossEntropyWithLogits.pbtxt
@@ -1,6 +1,6 @@
 op {
   graph_op_name: "SparseSoftmaxCrossEntropyWithLogits"
   endpoint {
-    name: "nn.SparseSoftmaxCrossEntropyWithLogits"
+    name: "nn.raw.SparseSoftmaxCrossEntropyWithLogits"
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java
new file mode 100644
index 00000000000..b4fa7bd01de
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java
@@ -0,0 +1,379 @@
+package org.tensorflow.op.core;
+
+import org.tensorflow.DataType;
+import org.tensorflow.Operand;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Op;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.op.math.*;
+import org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits;
+import org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits;
+import org.tensorflow.types.*;
+import org.tensorflow.types.family.TNumber;
+import org.tensorflow.op.dtypes.Cast;
+import org.tensorflow.types.family.TType;
+import org.tensorflow.op.linalg.Transpose;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.List;
+
+@Operator(group = "nn")
+public abstract class NN {
+
+  /**
+   * Computes softmax cross entropy between `logits` and `labels`.
+   *
+   * 
Measures the probability error in discrete classification tasks in which the classes are
+   * mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is
+   * labeled with one and only one label: an image can be a dog or a truck, but not both.
+   *
+   * 
**NOTE:** While the classes are mutually exclusive, their probabilities need not be. All
+   * that is required is that each row of `labels` is a valid probability distribution. If they are
+   * not, the computation of the gradient will be incorrect.
+   *
+   * 
If using exclusive `labels` (wherein one and only one class is true at a time), see
+   * `sparse_softmax_cross_entropy_with_logits`.
+   *
+   * 
Usage:
+   *
+   * 
+   *   >>> logits = [[4.0, 2.0, 1.0], [0.0, 5.0, 1.0]]
+   *   >>> labels = [[1.0, 0.0, 0.0], [0.0, 0.8, 0.2]]
+   *   >>> tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits)
+   *   
+   * 

+   *
+   * 
Backpropagation will happen into both `logits` and `labels`. To disallow backpropagation
+   * into `labels`, pass label tensors through `tf.stop_gradient` before feeding it to this
+   * function.
+   *
+   * @param scope current scope
+   * @param labels Each vector along the class dimension should hold a valid probability
+   *     distribution e.g. for the case in which labels are of shape `[batch_size, num_classes]`,
+   *     each row of `labels[i]` must be a valid probability distribution.
+   * @param logits Per-label activations, typically a linear output. These activation energies are
+   *     interpreted as unnormalized log probabilities.
+   * @param axis The class dimension. -1 is the last dimension.
+   * @param  the data type of the logits
+   * @param  the number type of the operands
+   * @return the softmax cross entropy loss. Its type is the same as `logits` and its shape is the
+   *     same as `labels` except that it does not have the last dimension of `labels`.
+   */
+  @Endpoint(name = "softmaxCrossEntropyWithLogits")
+  public static  Operand softmaxCrossEntropyWithLogits(
+      Scope scope, Operand labels, Operand logits, int axis) {
+    axis = axis % logits.asOutput().shape().numDimensions();
+    if (axis < 0) {
+      axis += logits.asOutput().shape().numDimensions();
+    }
+
+    Operand precise_logits =
+        logits; // cannot use generics cause logits of bool gets cast to TFloat32
+
+    boolean convertToFloat32 =
+        logits.asOutput().dataType() == TFloat16.DTYPE
+            || logits.asOutput().dataType() == TBfloat16.DTYPE;
+    if (convertToFloat32) {
+      precise_logits = Cast.create(scope, logits, TFloat32.DTYPE);
+    }
+    /* cannot use generics on DataType because precis_logits may have been cast. */
+    DataType dtype = precise_logits.asOutput().dataType();
+    labels = Cast.create(scope, labels, dtype);
+    Operand inputRank =
+        Cast.create(scope, Rank.create(scope, precise_logits), TInt64.DTYPE);
+    Shape shape = logits.asOutput().shape();
+
+    // Move the dim to the end if dim is not the last dimension.
+    if (axis != -1 && axis != precise_logits.asOutput().shape().numDimensions() - 1) {
+      precise_logits = moveDimToEnd(scope, precise_logits, axis, inputRank);
+      labels = moveDimToEnd(scope, labels, axis, inputRank);
+    }
+
+    Shape inputShape = precise_logits.asOutput().shape();
+    precise_logits = flattenOuterDims(scope, precise_logits);
+    labels = flattenOuterDims(scope, labels);
+    SoftmaxCrossEntropyWithLogits smax =
+        SoftmaxCrossEntropyWithLogits.create(scope, precise_logits, labels);
+    /* cannot use generic on cost, because cost may be recast later. */
+    Operand cost = smax.loss();
+    Operand outputShape =
+        Slice.create(
+            scope,
+            Constant.vectorOf(scope, inputShape.asArray()),
+            Constant.vectorOf(scope, new long[] {0}),
+            Constant.vectorOf(scope, new long[] {inputShape.numDimensions() - 1}));
+    cost = Reshape.create(scope, cost, outputShape);
+    if (scope.env().isGraph() && !shape.hasUnknownDimension()) {
+      long[] array = shape.asArray();
+      long[] newArray = new long[array.length - 1];
+      if (axis < 0) {
+        axis = shape.numDimensions() + axis;
+      }
+      for (int i = 0; i < axis; i++) {
+        newArray[i] = shape.size(i);
+      }
+      for (int i = axis + 1; i < shape.numDimensions(); i++) {
+        newArray[i - 1] = shape.size(i);
+      }
+      Shape newShape = Shape.of(newArray);
+      cost = Reshape.create(scope, cost, Constant.vectorOf(scope, newShape.asArray()));
+    }
+
+    if (convertToFloat32) {
+      cost = Cast.create(scope, cost, logits.asOutput().dataType());
+    }
+    return cost;
+  }
+
+  /**
+   * Computes sparse softmax cross entropy between `logits` and `labels`.
+   *
+   * @param scope current scope
+   * @param labels `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of `labels` and
+   *     result) and dtype `int32` or `int64`. Each entry in `labels` must be an index in `[0,
+   *     num_classes)`. Other values will raise an exception when this op is run on CPU, and return
+   *     `NaN` for corresponding loss and gradient rows on GPU.
+   * @param logits Per-label activations (typically a linear output) of shape `[d_0, d_1, ...,
+   *     d_{r-1}, num_classes]` and dtype `float16`, `float32`, or `float64`. These activation
+   *     energies are interpreted as unnormalized log probabilities.
+   * @return A `Tensor` of the same shape as `labels` and of the same type as `logits` with the
+   *     softmax cross entropy loss.
+   */
+  @Endpoint(name = "sparseSoftmaxCrossEntropyWithLogits")
+  public static  Operand sparseSoftmaxCrossEntropyWithLogits(
+      Scope scope, Operand labels, Operand logits) {
+    // assert shapeIsCompatible(labels.asOutput().shape(), logits.asOutput().shape()):
+    //        String.format("Shapes %s and %s are incompatible",
+    //                labels.asOutput().shape(), logits.asOutput().shape());
+    scope = scope.withSubScope("SparseSoftmaxCrossEntropyWithLogits");
+    /** cannot use generics on precise_logits as it may be recast later */
+    Operand precise_logits = logits;
+    boolean convertToFloat32 =
+        logits.asOutput().dataType() == TFloat16.DTYPE
+            || logits.asOutput().dataType() == TBfloat16.DTYPE;
+    if (convertToFloat32) {
+      precise_logits = Cast.create(scope, logits, TFloat32.DTYPE);
+    }
+    Shape labelsStaticShape = labels.asOutput().shape();
+    org.tensorflow.op.core.Shape labelsShape =
+        org.tensorflow.op.core.Shape.create(scope, labels);
+    Shape logitsShape = logits.asOutput().shape();
+    Shape logitsShortened = logitsShape.take(logitsShape.numDimensions() - 1);
+
+    boolean staticShapesFullyDefined =
+        !labelsStaticShape.hasUnknownDimension() && !logitsShortened.hasUnknownDimension();
+    if (logitsShape.numDimensions() == 0) {
+      throw new IllegalArgumentException(
+          String.format("Logits cannot be scalars - received shape %s.", logitsShape));
+    }
+    if (!logitsShape.hasUnknownDimension()
+        && !labelsStaticShape.hasUnknownDimension()
+        && labelsStaticShape.numDimensions() != logitsShape.numDimensions() - 1) {
+      throw new IllegalArgumentException(
+          String.format(
+              "Rank mismatch: Rank of labels (received %s) should equal rank of logits minus 1 (received %s).",
+              labelsStaticShape.toString(), logitsShape.toString()));
+    }
+
+    if (staticShapesFullyDefined && !labelsStaticShape.equals(logitsShortened)) {
+      throw new IllegalArgumentException(
+          String.format(
+              "Shape mismatch: The shape of labels (received %s) "
+                  + "should equal the shape of logits except for the last "
+                  + "dimension (received %s).",
+              labelsStaticShape.toString(), logitsShape.toString()));
+    }
+    // Check if no reshapes are required.
+    if (logitsShape.numDimensions() == 2) {
+      SparseSoftmaxCrossEntropyWithLogits smax =
+          SparseSoftmaxCrossEntropyWithLogits.create(scope, precise_logits, labels);
+      Operand loss = smax.loss();
+      if (logits.asOutput().dataType() == TFloat16.DTYPE) {
+        loss = Cast.create(scope, loss, TFloat16.DTYPE);
+      }
+      return loss;
+    }
+
+    List shapeChecks = new ArrayList<>();
+
+    if (!staticShapesFullyDefined) {
+      shapeChecks.add(
+          AssertThat.create(
+              scope,
+              Equal.create(
+                  scope,
+                  org.tensorflow.op.core.Shape.create(scope, labels),
+                  Shapes.take(
+                      scope,
+                      org.tensorflow.op.core.Shape.create(scope, logits),
+                      Constant.scalarOf(scope, -1))),
+              Collections.singletonList(
+                  Constant.scalarOf(
+                      scope,
+                      "Shape mismatch: The shape of labels  "
+                          + "should equal the shape of logits except for the last "
+                          + "dimension "))));
+    }
+
+    // Reshape logits to 2 dim, labels to 1 dim.
+    long numClassses = logitsShape.size(logitsShape.numDimensions() - 1);
+
+    precise_logits =
+        Reshape.create(
+            scope, precise_logits, Constant.vectorOf(scope, new long[] {-1, numClassses}));
+    labels = Reshape.create(scope, labels, Constant.scalarOf(scope, -1));
+    scope.withControlDependencies(shapeChecks);
+    SparseSoftmaxCrossEntropyWithLogits smax =
+        SparseSoftmaxCrossEntropyWithLogits.create(scope, precise_logits, labels);
+    Operand cost = smax.loss();
+    cost = Reshape.create(scope, cost, labelsShape);
+    if (logits.asOutput().dataType() == TFloat16.DTYPE) {
+      cost = Cast.create(scope, cost, TFloat16.DTYPE);
+    }
+    return cost;
+  }
+
+  /**
+   * Computes sigmoid cross entropy given `logits`.
+   *
+   * 
Measures the probability error in discrete classification tasks in which each class is
+   * independent and not mutually exclusive. For instance, one could perform multilabel
+   * classification where a picture can contain both an elephant and a dog at the same time.
+   *
+   * 
For brevity, let `x = logits`, `z = labels`. The logistic loss is
+   *
+   * 
+   *     z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
+   *     = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
+   *     = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
+   *     = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
+   *     = (1 - z) * x + log(1 + exp(-x))
+   *     = x - x * z + log(1 + exp(-x))
+   * 

+   *
+   * 
For x < 0, to avoid overflow in exp(-x), we reformulate the above
+   *
+   * 
+   *      x - x * z + log(1 + exp(-x))
+   *      = log(exp(x)) - x * z + log(1 + exp(-x))
+   *      = - x * z + log(1 + exp(x))
+   * 

+   *
+   * 
Hence, to ensure stability and avoid overflow, the implementation uses this equivalent
+   * formulation
+   *
+   * 
+   *     max(x, 0) - x * z + log(1 + exp(-abs(x)))
+   * 

+   *
+   * 
`logits` and `labels` must have the same type and shape.
+   *
+   * @param scope The TensorFlow scope
+   * @param labels the labels
+   * @param logits the logits of type float32 or float64
+   * @param  the type of labels and logits
+   * @return the component-wise logistic losses.
+   */
+  @Endpoint(name = "sigmoidCrossEntropyWithLogits")
+  public static  Operand sigmoidCrossEntropyWithLogits(
+      Scope scope, Operand labels, Operand logits) {
+    if (labels.asOutput().shape().numDimensions() != logits.asOutput().shape().numDimensions())
+      throw new IllegalArgumentException(
+          String.format(
+              "logits and labels must have the same shape (%s vs %s)",
+              labels.asOutput().shape().toString(), logits.asOutput().shape()));
+    Operand zeros =
+        Cast.create(scope, ZerosLike.create(scope, logits), logits.asOutput().dataType());
+    Operand cond = GreaterEqual.create(scope, logits, zeros);
+
+    Operand relu_logits = Select.create(scope, cond, logits, zeros);
+    Operand neg_abs_logits = Select.create(scope, cond, Neg.create(scope, logits), logits);
+    return Add.create(
+        scope,
+        Sub.create(scope, relu_logits, Mul.create(scope, logits, labels)),
+        Log1p.create(scope, Exp.create(scope, neg_abs_logits)));
+  }
+
+  /**
+   * Flattens logits' outer dimensions and keep its last dimension.
+   *
+   * @param scope the TensorFlow scope
+   * @param logits the logits
+   * @param  the type of logits
+   * @return the flattened logits
+   */
+  private static  Operand flattenOuterDims(Scope scope, Operand logits) {
+    Operand one = Constant.scalarOf(scope, 1L);
+
+    org.tensorflow.ndarray.Shape shape = logits.asOutput().shape();
+    int ndims = shape.numDimensions();
+    if (!shape.hasUnknownDimension()) {
+      long product = 1L;
+      boolean productValid = true;
+      for (int i = ndims - 2; i >= 0; i--) {
+        long d = shape.size(i);
+        if (d == org.tensorflow.ndarray.Shape.UNKNOWN_SIZE) {
+          productValid = false;
+          break;
+        }
+        product *= d;
+      }
+      if (productValid) {
+        org.tensorflow.ndarray.Shape outputShape = Shape.of(product, shape.size(ndims - 1));
+        return Reshape.create(scope, logits, Constant.vectorOf(scope, outputShape.asArray()));
+      }
+    }
+
+    Operand rank = Cast.create(scope, Rank.create(scope, logits), TInt64.DTYPE);
+    Operand rankMinusOne = Sub.create(scope, rank, one);
+
+    Operand last_dim_size =
+        Slice.create(
+            scope,
+            org.tensorflow.op.core.Shape.create(scope, logits, TInt64.DTYPE),
+            rankMinusOne,
+            one);
+    Operand concat =
+        Concat.create(
+            scope,
+            Arrays.asList(Constant.vectorOf(scope, new long[] {-1}), last_dim_size),
+            Constant.scalarOf(scope, 0));
+    return Reshape.create(scope, logits, concat);
+  }
+
+  /**
+   * Move the dim to the end if dim is not the last dimension.
+   *
+   * @param scope The TensorFlow Scope
+   * @param input the input to reshape
+   * @param dim_index the index to move
+   * @param rank the number of Dimensions in the tensor
+   * @param  the data type of the tensor.
+   * @param  the data type of the rank
+   * @return the reshaped input
+   */
+  private static  Operand moveDimToEnd(
+      Scope scope, Operand input, int dim_index, Operand rank) {
+    DataType rankDType = rank.asOutput().dataType();
+    Operand one = Cast.create(scope, Constant.scalarOf(scope, 1), rankDType);
+    List> concatList =
+        Arrays.asList(
+            Range.create(
+                scope,
+                Cast.create(scope, Constant.scalarOf(scope, dim_index), rankDType),
+                one,
+                one),
+            Range.create(
+                scope,
+                Cast.create(scope, Constant.scalarOf(scope, (dim_index + 1)), rankDType),
+                rank,
+                one));
+    return Transpose.create(
+        scope, input, Concat.create(scope, concatList, Constant.scalarOf(scope, 0)));
+  }
+}

From 11cda5fde99a6bec21fb04ed1465934ec1889485 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 09:58:05 -0400
Subject: [PATCH 06/33] Moved SoftmaxCrossEntropyWithLogits and 
 SparseSoftmaxCrossEntropyWithLogits to org.tensorflow.op.nn.raw

---
 .../nn/raw/SoftmaxCrossEntropyWithLogits.java | 86 ++++++++++++++++++
 .../SparseSoftmaxCrossEntropyWithLogits.java  | 90 +++++++++++++++++++
 2 files changed, 176 insertions(+)
 create mode 100644 tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java
 create mode 100644 tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java

diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java
new file mode 100644
index 00000000000..4c23683d9ef
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java
@@ -0,0 +1,86 @@
+/* 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.
+=======================================================================*/
+
+// This class has been generated, DO NOT EDIT!
+
+package org.tensorflow.op.nn.raw;
+
+import org.tensorflow.Operand;
+import org.tensorflow.Operation;
+import org.tensorflow.OperationBuilder;
+import org.tensorflow.Output;
+import org.tensorflow.op.RawOp;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.family.TNumber;
+import org.tensorflow.types.family.TType;
+
+/**
+ * Computes softmax cross entropy cost and gradients to backpropagate.
+ * 

+ * Inputs are the logits, not probabilities.
+ * 
+ * @param  data type for {@code loss()} output
+ */
+@Operator(group = "nn.raw")
+public final class SoftmaxCrossEntropyWithLogits extends RawOp {
+  
+  /**
+   * Factory method to create a class wrapping a new SoftmaxCrossEntropyWithLogits operation.
+   * 
+   * @param scope current scope
+   * @param features batch_size x num_classes matrix
+   * @param labels batch_size x num_classes matrix
+   * The caller must ensure that each batch of labels represents a valid
+   * probability distribution.
+   * @return a new instance of SoftmaxCrossEntropyWithLogits
+   */
+  @Endpoint(describeByClass = true)
+  public static  SoftmaxCrossEntropyWithLogits create(Scope scope, Operand features, Operand labels) {
+    OperationBuilder opBuilder = scope.env().opBuilder("SoftmaxCrossEntropyWithLogits", scope.makeOpName("SoftmaxCrossEntropyWithLogits"));
+    opBuilder.addInput(features.asOutput());
+    opBuilder.addInput(labels.asOutput());
+    opBuilder = scope.applyControlDependencies(opBuilder);
+    return new SoftmaxCrossEntropyWithLogits(opBuilder.build());
+  }
+  
+  /**
+   * Per example loss (batch_size vector).
+   */
+  public Output loss() {
+    return loss;
+  }
+  
+  /**
+   * backpropagated gradients (batch_size x num_classes matrix).
+   */
+  public Output backprop() {
+    return backprop;
+  }
+  
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SoftmaxCrossEntropyWithLogits";
+  
+  private Output loss;
+  private Output backprop;
+  
+  private SoftmaxCrossEntropyWithLogits(Operation operation) {
+    super(operation);
+    int outputIdx = 0;
+    loss = operation.output(outputIdx++);
+    backprop = operation.output(outputIdx++);
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java
new file mode 100644
index 00000000000..e7cb45231de
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java
@@ -0,0 +1,90 @@
+/* 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.
+=======================================================================*/
+
+// This class has been generated, DO NOT EDIT!
+
+package org.tensorflow.op.nn.raw;
+
+import org.tensorflow.Operand;
+import org.tensorflow.Operation;
+import org.tensorflow.OperationBuilder;
+import org.tensorflow.Output;
+import org.tensorflow.op.RawOp;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.family.TNumber;
+import org.tensorflow.types.family.TType;
+
+/**
+ * Computes softmax cross entropy cost and gradients to backpropagate.
+ * 

+ * Unlike `SoftmaxCrossEntropyWithLogits`, this operation does not accept
+ * a matrix of label probabilities, but rather a single label per row
+ * of features.  This label is considered to have probability 1.0 for the
+ * given row.
+ * 

+ * Inputs are the logits, not probabilities.
+ * 
+ * @param  data type for {@code loss()} output
+ */
+@Operator(group = "nn.raw")
+public final class SparseSoftmaxCrossEntropyWithLogits extends RawOp {
+  
+  /**
+   * Factory method to create a class wrapping a new SparseSoftmaxCrossEntropyWithLogits operation.
+   * 
+   * @param scope current scope
+   * @param features batch_size x num_classes matrix
+   * @param labels batch_size vector with values in [0, num_classes).
+   * This is the label for the given minibatch entry.
+   * @return a new instance of SparseSoftmaxCrossEntropyWithLogits
+   */
+  @Endpoint(describeByClass = true)
+  public static  SparseSoftmaxCrossEntropyWithLogits create(Scope scope, Operand features, Operand labels) {
+    OperationBuilder opBuilder = scope.env().opBuilder("SparseSoftmaxCrossEntropyWithLogits", scope.makeOpName("SparseSoftmaxCrossEntropyWithLogits"));
+    opBuilder.addInput(features.asOutput());
+    opBuilder.addInput(labels.asOutput());
+    opBuilder = scope.applyControlDependencies(opBuilder);
+    return new SparseSoftmaxCrossEntropyWithLogits(opBuilder.build());
+  }
+  
+  /**
+   * Per example loss (batch_size vector).
+   */
+  public Output loss() {
+    return loss;
+  }
+  
+  /**
+   * backpropagated gradients (batch_size x num_classes matrix).
+   */
+  public Output backprop() {
+    return backprop;
+  }
+  
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSoftmaxCrossEntropyWithLogits";
+  
+  private Output loss;
+  private Output backprop;
+  
+  private SparseSoftmaxCrossEntropyWithLogits(Operation operation) {
+    super(operation);
+    int outputIdx = 0;
+    loss = operation.output(outputIdx++);
+    backprop = operation.output(outputIdx++);
+  }
+}

From 9c7dfaa92815bf85cbf97febcbb61e1aaf707142 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 10:00:25 -0400
Subject: [PATCH 07/33] Generated classes now have public static final String
 OP_NAME = "XXXXXXXX";

---
 .../src/gen/java/org/tensorflow/op/nn/AvgPool.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/AvgPool3d.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java         | 3 +++
 .../org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java | 3 +++
 .../tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/BiasAdd.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/BlockLSTM.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/CTCLossV2.java           | 3 +++
 .../gen/java/org/tensorflow/op/nn/ComputeAccidentalHits.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Conv2d.java              | 3 +++
 .../gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Conv3d.java              | 3 +++
 .../gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java | 3 +++
 .../gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/CtcLoss.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/CudnnRNN.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java    | 3 +++
 .../java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java   | 3 +++
 .../java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java    | 3 +++
 .../gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/DepthToSpace.java        | 3 +++
 .../gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java   | 3 +++
 .../tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java  | 3 +++
 .../tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Dilation2d.java          | 3 +++
 .../java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java    | 3 +++
 .../gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Elu.java                 | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/EluGrad.java             | 3 +++
 .../org/tensorflow/op/nn/FixedUnigramCandidateSampler.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java   | 3 +++
 .../gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java   | 3 +++
 .../gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java      | 3 +++
 .../gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/InTopK.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/InvGrad.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/L2Loss.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/LeakyRelu.java           | 3 +++
 .../org/tensorflow/op/nn/LearnedUnigramCandidateSampler.java   | 3 +++
 .../java/org/tensorflow/op/nn/LocalResponseNormalization.java  | 3 +++
 .../org/tensorflow/op/nn/LocalResponseNormalizationGrad.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/LogSoftmax.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/MaxPool.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/MaxPool3d.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java     | 3 +++
 .../java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java   | 3 +++
 .../gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/NthElement.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java    | 3 +++
 .../op/nn/QuantizedBatchNormWithGlobalNormalization.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java    | 3 +++
 .../gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java  | 3 +++
 .../tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java  | 3 +++
 .../org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java     | 3 +++
 .../java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java   | 3 +++
 .../gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java | 3 +++
 .../org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java   | 3 +++
 .../op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java     | 3 +++
 .../tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java | 3 +++
 .../QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java  | 3 +++
 .../tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java    | 3 +++
 .../op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java     | 3 +++
 .../java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java    | 3 +++
 .../org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java | 3 +++
 .../op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java         | 3 +++
 .../QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java  | 3 +++
 .../gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/QuantizedMaxPool.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Relu.java                | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Relu6.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Relu6Grad.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/ReluGrad.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Selu.java                | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/SeluGrad.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Softmax.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/Softsign.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/nn/TopK.java                | 3 +++
 104 files changed, 312 insertions(+)

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 de1a858b738..527d1a49713 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AvgPool";
+  
   private Output output;
   
   private AvgPool(Operation operation) {
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 1700745d1ba..87467c8a982 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
@@ -122,6 +122,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AvgPool3D";
+  
   private Output output;
   
   private AvgPool3d(Operation operation) {
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 9426ff8f682..3e34c87f9b6 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
@@ -125,6 +125,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AvgPool3DGrad";
+  
   private Output output;
   
   private AvgPool3dGrad(Operation operation) {
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 9389f98ad3b..7ec252eaac0 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AvgPoolGrad";
+  
   private Output output;
   
   private AvgPoolGrad(Operation operation) {
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 23cc0b463ba..6c30a52cf2e 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
@@ -83,6 +83,9 @@ public Output asOutput() {
     return result;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchNormWithGlobalNormalization";
+  
   private Output result;
   
   private BatchNormWithGlobalNormalization(Operation operation) {
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 fe2813b3342..be07a5eea25 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
@@ -106,6 +106,9 @@ public Output dg() {
     return dg;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchNormWithGlobalNormalizationGrad";
+  
   private Output dx;
   private Output dm;
   private Output dv;
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 6296f75db61..462eaa6edc7 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BiasAdd";
+  
   private Output output;
   
   private BiasAdd(Operation operation) {
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 dcc2b537f65..df90cf9a2f3 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
@@ -112,6 +112,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BiasAddGrad";
+  
   private Output output;
   
   private BiasAddGrad(Operation operation) {
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 22f0d16f540..79de4f2f88c 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
@@ -192,6 +192,9 @@ public Output h() {
     return h;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BlockLSTMV2";
+  
   private Output i;
   private Output cs;
   private Output f;
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 e80bea4006d..4e49f23cb6e 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
@@ -146,6 +146,9 @@ public Output bGrad() {
     return bGrad;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BlockLSTMGradV2";
+  
   private Output xGrad;
   private Output csPrevGrad;
   private Output hPrevGrad;
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 918230851c3..c60fef4b2a7 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
@@ -158,6 +158,9 @@ public Output gradient() {
     return gradient;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CTCLossV2";
+  
   private Output loss;
   private Output gradient;
   
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 a11bb983ae9..f6daea0df2e 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
@@ -139,6 +139,9 @@ public Output weights() {
     return weights;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ComputeAccidentalHits";
+  
   private Output indices;
   private Output ids;
   private Output weights;
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 632d54c3890..79f2022d807 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
@@ -222,6 +222,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Conv2D";
+  
   private Output output;
   
   private Conv2d(Operation operation) {
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 91e147def81..9c145dc3d60 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
@@ -205,6 +205,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Conv2DBackpropFilter";
+  
   private Output output;
   
   private Conv2dBackpropFilter(Operation operation) {
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 389ddb0be4e..492c4f2aebb 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
@@ -204,6 +204,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Conv2DBackpropInput";
+  
   private Output output;
   
   private Conv2dBackpropInput(Operation operation) {
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 1e80fdb7f80..94ae4ffd2b5 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
@@ -154,6 +154,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Conv3D";
+  
   private Output output;
   
   private Conv3d(Operation operation) {
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 d6d85797b3f..0d73e491717 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
@@ -154,6 +154,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Conv3DBackpropFilterV2";
+  
   private Output output;
   
   private Conv3dBackpropFilter(Operation operation) {
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 08e163494bf..8b153890811 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
@@ -153,6 +153,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Conv3DBackpropInputV2";
+  
   private Output output;
   
   private Conv3dBackpropInput(Operation operation) {
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 8d212909901..96f179641e7 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
@@ -136,6 +136,9 @@ public Output logProbability() {
     return logProbability;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CTCBeamSearchDecoder";
+  
   private List> decodedIndices;
   private List> decodedValues;
   private List> decodedShape;
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 eecea029a34..b8b35b8ceaa 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
@@ -131,6 +131,9 @@ public Output logProbability() {
     return logProbability;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CTCGreedyDecoder";
+  
   private Output decodedIndices;
   private Output decodedValues;
   private Output decodedShape;
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 b39f344373e..ceb60a4baf7 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
@@ -161,6 +161,9 @@ public Output gradient() {
     return gradient;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CTCLoss";
+  
   private Output loss;
   private Output gradient;
   
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 9159d1c69c3..7cd9771acf1 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
@@ -313,6 +313,9 @@ public Output hostReserved() {
     return hostReserved;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CudnnRNNV3";
+  
   private Output output;
   private Output outputH;
   private Output outputC;
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 adeadb27292..3719c186716 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
@@ -314,6 +314,9 @@ public Output paramsBackprop() {
     return paramsBackprop;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CudnnRNNBackpropV3";
+  
   private Output inputBackprop;
   private Output inputHBackprop;
   private Output inputCBackprop;
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 945fdacdf62..155cfd2c0a4 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
@@ -251,6 +251,9 @@ public Output asOutput() {
     return params;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CudnnRNNCanonicalToParamsV2";
+  
   private Output params;
   
   private CudnnRNNCanonicalToParams(Operation operation) {
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 e7fbeebf99f..ea575f2d7a1 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
@@ -255,6 +255,9 @@ public List> biases() {
     return biases;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CudnnRNNParamsToCanonicalV2";
+  
   private List> weights;
   private List> biases;
   
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 6cff6fe9836..94421d0aa6e 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
@@ -242,6 +242,9 @@ public Output asOutput() {
     return paramsSize;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CudnnRNNParamsSize";
+  
   private Output paramsSize;
   
   private CudnnRnnParamsSize(Operation operation) {
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 eb82df7184c..6b1ff40761b 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
@@ -119,6 +119,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DataFormatDimMap";
+  
   private Output y;
   
   private DataFormatDimMap(Operation operation) {
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 5a04c0847c7..ba218c1923f 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
@@ -118,6 +118,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DataFormatVecPermute";
+  
   private Output y;
   
   private DataFormatVecPermute(Operation operation) {
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 523977a1db0..6456eff1f95 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
@@ -177,6 +177,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DepthToSpace";
+  
   private Output output;
   
   private DepthToSpace(Operation operation) {
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 36277e498d5..8775abedbaa 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
@@ -164,6 +164,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DepthwiseConv2dNative";
+  
   private Output output;
   
   private DepthwiseConv2dNative(Operation operation) {
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 074d37aba9b..bdbcf9f384b 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
@@ -160,6 +160,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DepthwiseConv2dNativeBackpropFilter";
+  
   private Output output;
   
   private DepthwiseConv2dNativeBackpropFilter(Operation operation) {
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 323890cbc1e..b5315e2ffde 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
@@ -160,6 +160,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DepthwiseConv2dNativeBackpropInput";
+  
   private Output output;
   
   private DepthwiseConv2dNativeBackpropInput(Operation operation) {
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 984c4621881..c7135b20361 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
@@ -106,6 +106,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Dilation2D";
+  
   private Output output;
   
   private Dilation2d(Operation operation) {
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 1e413d9a08c..9254ff8c285 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return filterBackprop;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Dilation2DBackpropFilter";
+  
   private Output filterBackprop;
   
   private Dilation2dBackpropFilter(Operation operation) {
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 7d247c4288b..525e06182c5 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return inBackprop;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Dilation2DBackpropInput";
+  
   private Output inBackprop;
   
   private Dilation2dBackpropInput(Operation operation) {
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 f138ee46ce3..daeef97895b 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return activations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Elu";
+  
   private Output activations;
   
   private Elu(Operation operation) {
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 fd41f261813..664475879a0 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EluGrad";
+  
   private Output backprops;
   
   private EluGrad(Operation operation) {
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 e99a41a2c56..25fd11071f9 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
@@ -312,6 +312,9 @@ public Output sampledExpectedCount() {
     return sampledExpectedCount;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FixedUnigramCandidateSampler";
+  
   private Output sampledCandidates;
   private Output trueExpectedCount;
   private Output sampledExpectedCount;
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 189f1b9c27c..101ea21ec8c 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
@@ -230,6 +230,9 @@ public Output colPoolingSequence() {
     return colPoolingSequence;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FractionalAvgPool";
+  
   private Output output;
   private Output rowPoolingSequence;
   private Output colPoolingSequence;
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 26c06215c54..03ae0136311 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
@@ -128,6 +128,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FractionalAvgPoolGrad";
+  
   private Output output;
   
   private FractionalAvgPoolGrad(Operation operation) {
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 015b99a14eb..a621e037740 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
@@ -254,6 +254,9 @@ public Output colPoolingSequence() {
     return colPoolingSequence;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FractionalMaxPool";
+  
   private Output output;
   private Output rowPoolingSequence;
   private Output colPoolingSequence;
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 cabbf2e038a..1b2bcc62dbf 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
@@ -124,6 +124,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FractionalMaxPoolGrad";
+  
   private Output output;
   
   private FractionalMaxPoolGrad(Operation operation) {
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 464ae92f2ae..04e8d71e1e5 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
@@ -205,6 +205,9 @@ public Output reserveSpace3() {
     return reserveSpace3;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FusedBatchNormV3";
+  
   private Output y;
   private Output batchMean;
   private Output batchVariance;
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 52bd5e98084..4d2ecc74a4f 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
@@ -187,6 +187,9 @@ public Output reserveSpace5() {
     return reserveSpace5;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FusedBatchNormGradV3";
+  
   private Output xBackprop;
   private Output scaleBackprop;
   private Output offsetBackprop;
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 11ec154a076..2d3de921f0b 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
@@ -93,6 +93,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FusedPadConv2D";
+  
   private Output output;
   
   private FusedPadConv2d(Operation operation) {
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 4eda6e97eaa..02f82242c7a 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
@@ -131,6 +131,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FusedResizeAndPadConv2D";
+  
   private Output output;
   
   private FusedResizeAndPadConv2d(Operation operation) {
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 49c7d619410..446f43cfb0c 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
@@ -129,6 +129,9 @@ public Output h() {
     return h;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GRUBlockCell";
+  
   private Output r;
   private Output u;
   private Output c;
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 bea3442c6c9..4a6b72b8e4c 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
@@ -173,6 +173,9 @@ public Output dRBarUBar() {
     return dRBarUBar;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GRUBlockCellGrad";
+  
   private Output dX;
   private Output dHPrev;
   private Output dCBar;
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 1255067ed44..d38388a3fd5 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
@@ -82,6 +82,9 @@ public Output asOutput() {
     return precision;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InTopKV2";
+  
   private Output precision;
   
   private InTopK(Operation operation) {
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 b0df0c43ee0..161d8771b83 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InvGrad";
+  
   private Output z;
   
   private InvGrad(Operation operation) {
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 91d141c787c..b38d9e99d96 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "L2Loss";
+  
   private Output output;
   
   private L2Loss(Operation operation) {
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 a10d335bc0b..ab5d1b8aee2 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
@@ -210,6 +210,9 @@ public Output h() {
     return h;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LSTMBlockCell";
+  
   private Output i;
   private Output cs;
   private Output f;
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 bfb5dae0118..3635ec433d6 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
@@ -119,6 +119,9 @@ public Output wcoGrad() {
     return wcoGrad;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LSTMBlockCellGrad";
+  
   private Output csPrevGrad;
   private Output dicfo;
   private Output wciGrad;
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 54579426b78..230b4238047 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
@@ -95,6 +95,9 @@ public Output asOutput() {
     return activations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LeakyRelu";
+  
   private Output activations;
   
   private LeakyRelu(Operation operation) {
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 017ee428cde..3f850ce672c 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
@@ -154,6 +154,9 @@ public Output sampledExpectedCount() {
     return sampledExpectedCount;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LearnedUnigramCandidateSampler";
+  
   private Output sampledCandidates;
   private Output trueExpectedCount;
   private Output sampledExpectedCount;
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 0004fed685b..a560c9cfb58 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
@@ -165,6 +165,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LRN";
+  
   private Output output;
   
   private LocalResponseNormalization(Operation operation) {
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 24d769e571a..08f10c12f26 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
@@ -157,6 +157,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LRNGrad";
+  
   private Output output;
   
   private LocalResponseNormalizationGrad(Operation operation) {
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 58035248560..bd1bff467a1 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return logsoftmax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LogSoftmax";
+  
   private Output logsoftmax;
   
   private LogSoftmax(Operation operation) {
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 4df68034706..f7b75951e31 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
@@ -112,6 +112,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPoolV2";
+  
   private Output output;
   
   private MaxPool(Operation operation) {
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 c38fd7b341e..61bf43372cc 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
@@ -122,6 +122,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPool3D";
+  
   private Output output;
   
   private MaxPool3d(Operation operation) {
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 8361c38b80a..7e11914cca2 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
@@ -125,6 +125,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPool3DGrad";
+  
   private Output output;
   
   private MaxPool3dGrad(Operation operation) {
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 93407692efa..4243e1e5143 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
@@ -126,6 +126,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPool3DGradGrad";
+  
   private Output output;
   
   private MaxPool3dGradGrad(Operation operation) {
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 7db3693e736..6f5cbd2ce64 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPoolGradV2";
+  
   private Output output;
   
   private MaxPoolGrad(Operation operation) {
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 9fee7af4c0e..4f9255e9286 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPoolGradGradV2";
+  
   private Output output;
   
   private MaxPoolGradGrad(Operation operation) {
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 232f2ec18a8..6258024daa9 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
@@ -118,6 +118,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPoolGradGradWithArgmax";
+  
   private Output output;
   
   private MaxPoolGradGradWithArgmax(Operation operation) {
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 8d1aa1da798..329c88b4d33 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPoolGradWithArgmax";
+  
   private Output output;
   
   private MaxPoolGradWithArgmax(Operation operation) {
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 4eeb66cbc68..63f92de1fea 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
@@ -147,6 +147,9 @@ public Output argmax() {
     return argmax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxPoolWithArgmax";
+  
   private Output output;
   private Output argmax;
   
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 cf379fa5ecf..340cd4b98f7 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
@@ -111,6 +111,9 @@ public Output asOutput() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NthElement";
+  
   private Output values;
   
   private NthElement(Operation operation) {
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 9ac24133f7c..0da9f10b1ef 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
@@ -92,6 +92,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedAvgPool";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 dd5b716b401..41cc16017fc 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
@@ -115,6 +115,9 @@ public Output resultMax() {
     return resultMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedBatchNormWithGlobalNormalization";
+  
   private Output result;
   private Output resultMin;
   private Output resultMax;
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 818c4455ac5..62a8002ad49 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
@@ -86,6 +86,9 @@ public Output maxOut() {
     return maxOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedBiasAdd";
+  
   private Output output;
   private Output minOut;
   private Output maxOut;
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 f1258c3ac71..961a4245155 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
@@ -149,6 +149,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DAndRelu";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 9a763e629d9..8b231edc09b 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
@@ -153,6 +153,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DAndReluAndRequantize";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 ac1ca66f079..8c9f1247d97 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
@@ -153,6 +153,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DAndRequantize";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 da2dfa6e491..efc0132e2a8 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
@@ -131,6 +131,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DPerChannel";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 da843bf735a..bc78b5b4ec1 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
@@ -151,6 +151,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DWithBias";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 6176626745d..719150ee139 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
@@ -151,6 +151,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DWithBiasAndRelu";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 d6700e175a5..a61cab41d5e 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
@@ -155,6 +155,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DWithBiasAndReluAndRequantize";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 7f8d24095e4..af89fd48962 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
@@ -155,6 +155,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DWithBiasAndRequantize";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 cc3d6cc73dc..cfa7770cf25 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
@@ -161,6 +161,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DWithBiasSignedSumAndReluAndRequantize";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 69759e0bc8a..1096fa12578 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
@@ -153,6 +153,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DWithBiasSumAndRelu";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 e6d03b99188..55adb0e016d 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
@@ -161,6 +161,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2DWithBiasSumAndReluAndRequantize";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 c791a624c51..39913922bdb 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
@@ -145,6 +145,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConv2D";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 2145de9c8eb..f64d9a7efbb 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
@@ -131,6 +131,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedDepthwiseConv2D";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 5aa0d466d0e..be5e2bb8657 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
@@ -133,6 +133,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedDepthwiseConv2DWithBias";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 46e628f2c29..8abd12b865f 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
@@ -156,6 +156,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedDepthwiseConv2DWithBiasAndRelu";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 3a13eaaa567..78c8048266e 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
@@ -160,6 +160,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 ba393889984..839338a1458 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
@@ -190,6 +190,9 @@ public Output yMax() {
     return yMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedInstanceNorm";
+  
   private Output y;
   private Output yMin;
   private Output yMax;
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 94c00253cc5..2cec96e411c 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
@@ -92,6 +92,9 @@ public Output maxOutput() {
     return maxOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMaxPool";
+  
   private Output output;
   private Output minOutput;
   private Output maxOutput;
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 9c9407e0b9a..308e14e9512 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
@@ -79,6 +79,9 @@ public Output maxActivations() {
     return maxActivations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedRelu";
+  
   private Output activations;
   private Output minActivations;
   private Output maxActivations;
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 150ec50779e..46f04fd5722 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
@@ -79,6 +79,9 @@ public Output maxActivations() {
     return maxActivations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedRelu6";
+  
   private Output activations;
   private Output minActivations;
   private Output maxActivations;
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 2d446c3a45d..e47a6a5c043 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
@@ -81,6 +81,9 @@ public Output maxActivations() {
     return maxActivations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedReluX";
+  
   private Output activations;
   private Output minActivations;
   private Output maxActivations;
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 2facaa697ec..c6a515d4c75 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return activations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Relu";
+  
   private Output activations;
   
   private Relu(Operation operation) {
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 f32eb410f00..e4e674b7e35 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return activations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Relu6";
+  
   private Output activations;
   
   private Relu6(Operation operation) {
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 7cd8e3197e6..cf4edc9debf 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Relu6Grad";
+  
   private Output backprops;
   
   private Relu6Grad(Operation operation) {
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 c467c606b69..d1c7cf7d44c 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReluGrad";
+  
   private Output backprops;
   
   private ReluGrad(Operation operation) {
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 dae469aa5a3..2ce8484b299 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return activations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Selu";
+  
   private Output activations;
   
   private Selu(Operation operation) {
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 91389503235..514ad00b38d 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SeluGrad";
+  
   private Output backprops;
   
   private SeluGrad(Operation operation) {
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 c1744627645..d9971b6667d 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return softmax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Softmax";
+  
   private Output softmax;
   
   private Softmax(Operation operation) {
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 e117be94537..e4276c679a3 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return activations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Softsign";
+  
   private Output activations;
   
   private Softsign(Operation operation) {
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 2c4fd467661..220763e57a2 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SoftsignGrad";
+  
   private Output backprops;
   
   private SoftsignGrad(Operation operation) {
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 b8ab8d48658..9b1796c99aa 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
@@ -142,6 +142,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SpaceToBatch";
+  
   private Output output;
   
   private SpaceToBatch(Operation operation) {
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 100ac91e7da..0e9068c9b31 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
@@ -171,6 +171,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SpaceToDepth";
+  
   private Output output;
   
   private SpaceToDepth(Operation operation) {
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 28a810ebc54..acd4ba679f7 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
@@ -116,6 +116,9 @@ public Output indices() {
     return indices;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TopKV2";
+  
   private Output values;
   private Output indices;
   

From 84f49db3fb6c085befabfcb8356ab77589facf5d Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 10:03:38 -0400
Subject: [PATCH 08/33] Generated classes now have public static final String
 OP_NAME = "XXXXXXXX";

---
 .../src/gen/java/org/tensorflow/op/audio/AudioSpectrogram.java | 3 +++
 .../src/gen/java/org/tensorflow/op/audio/DecodeWav.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/audio/EncodeWav.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/audio/Mfcc.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/bitwise/Invert.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/bitwise/LeftShift.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/bitwise/RightShift.java     | 3 +++
 .../org/tensorflow/op/cluster/KMC2ChainInitialization.java     | 3 +++
 .../tensorflow/op/cluster/KmeansPlusPlusInitialization.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/collective/AllReduce.java   | 3 +++
 .../gen/java/org/tensorflow/op/collective/BroadcastRecv.java   | 3 +++
 .../gen/java/org/tensorflow/op/collective/BroadcastSend.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Abort.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/All.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Any.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/core/AssertThat.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Assign.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/core/AssignAdd.java         | 3 +++
 .../gen/java/org/tensorflow/op/core/AssignAddVariableOp.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/AssignSub.java         | 3 +++
 .../gen/java/org/tensorflow/op/core/AssignSubVariableOp.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/AssignVariableOp.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Barrier.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/BarrierClose.java      | 3 +++
 .../gen/java/org/tensorflow/op/core/BarrierIncompleteSize.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/BarrierInsertMany.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/BarrierReadySize.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Batch.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/BatchToSpace.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Bitcast.java           | 3 +++
 .../gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java | 3 +++
 .../gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/BroadcastTo.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Bucketize.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ClipByValue.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/core/CollectiveGather.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Concat.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ConsumeMutexLock.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ControlTrigger.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Copy.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/CopyHost.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/CountUpTo.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/DecodeProto.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/core/DeepCopy.java          | 3 +++
 .../gen/java/org/tensorflow/op/core/DeleteSessionTensor.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/DestroyResourceOp.java | 3 +++
 .../java/org/tensorflow/op/core/DestroyTemporaryVariable.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/DummyMemoryCache.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/DynamicPartition.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/DynamicStitch.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/core/EditDistance.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Empty.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/EmptyTensorList.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/EncodeProto.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/core/EnsureShape.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Enter.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Exit.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ExpandDims.java        | 3 +++
 .../gen/java/org/tensorflow/op/core/ExtractVolumePatches.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Fill.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Fingerprint.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Gather.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/core/GatherNd.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/GetSessionHandle.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/GetSessionTensor.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/GuaranteeConst.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/HashTable.java         | 3 +++
 .../gen/java/org/tensorflow/op/core/HistogramFixedWidth.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Identity.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/IdentityN.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ImmutableConst.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/InitializeTable.java   | 3 +++
 .../org/tensorflow/op/core/InitializeTableFromTextFile.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/InplaceAdd.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/InplaceSub.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/InplaceUpdate.java     | 3 +++
 .../gen/java/org/tensorflow/op/core/IsVariableInitialized.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LinSpace.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LookupTableExport.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LookupTableFind.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LookupTableImport.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LookupTableInsert.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LookupTableRemove.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LookupTableSize.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LoopCond.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/LowerBound.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MapClear.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MapPeek.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MapSize.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MapStage.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MapUnstage.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Max.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Merge.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Min.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MirrorPad.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java | 3 +++
 .../gen/java/org/tensorflow/op/core/MutableDenseHashTable.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MutableHashTable.java  | 3 +++
 .../java/org/tensorflow/op/core/MutableHashTableOfTensors.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Mutex.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/MutexLock.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/NcclAllReduce.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/core/NcclBroadcast.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/core/NcclReduce.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/NextIteration.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/core/NoOp.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/OneHot.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/core/OnesLike.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/OrderedMapClear.java   | 3 +++
 .../java/org/tensorflow/op/core/OrderedMapIncompleteSize.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/OrderedMapSize.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/OrderedMapStage.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java | 3 +++
 .../java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Pad.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ParallelConcat.java    | 3 +++
 .../gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Placeholder.java       | 3 +++
 .../java/org/tensorflow/op/core/PlaceholderWithDefault.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Print.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Prod.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/QuantizedReshape.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Range.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Rank.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReadVariableOp.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Recv.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReduceAll.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReduceAny.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReduceMax.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReduceMin.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReduceProd.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReduceSum.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/RefEnter.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/RefExit.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/RefIdentity.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/core/RefMerge.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/RefNextIteration.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/core/RefSelect.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/RefSwitch.java         | 3 +++
 .../java/org/tensorflow/op/core/RemoteFusedGraphExecute.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Reshape.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ResourceGather.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java  | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterAdd.java    | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterDiv.java    | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterMax.java    | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterMin.java    | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterMul.java    | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterNdAdd.java  | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterNdSub.java  | 3 +++
 .../java/org/tensorflow/op/core/ResourceScatterNdUpdate.java   | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterSub.java    | 3 +++
 .../gen/java/org/tensorflow/op/core/ResourceScatterUpdate.java | 3 +++
 .../org/tensorflow/op/core/ResourceStridedSliceAssign.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Reverse.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ReverseSequence.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Roll.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Rpc.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterAdd.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterDiv.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterMax.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterMin.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterMul.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterNd.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java      | 3 +++
 .../java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterNdSub.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterSub.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ScatterUpdate.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Select.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Send.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/SetDiff1d.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/SetSize.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Shape.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/ShapeN.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Size.java              | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Skipgram.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Slice.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Snapshot.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Split.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/SplitV.java            | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Squeeze.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Stack.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/Stage.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/core/StageClear.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/core/StagePeek.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/StageSize.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/core/StopGradient.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/core/StridedSlice.java      | 3 +++
 .../gen/java/org/tensorflow/op/core/StridedSliceAssign.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java  | 3 +++
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 .../gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java | 3 +++
 .../gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java | 3 +++
 .../java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java | 3 +++
 .../java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java | 3 +++
 .../java/org/tensorflow/op/sparse/SparseReduceSumSparse.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseReorder.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseReshape.java   | 3 +++
 .../gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java   | 3 +++
 .../java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java   | 3 +++
 .../tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java | 3 +++
 .../gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java  | 3 +++
 .../java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java  | 3 +++
 .../op/sparse/SparseSegmentSqrtNWithNumSegments.java           | 3 +++
 .../gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java    | 3 +++
 .../tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseSlice.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java   | 3 +++
 .../gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java | 3 +++
 .../gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseSplit.java     | 3 +++
 .../java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java    | 3 +++
 .../java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java | 3 +++
 .../src/gen/java/org/tensorflow/op/sparse/SparseToDense.java   | 3 +++
 .../org/tensorflow/op/sparse/SparseToSparseSetOperation.java   | 3 +++
 .../org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/Join.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/Lower.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/ReduceJoin.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/RegexFullMatch.java | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/RegexReplace.java   | 3 +++
 .../java/org/tensorflow/op/strings/StaticRegexFullMatch.java   | 3 +++
 .../gen/java/org/tensorflow/op/strings/StaticRegexReplace.java | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/StringFormat.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/StringLength.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/StringNGrams.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/StringSplit.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/Strip.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/Substr.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/ToHashBucket.java   | 3 +++
 .../gen/java/org/tensorflow/op/strings/ToHashBucketFast.java   | 3 +++
 .../gen/java/org/tensorflow/op/strings/ToHashBucketStrong.java | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/ToNumber.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java  | 3 +++
 .../org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/UnicodeScript.java  | 3 +++
 .../gen/java/org/tensorflow/op/strings/UnicodeTranscode.java   | 3 +++
 .../java/org/tensorflow/op/strings/UnsortedSegmentJoin.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/strings/Upper.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/AudioSummary.java   | 3 +++
 .../gen/java/org/tensorflow/op/summary/CloseSummaryWriter.java | 3 +++
 .../java/org/tensorflow/op/summary/CreateSummaryDbWriter.java  | 3 +++
 .../org/tensorflow/op/summary/CreateSummaryFileWriter.java     | 3 +++
 .../gen/java/org/tensorflow/op/summary/FlushSummaryWriter.java | 3 +++
 .../gen/java/org/tensorflow/op/summary/HistogramSummary.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/ImageSummary.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/ImportEvent.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/MergeSummary.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/ScalarSummary.java  | 3 +++
 .../java/org/tensorflow/op/summary/StatsAggregatorSummary.java | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/SummaryWriter.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/TensorSummary.java  | 3 +++
 .../gen/java/org/tensorflow/op/summary/WriteAudioSummary.java  | 3 +++
 .../gen/java/org/tensorflow/op/summary/WriteGraphSummary.java  | 3 +++
 .../java/org/tensorflow/op/summary/WriteHistogramSummary.java  | 3 +++
 .../gen/java/org/tensorflow/op/summary/WriteImageSummary.java  | 3 +++
 .../java/org/tensorflow/op/summary/WriteRawProtoSummary.java   | 3 +++
 .../gen/java/org/tensorflow/op/summary/WriteScalarSummary.java | 3 +++
 .../src/gen/java/org/tensorflow/op/summary/WriteSummary.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/AllToAll.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/CollectivePermute.java  | 3 +++
 .../java/org/tensorflow/op/tpu/ConfigureDistributedTPU.java    | 3 +++
 .../gen/java/org/tensorflow/op/tpu/ConfigureTPUEmbedding.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java    | 3 +++
 .../org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java | 3 +++
 .../org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java  | 3 +++
 .../op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java      | 3 +++
 .../tensorflow/op/tpu/InfeedEnqueuePrelinearizedBuffer.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java | 3 +++
 .../org/tensorflow/op/tpu/LoadTPUEmbeddingADAMParameters.java  | 3 +++
 .../op/tpu/LoadTPUEmbeddingADAMParametersGradAccumDebug.java   | 3 +++
 .../tensorflow/op/tpu/LoadTPUEmbeddingAdadeltaParameters.java  | 3 +++
 .../tpu/LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.java  | 3 +++
 .../tensorflow/op/tpu/LoadTPUEmbeddingAdagradParameters.java   | 3 +++
 .../tpu/LoadTPUEmbeddingAdagradParametersGradAccumDebug.java   | 3 +++
 .../op/tpu/LoadTPUEmbeddingCenteredRMSPropParameters.java      | 3 +++
 .../org/tensorflow/op/tpu/LoadTPUEmbeddingFTRLParameters.java  | 3 +++
 .../op/tpu/LoadTPUEmbeddingFTRLParametersGradAccumDebug.java   | 3 +++
 .../op/tpu/LoadTPUEmbeddingMDLAdagradLightParameters.java      | 3 +++
 .../tensorflow/op/tpu/LoadTPUEmbeddingMomentumParameters.java  | 3 +++
 .../tpu/LoadTPUEmbeddingMomentumParametersGradAccumDebug.java  | 3 +++
 .../op/tpu/LoadTPUEmbeddingProximalAdagradParameters.java      | 3 +++
 ...oadTPUEmbeddingProximalAdagradParametersGradAccumDebug.java | 3 +++
 .../tensorflow/op/tpu/LoadTPUEmbeddingRMSPropParameters.java   | 3 +++
 .../tpu/LoadTPUEmbeddingRMSPropParametersGradAccumDebug.java   | 3 +++
 .../LoadTPUEmbeddingStochasticGradientDescentParameters.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java     | 3 +++
 .../gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/OutfeedEnqueue.java     | 3 +++
 .../gen/java/org/tensorflow/op/tpu/OutfeedEnqueueTuple.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/Prelinearize.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java  | 3 +++
 .../org/tensorflow/op/tpu/RecvTPUEmbeddingActivations.java     | 3 +++
 .../tensorflow/op/tpu/RetrieveTPUEmbeddingADAMParameters.java  | 3 +++
 .../tpu/RetrieveTPUEmbeddingADAMParametersGradAccumDebug.java  | 3 +++
 .../op/tpu/RetrieveTPUEmbeddingAdadeltaParameters.java         | 3 +++
 .../RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.java  | 3 +++
 .../op/tpu/RetrieveTPUEmbeddingAdagradParameters.java          | 3 +++
 .../RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.java   | 3 +++
 .../op/tpu/RetrieveTPUEmbeddingCenteredRMSPropParameters.java  | 3 +++
 .../tensorflow/op/tpu/RetrieveTPUEmbeddingFTRLParameters.java  | 3 +++
 .../tpu/RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.java  | 3 +++
 .../op/tpu/RetrieveTPUEmbeddingMDLAdagradLightParameters.java  | 3 +++
 .../op/tpu/RetrieveTPUEmbeddingMomentumParameters.java         | 3 +++
 .../RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.java  | 3 +++
 .../op/tpu/RetrieveTPUEmbeddingProximalAdagradParameters.java  | 3 +++
 ...eveTPUEmbeddingProximalAdagradParametersGradAccumDebug.java | 3 +++
 .../op/tpu/RetrieveTPUEmbeddingRMSPropParameters.java          | 3 +++
 .../RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.java   | 3 +++
 ...etrieveTPUEmbeddingStochasticGradientDescentParameters.java | 3 +++
 .../java/org/tensorflow/op/tpu/SendTPUEmbeddingGradients.java  | 3 +++
 .../gen/java/org/tensorflow/op/tpu/ShutdownDistributedTPU.java | 3 +++
 .../gen/java/org/tensorflow/op/tpu/TPUCompilationResult.java   | 3 +++
 .../java/org/tensorflow/op/tpu/TPUEmbeddingActivations.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/TPUOrdinalSelector.java | 3 +++
 .../gen/java/org/tensorflow/op/tpu/TPUReplicateMetadata.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java | 3 +++
 .../gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/tpu/WorkerHeartbeat.java    | 3 +++
 .../java/org/tensorflow/op/train/AccumulatorApplyGradient.java | 3 +++
 .../org/tensorflow/op/train/AccumulatorNumAccumulated.java     | 3 +++
 .../java/org/tensorflow/op/train/AccumulatorSetGlobalStep.java | 3 +++
 .../java/org/tensorflow/op/train/AccumulatorTakeGradient.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyAdam.java        | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyAddSign.java     | 3 +++
 .../gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyFtrl.java        | 3 +++
 .../gen/java/org/tensorflow/op/train/ApplyGradientDescent.java | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyMomentum.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java   | 3 +++
 .../gen/java/org/tensorflow/op/train/ApplyProximalAdagrad.java | 3 +++
 .../org/tensorflow/op/train/ApplyProximalGradientDescent.java  | 3 +++
 .../src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/train/BatchMatMul.java      | 3 +++
 .../java/org/tensorflow/op/train/ConditionalAccumulator.java   | 3 +++
 .../java/org/tensorflow/op/train/GenerateVocabRemapping.java   | 3 +++
 .../gen/java/org/tensorflow/op/train/MergeV2Checkpoints.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/train/NegTrain.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/train/PreventGradient.java  | 3 +++
 .../tensorflow/op/train/ResourceAccumulatorApplyGradient.java  | 3 +++
 .../tensorflow/op/train/ResourceAccumulatorNumAccumulated.java | 3 +++
 .../tensorflow/op/train/ResourceAccumulatorSetGlobalStep.java  | 3 +++
 .../tensorflow/op/train/ResourceAccumulatorTakeGradient.java   | 3 +++
 .../gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java  | 3 +++
 .../java/org/tensorflow/op/train/ResourceApplyAdadelta.java    | 3 +++
 .../gen/java/org/tensorflow/op/train/ResourceApplyAdagrad.java | 3 +++
 .../java/org/tensorflow/op/train/ResourceApplyAdagradDa.java   | 3 +++
 .../gen/java/org/tensorflow/op/train/ResourceApplyAdam.java    | 3 +++
 .../org/tensorflow/op/train/ResourceApplyAdamWithAmsgrad.java  | 3 +++
 .../gen/java/org/tensorflow/op/train/ResourceApplyAddSign.java | 3 +++
 .../org/tensorflow/op/train/ResourceApplyCenteredRmsProp.java  | 3 +++
 .../gen/java/org/tensorflow/op/train/ResourceApplyFtrl.java    | 3 +++
 .../org/tensorflow/op/train/ResourceApplyGradientDescent.java  | 3 +++
 .../org/tensorflow/op/train/ResourceApplyKerasMomentum.java    | 3 +++
 .../java/org/tensorflow/op/train/ResourceApplyMomentum.java    | 3 +++
 .../java/org/tensorflow/op/train/ResourceApplyPowerSign.java   | 3 +++
 .../org/tensorflow/op/train/ResourceApplyProximalAdagrad.java  | 3 +++
 .../op/train/ResourceApplyProximalGradientDescent.java         | 3 +++
 .../gen/java/org/tensorflow/op/train/ResourceApplyRmsProp.java | 3 +++
 .../tensorflow/op/train/ResourceConditionalAccumulator.java    | 3 +++
 .../org/tensorflow/op/train/ResourceSparseApplyAdadelta.java   | 3 +++
 .../org/tensorflow/op/train/ResourceSparseApplyAdagrad.java    | 3 +++
 .../org/tensorflow/op/train/ResourceSparseApplyAdagradDa.java  | 3 +++
 .../org/tensorflow/op/train/ResourceSparseApplyAdagradV2.java  | 3 +++
 .../op/train/ResourceSparseApplyCenteredRmsProp.java           | 3 +++
 .../java/org/tensorflow/op/train/ResourceSparseApplyFtrl.java  | 3 +++
 .../tensorflow/op/train/ResourceSparseApplyKerasMomentum.java  | 3 +++
 .../org/tensorflow/op/train/ResourceSparseApplyMomentum.java   | 3 +++
 .../op/train/ResourceSparseApplyProximalAdagrad.java           | 3 +++
 .../op/train/ResourceSparseApplyProximalGradientDescent.java   | 3 +++
 .../org/tensorflow/op/train/ResourceSparseApplyRmsProp.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/train/Restore.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/train/RestoreSlice.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/train/Save.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/train/SaveSlices.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/train/SdcaFprint.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/train/SdcaOptimizer.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/train/SdcaShrinkL1.java     | 3 +++
 .../gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java  | 3 +++
 .../gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java   | 3 +++
 .../gen/java/org/tensorflow/op/train/SparseApplyAdagradDa.java | 3 +++
 .../org/tensorflow/op/train/SparseApplyCenteredRmsProp.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/train/SparseApplyFtrl.java  | 3 +++
 .../gen/java/org/tensorflow/op/train/SparseApplyMomentum.java  | 3 +++
 .../org/tensorflow/op/train/SparseApplyProximalAdagrad.java    | 3 +++
 .../op/train/SparseApplyProximalGradientDescent.java           | 3 +++
 .../gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java   | 3 +++
 .../src/gen/java/org/tensorflow/op/train/TileGrad.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/BroadcastHelper.java    | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/ClusterOutput.java      | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Conv.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Dequantize.java         | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Dot.java                | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/DynamicSlice.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/DynamicUpdateSlice.java | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Einsum.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Gather.java             | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/KeyValueSort.java       | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Pad.java                | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Recv.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/ReplicaId.java          | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/SelfAdjointEig.java     | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Send.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Sharding.java           | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Sort.java               | 3 +++
 .../src/gen/java/org/tensorflow/op/xla/Svd.java                | 3 +++
 1002 files changed, 3006 insertions(+)

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 6774323de4d..28fdb7791bc 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
@@ -127,6 +127,9 @@ public Output asOutput() {
     return spectrogram;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AudioSpectrogram";
+  
   private Output spectrogram;
   
   private AudioSpectrogram(Operation operation) {
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 a58d814660c..ec80ffdaf7c 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
@@ -132,6 +132,9 @@ public Output sampleRate() {
     return sampleRate;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeWav";
+  
   private Output audio;
   private Output sampleRate;
   
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 2336a3124c5..b1920318564 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return contents;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EncodeWav";
+  
   private Output contents;
   
   private EncodeWav(Operation operation) {
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 a13d22fdb4a..07ab4a13215 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
@@ -165,6 +165,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Mfcc";
+  
   private Output output;
   
   private Mfcc(Operation operation) {
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 70318891190..e199ff2201f 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BitwiseAnd";
+  
   private Output z;
   
   private BitwiseAnd(Operation operation) {
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 4d882a6c202..264c2bc340b 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BitwiseOr";
+  
   private Output z;
   
   private BitwiseOr(Operation operation) {
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 597ae15fb90..1d8f668c175 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BitwiseXor";
+  
   private Output z;
   
   private BitwiseXor(Operation operation) {
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 6cbacade24d..9f8bdfd56d8 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
@@ -103,6 +103,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Invert";
+  
   private Output y;
   
   private Invert(Operation operation) {
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 bddf9269c42..f7a47534d81 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
@@ -95,6 +95,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LeftShift";
+  
   private Output z;
   
   private LeftShift(Operation operation) {
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 92487345d8c..99c5fe5766e 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
@@ -98,6 +98,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RightShift";
+  
   private Output z;
   
   private RightShift(Operation operation) {
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 350036bbdc6..272695dad5c 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return index;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "KMC2ChainInitialization";
+  
   private Output index;
   
   private KMC2ChainInitialization(Operation operation) {
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 a8d6f3eb70b..63d8ef01222 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return samples;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "KmeansPlusPlusInitialization";
+  
   private Output samples;
   
   private KmeansPlusPlusInitialization(Operation operation) {
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 40125fa7856..3776697d4e0 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
@@ -135,6 +135,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CollectiveReduce";
+  
   private Output output;
   
   private AllReduce(Operation operation) {
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 c754a3d9dea..babdee94a27 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CollectiveBcastRecv";
+  
   private Output output;
   
   private BroadcastRecv(Operation operation) {
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 72f721a9fa3..41b8faa0f67 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
@@ -103,6 +103,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CollectiveBcastSend";
+  
   private Output output;
   
   private BroadcastSend(Operation operation) {
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 6fde31b3dbc..53e9401dfa2 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
@@ -101,6 +101,9 @@ public static Options exitWithoutError(Boolean exitWithoutError) {
     return new Options().exitWithoutError(exitWithoutError);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Abort";
+  
   
   private Abort(Operation operation) {
     super(operation);
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 2c92e6934cc..909427d1a57 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "All";
+  
   private Output output;
   
   private All(Operation operation) {
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 c30305b2207..0316e5e1a94 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Any";
+  
   private Output output;
   
   private Any(Operation operation) {
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 a56b01c90aa..950830b7462 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
@@ -87,6 +87,9 @@ public static Options summarize(Long summarize) {
     return new Options().summarize(summarize);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Assert";
+  
   
   private AssertThat(Operation operation) {
     super(operation);
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 c0319759f33..27f66d3da23 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
@@ -127,6 +127,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Assign";
+  
   private Output outputRef;
   
   private Assign(Operation operation) {
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 9208756aa95..770842d2764 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AssignAdd";
+  
   private Output outputRef;
   
   private AssignAdd(Operation operation) {
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 3725c318637..5adaccf15e0 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
@@ -52,6 +52,9 @@ public static  AssignAddVariableOp create(Scope scope, Operand<
     return new AssignAddVariableOp(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AssignAddVariableOp";
+  
   
   private AssignAddVariableOp(Operation operation) {
     super(operation);
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 13506b03543..37841e0dadc 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AssignSub";
+  
   private Output outputRef;
   
   private AssignSub(Operation operation) {
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 c47fc330702..4bb683c97d2 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
@@ -52,6 +52,9 @@ public static  AssignSubVariableOp create(Scope scope, Operand<
     return new AssignSubVariableOp(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AssignSubVariableOp";
+  
   
   private AssignSubVariableOp(Operation operation) {
     super(operation);
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 bdd89c0204d..90cabd12a24 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
@@ -52,6 +52,9 @@ public static  AssignVariableOp create(Scope scope, Operand
     return new AssignVariableOp(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AssignVariableOp";
+  
   
   private AssignVariableOp(Operation operation) {
     super(operation);
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 dea40abd45c..b9c5c84083f 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
@@ -181,6 +181,9 @@ public Output asOutput() {
     return handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Barrier";
+  
   private Output handle;
   
   private Barrier(Operation operation) {
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 2b1cbc84c2b..a777d684ec1 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
@@ -92,6 +92,9 @@ public static Options cancelPendingEnqueues(Boolean cancelPendingEnqueues) {
     return new Options().cancelPendingEnqueues(cancelPendingEnqueues);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BarrierClose";
+  
   
   private BarrierClose(Operation operation) {
     super(operation);
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 62bcdcf1e56..72dbe1533d6 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BarrierIncompleteSize";
+  
   private Output size;
   
   private BarrierIncompleteSize(Operation operation) {
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 8e16fe1df11..31488738838 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
@@ -60,6 +60,9 @@ public static  BarrierInsertMany create(Scope scope, Operand asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BarrierReadySize";
+  
   private Output size;
   
   private BarrierReadySize(Operation operation) {
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 481cdcd1d7a..6c391fab5fa 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
@@ -172,6 +172,9 @@ public List> values() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BarrierTakeMany";
+  
   private Output indices;
   private Output keys;
   private List> values;
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 895ad5e3c77..21d7cf0a6c0 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
@@ -228,6 +228,9 @@ public Output id() {
     return id;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Batch";
+  
   private List> batchedTensors;
   private Output batchIndex;
   private Output id;
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 3d1fc8af44e..b20c60ee4ac 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
@@ -134,6 +134,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchToSpace";
+  
   private Output output;
   
   private BatchToSpace(Operation operation) {
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 8c2a3d9b703..ef6f31d0f89 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
@@ -168,6 +168,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchToSpaceND";
+  
   private Output output;
   
   private BatchToSpaceNd(Operation operation) {
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 fa7777e0d98..b01c8598ae6 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
@@ -115,6 +115,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Bitcast";
+  
   private Output output;
   
   private Bitcast(Operation operation) {
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 88758189167..3027e8234a4 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return r0;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BroadcastArgs";
+  
   private Output r0;
   
   private BroadcastDynamicShape(Operation operation) {
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 309cfef9430..2d95c71086e 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
@@ -66,6 +66,9 @@ public Output r1() {
     return r1;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BroadcastGradientArgs";
+  
   private Output r0;
   private Output r1;
   
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 e4c1b80764f..7e1a7b89324 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BroadcastTo";
+  
   private Output output;
   
   private BroadcastTo(Operation operation) {
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 f7f32115de1..84e9b454d0d 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Bucketize";
+  
   private Output output;
   
   private Bucketize(Operation operation) {
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 1c33f21ba98..8a5b99d9389 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ClipByValue";
+  
   private Output output;
   
   private ClipByValue(Operation operation) {
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 da4f82ad2a2..22ce5634f75 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CollectiveGather";
+  
   private Output output;
   
   private CollectiveGather(Operation operation) {
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 eb62cb86bf5..9782b3d6ec9 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ConcatV2";
+  
   private Output output;
   
   private Concat(Operation operation) {
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 8a7440297f3..39dd4ffc7d9 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
@@ -54,6 +54,9 @@ public static ConsumeMutexLock create(Scope scope, Operand mutexLock) {
     return new ConsumeMutexLock(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ConsumeMutexLock";
+  
   
   private ConsumeMutexLock(Operation operation) {
     super(operation);
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 9c1baf17ed3..721112b8204 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
@@ -45,6 +45,9 @@ public static ControlTrigger create(Scope scope) {
     return new ControlTrigger(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ControlTrigger";
+  
   
   private ControlTrigger(Operation operation) {
     super(operation);
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 6ca879bf1b9..fb9cbbb122a 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
@@ -135,6 +135,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Copy";
+  
   private Output output;
   
   private Copy(Operation operation) {
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 b57961ead25..566258c0430 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
@@ -133,6 +133,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CopyHost";
+  
   private Output output;
   
   private CopyHost(Operation operation) {
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 84dfbc90633..2884783695d 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CountUpTo";
+  
   private Output output;
   
   private CountUpTo(Operation operation) {
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 8a423575c08..28af55f8465 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
@@ -206,6 +206,9 @@ public List> values() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeProtoV2";
+  
   private Output sizes;
   private List> values;
   
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 0abe365a8a9..da22489acc9 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeepCopy";
+  
   private Output y;
   
   private DeepCopy(Operation operation) {
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 2da72b19db9..50c7615a0ff 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
@@ -47,6 +47,9 @@ public static DeleteSessionTensor create(Scope scope, Operand handle) {
     return new DeleteSessionTensor(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeleteSessionTensor";
+  
   
   private DeleteSessionTensor(Operation operation) {
     super(operation);
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 dc494cea751..e1958682ee1 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
@@ -85,6 +85,9 @@ public static Options ignoreLookupError(Boolean ignoreLookupError) {
     return new Options().ignoreLookupError(ignoreLookupError);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DestroyResourceOp";
+  
   
   private DestroyResourceOp(Operation operation) {
     super(operation);
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 65fa9c62e4a..7941a7a5870 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return value;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DestroyTemporaryVariable";
+  
   private Output value;
   
   private DestroyTemporaryVariable(Operation operation) {
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 c5a6187d1ed..56f16d48a9b 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
@@ -56,6 +56,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DummyMemoryCache";
+  
   private Output handle;
   
   private DummyMemoryCache(Operation operation) {
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 48dd3b54f8e..d9da09b5d34 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
@@ -104,6 +104,9 @@ public Iterator> iterator() {
     return (Iterator) outputs.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DynamicPartition";
+  
   private List> outputs;
   
   @SuppressWarnings("unchecked")
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 ba41dcf77f8..b7dd72f8a57 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
@@ -120,6 +120,9 @@ public Output asOutput() {
     return merged;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DynamicStitch";
+  
   private Output merged;
   
   private DynamicStitch(Operation operation) {
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 7c0a35798d5..29423a3c548 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
@@ -151,6 +151,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EditDistance";
+  
   private Output output;
   
   private EditDistance(Operation operation) {
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 0e39ea25f92..c8305349d37 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
@@ -102,6 +102,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Empty";
+  
   private Output output;
   
   private Empty(Operation operation) {
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 e91ebafbb03..619fb90657f 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EmptyTensorList";
+  
   private Output handle;
   
   private EmptyTensorList(Operation operation) {
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 6f2e448d053..4d0396dcb9d 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
@@ -147,6 +147,9 @@ public Output asOutput() {
     return bytes;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EncodeProto";
+  
   private Output bytes;
   
   private EncodeProto(Operation operation) {
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 3b8a8790afa..8ea86427b7c 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EnsureShape";
+  
   private Output output;
   
   private EnsureShape(Operation operation) {
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 d6802061959..fa19763defb 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
@@ -122,6 +122,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Enter";
+  
   private Output output;
   
   private Enter(Operation operation) {
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 879225e5dbc..4e42bb0bb0e 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Exit";
+  
   private Output output;
   
   private Exit(Operation operation) {
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 12cb36b98dc..eb0e977e163 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
@@ -97,6 +97,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExpandDims";
+  
   private Output output;
   
   private ExpandDims(Operation operation) {
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 6816275860b..0b9bcd78e20 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return patches;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExtractVolumePatches";
+  
   private Output patches;
   
   private ExtractVolumePatches(Operation operation) {
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 adbcc23f363..79b827ea2aa 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
@@ -91,6 +91,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Fill";
+  
   private Output output;
   
   private Fill(Operation operation) {
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 4aca6b0201e..0ea88f2b1f1 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
@@ -96,6 +96,9 @@ public Output asOutput() {
     return fingerprint;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Fingerprint";
+  
   private Output fingerprint;
   
   private Fingerprint(Operation operation) {
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 8eaec57f813..f40581ef26c 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
@@ -130,6 +130,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GatherV2";
+  
   private Output output;
   
   private Gather(Operation operation) {
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 917db87705f..e932794001e 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
@@ -159,6 +159,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GatherNd";
+  
   private Output output;
   
   private GatherNd(Operation operation) {
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 57754705177..93a31f1cba1 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GetSessionHandleV2";
+  
   private Output handle;
   
   private GetSessionHandle(Operation operation) {
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 634b23ed56c..93ba5af508c 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return value;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GetSessionTensor";
+  
   private Output value;
   
   private GetSessionTensor(Operation operation) {
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 ff9064f3ac9..df0a48ad28f 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GuaranteeConst";
+  
   private Output output;
   
   private GuaranteeConst(Operation operation) {
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 2b097647e32..87d9cab4c3f 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
@@ -146,6 +146,9 @@ public Output asOutput() {
     return (Output) tableHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "HashTableV2";
+  
   private Output tableHandle;
   
   private HashTable(Operation operation) {
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 b7f7a90a90d..da1c1a7b713 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "HistogramFixedWidth";
+  
   private Output out;
   
   private HistogramFixedWidth(Operation operation) {
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 32c3d0d4cab..1cafffdf5c9 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Identity";
+  
   private Output output;
   
   private Identity(Operation operation) {
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 4ad5ab1f261..e000005eabf 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
@@ -80,6 +80,9 @@ public Iterator> iterator() {
     return (Iterator) output.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IdentityN";
+  
   private List> output;
   
   private IdentityN(Operation operation) {
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 c301ab66ca4..ecbc3154498 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return tensor;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ImmutableConst";
+  
   private Output tensor;
   
   private ImmutableConst(Operation operation) {
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 2ffb3c37290..5de2ca6ff07 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
@@ -51,6 +51,9 @@ public static  InitializeTable create(Scope sc
     return new InitializeTable(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InitializeTableV2";
+  
   
   private InitializeTable(Operation operation) {
     super(operation);
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 672bf052e49..0a88cea3ef2 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
@@ -118,6 +118,9 @@ public static Options delimiter(String delimiter) {
     return new Options().delimiter(delimiter);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InitializeTableFromTextFileV2";
+  
   
   private InitializeTableFromTextFile(Operation operation) {
     super(operation);
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 5eab2e36d95..8de34bc569f 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InplaceAdd";
+  
   private Output y;
   
   private InplaceAdd(Operation operation) {
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 7ff3c5ef9bc..999f793c869 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InplaceSub";
+  
   private Output y;
   
   private InplaceSub(Operation operation) {
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 877c9400f7f..a7c616cbbc2 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InplaceUpdate";
+  
   private Output y;
   
   private InplaceUpdate(Operation operation) {
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 f4f6bf5fe36..e9dc32ec1d7 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return isInitialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IsVariableInitialized";
+  
   private Output isInitialized;
   
   private IsVariableInitialized(Operation operation) {
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 c8b4d2dfa95..5dbd14154de 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LinSpace";
+  
   private Output output;
   
   private LinSpace(Operation operation) {
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 0f31790fe45..6bebbb35895 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
@@ -70,6 +70,9 @@ public Output values() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LookupTableExportV2";
+  
   private Output keys;
   private Output values;
   
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 e0dbead12d2..bfc8e92e16f 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LookupTableFindV2";
+  
   private Output values;
   
   private LookupTableFind(Operation operation) {
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 3df4d4653e0..a94393a50f1 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
@@ -54,6 +54,9 @@ public static  LookupTableImport create(Scope
     return new LookupTableImport(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LookupTableImportV2";
+  
   
   private LookupTableImport(Operation operation) {
     super(operation);
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 9e355312479..c31784ea942 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
@@ -54,6 +54,9 @@ public static  LookupTableInsert create(Scope
     return new LookupTableInsert(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LookupTableInsertV2";
+  
   
   private LookupTableInsert(Operation operation) {
     super(operation);
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 875bbfa486c..584e7e1325c 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
@@ -51,6 +51,9 @@ public static  LookupTableRemove create(Scope scope, Operand
     return new LookupTableRemove(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LookupTableRemoveV2";
+  
   
   private LookupTableRemove(Operation operation) {
     super(operation);
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 441c2208bd3..10e84953496 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LookupTableSizeV2";
+  
   private Output size;
   
   private LookupTableSize(Operation operation) {
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 bef80f40840..57b82598f84 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoopCond";
+  
   private Output output;
   
   private LoopCond(Operation operation) {
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 dfce8ac4d1f..6f0f5158cca 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
@@ -103,6 +103,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LowerBound";
+  
   private Output output;
   
   private LowerBound(Operation operation) {
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 5ffc0da9c6c..ea7581ef2c7 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
@@ -142,6 +142,9 @@ public static Options sharedName(String sharedName) {
     return new Options().sharedName(sharedName);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MapClear";
+  
   
   private MapClear(Operation operation) {
     super(operation);
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 a4522bb2993..19e9e87a08a 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MapIncompleteSize";
+  
   private Output size;
   
   private MapIncompleteSize(Operation operation) {
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 38087a7b46f..1925ca680ea 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
@@ -168,6 +168,9 @@ public Iterator> iterator() {
     return (Iterator) values.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MapPeek";
+  
   private List> values;
   
   private MapPeek(Operation operation) {
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 20a2b619d1e..7f4eea906f5 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MapSize";
+  
   private Output size;
   
   private MapSize(Operation operation) {
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 cc09bdf78a2..5d72ce8f22f 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
@@ -157,6 +157,9 @@ public static Options sharedName(String sharedName) {
     return new Options().sharedName(sharedName);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MapStage";
+  
   
   private MapStage(Operation operation) {
     super(operation);
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 932c1f4f970..849f6f3ef6a 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
@@ -168,6 +168,9 @@ public Iterator> iterator() {
     return (Iterator) values.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MapUnstage";
+  
   private List> values;
   
   private MapUnstage(Operation operation) {
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 a915362108e..10a119ec6c4 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
@@ -164,6 +164,9 @@ public List> values() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MapUnstageNoKey";
+  
   private Output key;
   private List> values;
   
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 e97fc9d17ca..94bcd0f544c 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Max";
+  
   private Output output;
   
   private Max(Operation operation) {
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 476253b5601..41eca5fc33f 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
@@ -72,6 +72,9 @@ public Output valueIndex() {
     return valueIndex;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Merge";
+  
   private Output output;
   private Output valueIndex;
   
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 c19b8eaefdf..ed8ea366e7a 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Min";
+  
   private Output output;
   
   private Min(Operation operation) {
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 beb9448138c..6c8292a671a 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
@@ -98,6 +98,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MirrorPad";
+  
   private Output output;
   
   private MirrorPad(Operation operation) {
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 ee3a76eab9f..7b1727c3fb5 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
@@ -86,6 +86,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MirrorPadGrad";
+  
   private Output output;
   
   private MirrorPadGrad(Operation operation) {
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 fc482784607..a6c92896683 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
@@ -103,6 +103,9 @@ public Iterator> iterator() {
     return (Iterator) outputs.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MlirPassthroughOp";
+  
   private List> outputs;
   
   private MlirPassthroughOp(Operation operation) {
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 1b5fca24ce2..4ff3c1f3ea6 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
@@ -212,6 +212,9 @@ public Output asOutput() {
     return (Output) tableHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MutableDenseHashTableV2";
+  
   private Output tableHandle;
   
   private MutableDenseHashTable(Operation operation) {
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 74d304d82ab..a11789f9f34 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
@@ -146,6 +146,9 @@ public Output asOutput() {
     return (Output) tableHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MutableHashTableV2";
+  
   private Output tableHandle;
   
   private MutableHashTable(Operation operation) {
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 6ef45423fba..975f040ae3b 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
@@ -164,6 +164,9 @@ public Output asOutput() {
     return (Output) tableHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MutableHashTableOfTensorsV2";
+  
   private Output tableHandle;
   
   private MutableHashTableOfTensors(Operation operation) {
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 41f57d9a755..1af2b439372 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return (Output) resource;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MutexV2";
+  
   private Output resource;
   
   private Mutex(Operation operation) {
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 e67ea7a228b..de28b8f5025 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return (Output) mutexLock;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MutexLock";
+  
   private Output mutexLock;
   
   private MutexLock(Operation operation) {
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 179e8f08e1d..a44611b5a41 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NcclAllReduce";
+  
   private Output output;
   
   private NcclAllReduce(Operation operation) {
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 70339b3853a..da0832e437a 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NcclBroadcast";
+  
   private Output output;
   
   private NcclBroadcast(Operation operation) {
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 c6376f1a908..ced1473e60a 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NcclReduce";
+  
   private Output output;
   
   private NcclReduce(Operation operation) {
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 99f0fa0dd1b..69b6be6a810 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NextIteration";
+  
   private Output output;
   
   private NextIteration(Operation operation) {
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 aa37e24c61a..862aabcd795 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
@@ -43,6 +43,9 @@ public static NoOp create(Scope scope) {
     return new NoOp(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NoOp";
+  
   
   private NoOp(Operation operation) {
     super(operation);
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 9b4d6a4927d..442b9ae9108 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
@@ -185,6 +185,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OneHot";
+  
   private Output output;
   
   private OneHot(Operation operation) {
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 5d9ce5861c2..986d0201f26 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OnesLike";
+  
   private Output y;
   
   private OnesLike(Operation operation) {
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 df85e76bc3b..29f4133ce09 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
@@ -142,6 +142,9 @@ public static Options sharedName(String sharedName) {
     return new Options().sharedName(sharedName);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OrderedMapClear";
+  
   
   private OrderedMapClear(Operation operation) {
     super(operation);
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 9ae3fd09642..865810568db 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OrderedMapIncompleteSize";
+  
   private Output size;
   
   private OrderedMapIncompleteSize(Operation operation) {
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 dd7fc0e3f40..21c6adcc039 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
@@ -169,6 +169,9 @@ public Iterator> iterator() {
     return (Iterator) values.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OrderedMapPeek";
+  
   private List> values;
   
   private OrderedMapPeek(Operation operation) {
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 d16383393f4..afdee7de1bd 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OrderedMapSize";
+  
   private Output size;
   
   private OrderedMapSize(Operation operation) {
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 c752a0dd84e..b51f94c148a 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
@@ -159,6 +159,9 @@ public static Options sharedName(String sharedName) {
     return new Options().sharedName(sharedName);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OrderedMapStage";
+  
   
   private OrderedMapStage(Operation operation) {
     super(operation);
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 c44e344638d..e2460e42dd8 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
@@ -168,6 +168,9 @@ public Iterator> iterator() {
     return (Iterator) values.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OrderedMapUnstage";
+  
   private List> values;
   
   private OrderedMapUnstage(Operation operation) {
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 d0fa6beea68..f20a23b9806 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
@@ -164,6 +164,9 @@ public List> values() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OrderedMapUnstageNoKey";
+  
   private Output key;
   private List> values;
   
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 c21f7aa9a58..205e6ab0a62 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
@@ -91,6 +91,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PadV2";
+  
   private Output output;
   
   private Pad(Operation operation) {
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 ed9af9dde57..e373612bb68 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
@@ -83,6 +83,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParallelConcat";
+  
   private Output output;
   
   private ParallelConcat(Operation operation) {
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 3fd6514f285..2770fa01591 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
@@ -119,6 +119,9 @@ public Output asOutput() {
     return merged;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParallelDynamicStitch";
+  
   private Output merged;
   
   private ParallelDynamicStitch(Operation operation) {
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 c9c7727fcf8..caef9fc0783 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Placeholder";
+  
   private Output output;
   
   private Placeholder(Operation operation) {
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 e794a0623cb..59a9ca223ab 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PlaceholderWithDefault";
+  
   private Output output;
   
   private PlaceholderWithDefault(Operation operation) {
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 1f341e11de5..3e96c00d369 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
@@ -102,6 +102,9 @@ public static Options end(String end) {
     return new Options().end(end);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PrintV2";
+  
   
   private Print(Operation operation) {
     super(operation);
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 b9b7b8b65a4..6bf1b7cd37d 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Prod";
+  
   private Output output;
   
   private Prod(Operation operation) {
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 f4996cd8875..e644855bbc9 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
@@ -80,6 +80,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedReshape";
+  
   private Output output;
   private Output outputMin;
   private Output outputMax;
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 5134f49c314..967a490382e 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Range";
+  
   private Output output;
   
   private Range(Operation operation) {
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 f7e1959280d..071551d6492 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Rank";
+  
   private Output output;
   
   private Rank(Operation operation) {
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 c535547a925..aa2d1d2b9b2 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return value;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReadVariableOp";
+  
   private Output value;
   
   private ReadVariableOp(Operation operation) {
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 5feb610b6fd..db6511c1583 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
@@ -110,6 +110,9 @@ public Output asOutput() {
     return tensor;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Recv";
+  
   private Output tensor;
   
   private Recv(Operation operation) {
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 195a7bbbce8..9a5ad026ac8 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "All";
+  
   private Output output;
   
   private ReduceAll(Operation operation) {
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 9dde0ff6238..de479629f97 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Any";
+  
   private Output output;
   
   private ReduceAny(Operation operation) {
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 1df06cb441d..997481542b8 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Max";
+  
   private Output output;
   
   private ReduceMax(Operation operation) {
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 2ebdaa01247..60d64c3a58c 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Min";
+  
   private Output output;
   
   private ReduceMin(Operation operation) {
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 37fcf044469..7c9872758b1 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Prod";
+  
   private Output output;
   
   private ReduceProd(Operation operation) {
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 82bf9d35558..f87e5b22e15 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sum";
+  
   private Output output;
   
   private ReduceSum(Operation operation) {
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 bec8abb5f80..8292dcbb379 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
@@ -121,6 +121,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RefEnter";
+  
   private Output output;
   
   private RefEnter(Operation operation) {
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 80399854da4..d8896a59211 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RefExit";
+  
   private Output output;
   
   private RefExit(Operation operation) {
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 e3840bfa886..9deff66c3a9 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RefIdentity";
+  
   private Output output;
   
   private RefIdentity(Operation operation) {
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 eab96521ea6..990cfaaadb6 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
@@ -71,6 +71,9 @@ public Output valueIndex() {
     return valueIndex;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RefMerge";
+  
   private Output output;
   private Output valueIndex;
   
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 bb1423440fd..c151662820e 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RefNextIteration";
+  
   private Output output;
   
   private RefNextIteration(Operation operation) {
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 23864ed4820..8be3ae40e9e 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RefSelect";
+  
   private Output output;
   
   private RefSelect(Operation operation) {
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 b45250bb083..f0128f668fc 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
@@ -72,6 +72,9 @@ public Output outputTrue() {
     return outputTrue;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RefSwitch";
+  
   private Output outputFalse;
   private Output outputTrue;
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java
index 0242749bda6..bd76549c976 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java
@@ -83,6 +83,9 @@ public Iterator> iterator() {
     return (Iterator) outputs.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RemoteFusedGraphExecute";
+  
   private List> outputs;
   
   private RemoteFusedGraphExecute(Operation operation) {
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 eaeaa5ded4e..2829a332b0e 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
@@ -124,6 +124,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Reshape";
+  
   private Output output;
   
   private Reshape(Operation operation) {
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 cce86ab05ce..19f630dd014 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceCountUpTo";
+  
   private Output output;
   
   private ResourceCountUpTo(Operation operation) {
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 fd8ccc35cfa..38aa1fbd407 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
@@ -134,6 +134,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceGather";
+  
   private Output output;
   
   private ResourceGather(Operation operation) {
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 f2c501ec524..85e422179f7 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceGatherNd";
+  
   private Output output;
   
   private ResourceGatherNd(Operation operation) {
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 630a3716695..5383062823b 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
@@ -72,6 +72,9 @@ public static  ResourceScatterAdd create(Sco
     return new ResourceScatterAdd(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterAdd";
+  
   
   private ResourceScatterAdd(Operation operation) {
     super(operation);
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 dba2e37ec12..ed950863242 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
@@ -72,6 +72,9 @@ public static  ResourceScatterDiv create(Sco
     return new ResourceScatterDiv(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterDiv";
+  
   
   private ResourceScatterDiv(Operation operation) {
     super(operation);
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 6068660a905..7553fab4812 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
@@ -72,6 +72,9 @@ public static  ResourceScatterMax create(Sco
     return new ResourceScatterMax(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterMax";
+  
   
   private ResourceScatterMax(Operation operation) {
     super(operation);
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 3e0ffeae23a..68518b4c640 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
@@ -72,6 +72,9 @@ public static  ResourceScatterMin create(Sco
     return new ResourceScatterMin(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterMin";
+  
   
   private ResourceScatterMin(Operation operation) {
     super(operation);
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 1a8feb21838..f52b338de57 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
@@ -72,6 +72,9 @@ public static  ResourceScatterMul create(Sco
     return new ResourceScatterMul(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterMul";
+  
   
   private ResourceScatterMul(Operation operation) {
     super(operation);
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 a230b7d58bf..5abfcbea5ee 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
@@ -122,6 +122,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterNdAdd";
+  
   
   private ResourceScatterNdAdd(Operation operation) {
     super(operation);
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 9912c63f129..c4b6060d611 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
@@ -122,6 +122,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterNdSub";
+  
   
   private ResourceScatterNdSub(Operation operation) {
     super(operation);
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 625010c6aac..b47fb4a1367 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
@@ -124,6 +124,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterNdUpdate";
+  
   
   private ResourceScatterNdUpdate(Operation operation) {
     super(operation);
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 727dc01ab32..2559ff21a93 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
@@ -72,6 +72,9 @@ public static  ResourceScatterSub create(Sco
     return new ResourceScatterSub(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterSub";
+  
   
   private ResourceScatterSub(Operation operation) {
     super(operation);
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 c75107a4bb7..eff04c6c08a 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
@@ -63,6 +63,9 @@ public static  ResourceScatterUpdate create(
     return new ResourceScatterUpdate(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterUpdate";
+  
   
   private ResourceScatterUpdate(Operation operation) {
     super(operation);
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 10c93185348..2002140573b 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
@@ -173,6 +173,9 @@ public static Options shrinkAxisMask(Long shrinkAxisMask) {
     return new Options().shrinkAxisMask(shrinkAxisMask);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceStridedSliceAssign";
+  
   
   private ResourceStridedSliceAssign(Operation operation) {
     super(operation);
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 e64e165182f..340336ee9f9 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReverseV2";
+  
   private Output output;
   
   private Reverse(Operation operation) {
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 a78de7f9a4c..46fd2b54aa9 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
@@ -155,6 +155,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReverseSequence";
+  
   private Output output;
   
   private ReverseSequence(Operation operation) {
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 8f6559ca09f..761be92e533 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
@@ -96,6 +96,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Roll";
+  
   private Output output;
   
   private Roll(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rpc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rpc.java
index 2d753afec51..ad3195933bc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rpc.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Rpc.java
@@ -196,6 +196,9 @@ public Output asOutput() {
     return response;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Rpc";
+  
   private Output response;
   
   private Rpc(Operation operation) {
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 5d18510e225..c91e799a643 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
@@ -127,6 +127,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterAdd";
+  
   private Output outputRef;
   
   private ScatterAdd(Operation operation) {
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 800dada981d..12a27c67960 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterDiv";
+  
   private Output outputRef;
   
   private ScatterDiv(Operation operation) {
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 99e97ee0d23..20b84f016ea 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
@@ -127,6 +127,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterMax";
+  
   private Output outputRef;
   
   private ScatterMax(Operation operation) {
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 3b96560077a..5010da14eaa 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
@@ -127,6 +127,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterMin";
+  
   private Output outputRef;
   
   private ScatterMin(Operation operation) {
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 38305790fb5..ba0892e1a04 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterMul";
+  
   private Output outputRef;
   
   private ScatterMul(Operation operation) {
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 c59c526ca86..86acb2935db 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
@@ -145,6 +145,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterNd";
+  
   private Output output;
   
   private ScatterNd(Operation operation) {
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 11b1ddc0ef8..09192e601e9 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
@@ -138,6 +138,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterNdAdd";
+  
   private Output outputRef;
   
   private ScatterNdAdd(Operation operation) {
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 400f7e8b11c..98ce3cceba4 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterNdNonAliasingAdd";
+  
   private Output output;
   
   private ScatterNdNonAliasingAdd(Operation operation) {
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 bbeafdaa08b..39327cd553d 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
@@ -140,6 +140,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterNdSub";
+  
   private Output outputRef;
   
   private ScatterNdSub(Operation operation) {
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 c715f6c1c92..87e5949c07c 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
@@ -142,6 +142,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterNdUpdate";
+  
   private Output outputRef;
   
   private ScatterNdUpdate(Operation operation) {
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 5bdb1e39081..bad245da96e 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
@@ -126,6 +126,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterSub";
+  
   private Output outputRef;
   
   private ScatterSub(Operation operation) {
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 fc548962aa7..9790e2fc934 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
@@ -130,6 +130,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterUpdate";
+  
   private Output outputRef;
   
   private ScatterUpdate(Operation operation) {
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 fff55e1cf71..0aaa338eb1a 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SelectV2";
+  
   private Output output;
   
   private Select(Operation operation) {
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 04f1f5813b3..bf3db1cd88a 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
@@ -94,6 +94,9 @@ public static Options clientTerminated(Boolean clientTerminated) {
     return new Options().clientTerminated(clientTerminated);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Send";
+  
   
   private Send(Operation operation) {
     super(operation);
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 1b13994eebc..c7e458931e5 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
@@ -105,6 +105,9 @@ public Output idx() {
     return idx;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ListDiff";
+  
   private Output out;
   private Output 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 bd666afe4b2..2fcdf728542 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
@@ -109,6 +109,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SetSize";
+  
   private Output size;
   
   private SetSize(Operation operation) {
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 aef7aec2816..5d613401fc5 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Shape";
+  
   private Output output;
   
   private Shape(Operation operation) {
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 307e86b38a2..42340a8a83d 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
@@ -85,6 +85,9 @@ public Iterator> iterator() {
     return (Iterator) output.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ShapeN";
+  
   private List> output;
   
   @SuppressWarnings("unchecked")
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 d79f317a591..4aaccae0f30 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
@@ -88,6 +88,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Size";
+  
   private Output output;
   
   private Size(Operation operation) {
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 cef935f3389..9c63d317f98 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
@@ -176,6 +176,9 @@ public Output labels() {
     return labels;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Skipgram";
+  
   private Output vocabWord;
   private Output vocabFreq;
   private Output wordsPerEpoch;
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 e141b0a2243..31edde00b81 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Slice";
+  
   private Output output;
   
   private Slice(Operation operation) {
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 8599dac37e6..7209bccaaee 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Snapshot";
+  
   private Output output;
   
   private Snapshot(Operation operation) {
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 80e9a72e37f..150e18256e5 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
@@ -167,6 +167,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SpaceToBatchND";
+  
   private Output output;
   
   private SpaceToBatchNd(Operation operation) {
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 f810c353427..fffd73f8ef5 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
@@ -75,6 +75,9 @@ public Iterator> iterator() {
     return (Iterator) output.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Split";
+  
   private List> output;
   
   @SuppressWarnings("unchecked")
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 49646eecfc2..02b740c4d03 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
@@ -79,6 +79,9 @@ public Iterator> iterator() {
     return (Iterator) output.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SplitV";
+  
   private List> output;
   
   @SuppressWarnings("unchecked")
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 5bc2ba50645..3f962adc789 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Squeeze";
+  
   private Output output;
   
   private Squeeze(Operation operation) {
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 6e98ac9ab4b..f70f50b0d2b 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Pack";
+  
   private Output output;
   
   private Stack(Operation operation) {
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 c741a3ae391..408b6eca252 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
@@ -148,6 +148,9 @@ public static Options sharedName(String sharedName) {
     return new Options().sharedName(sharedName);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Stage";
+  
   
   private Stage(Operation operation) {
     super(operation);
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 ebe153dab5e..755e7ab72d9 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
@@ -142,6 +142,9 @@ public static Options sharedName(String sharedName) {
     return new Options().sharedName(sharedName);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StageClear";
+  
   
   private StageClear(Operation operation) {
     super(operation);
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 0d00e7f1db9..2126de722df 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
@@ -166,6 +166,9 @@ public Iterator> iterator() {
     return (Iterator) values.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StagePeek";
+  
   private List> values;
   
   private StagePeek(Operation operation) {
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 a6069a51690..94ef566e708 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StageSize";
+  
   private Output size;
   
   private StageSize(Operation operation) {
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 f884e7b98f7..b3c7d144ca5 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
@@ -86,6 +86,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StopGradient";
+  
   private Output output;
   
   private StopGradient(Operation operation) {
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 e19467389c2..719fb0787c7 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
@@ -304,6 +304,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StridedSlice";
+  
   private Output output;
   
   private StridedSlice(Operation operation) {
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 e89e6657ad7..b6836c65fca 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
@@ -187,6 +187,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StridedSliceAssign";
+  
   private Output outputRef;
   
   private StridedSliceAssign(Operation operation) {
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 f475104bc81..241d6d567e9 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
@@ -189,6 +189,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StridedSliceGrad";
+  
   private Output output;
   
   private StridedSliceGrad(Operation operation) {
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 4fe6e275bad..c153cdf4760 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sum";
+  
   private Output output;
   
   private Sum(Operation operation) {
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 b0abd4c0d55..191eb6292d2 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
@@ -72,6 +72,9 @@ public Output outputTrue() {
     return outputTrue;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Switch";
+  
   private Output outputFalse;
   private Output outputTrue;
   
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 dedd9f6d588..43d9247fe21 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return ref;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TemporaryVariable";
+  
   private Output ref;
   
   private TemporaryVariable(Operation operation) {
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 24b9a610f1f..f34dc414484 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
@@ -204,6 +204,9 @@ public Output flow() {
     return flow;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayV3";
+  
   private Output handle;
   private Output flow;
   
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 fe58e12dd65..a16e856ae72 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
@@ -49,6 +49,9 @@ public static TensorArrayClose create(Scope scope, Operand handle) {
     return new TensorArrayClose(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayCloseV3";
+  
   
   private TensorArrayClose(Operation operation) {
     super(operation);
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 1c39d8922bb..e25b7a2f958 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
@@ -126,6 +126,9 @@ public Output lengths() {
     return lengths;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayConcatV3";
+  
   private Output value;
   private Output lengths;
   
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 cd697f550d3..13c6dce3122 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return value;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayGatherV3";
+  
   private Output value;
   
   private TensorArrayGather(Operation operation) {
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 a4cf654bdcc..dca362c6934 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
@@ -102,6 +102,9 @@ public Output flowOut() {
     return flowOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayGradV3";
+  
   private Output gradHandle;
   private Output flowOut;
   
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 7ffbc95fac5..6128775dce6 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
@@ -75,6 +75,9 @@ public Output flowOut() {
     return flowOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayGradWithShape";
+  
   private Output gradHandle;
   private Output flowOut;
   
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 05643c5d774..4b4be4ac089 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
@@ -101,6 +101,9 @@ public Output asOutput() {
     return value;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayPack";
+  
   private Output value;
   
   private TensorArrayPack(Operation operation) {
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 22065261a6a..55cf48bb020 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return value;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayReadV3";
+  
   private Output value;
   
   private TensorArrayRead(Operation operation) {
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 f31f6b1428a..7b3eb238026 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return flowOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayScatterV3";
+  
   private Output flowOut;
   
   private TensorArrayScatter(Operation operation) {
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 89642346996..3e7987bc388 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArraySizeV3";
+  
   private Output size;
   
   private TensorArraySize(Operation operation) {
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 ca755929b77..d6aedc34a4a 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
@@ -91,6 +91,9 @@ public Output asOutput() {
     return flowOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArraySplitV3";
+  
   private Output flowOut;
   
   private TensorArraySplit(Operation operation) {
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 7d9e2b68ae1..9d2d92c4b85 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return flowOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayUnpack";
+  
   private Output flowOut;
   
   private TensorArrayUnpack(Operation operation) {
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 8f5c56e524a..a83a07a458b 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return flowOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorArrayWriteV3";
+  
   private Output flowOut;
   
   private TensorArrayWrite(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java
index ec0df709465..e647f58b2f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java
@@ -48,6 +48,9 @@ public static TensorForestCreateTreeVariable create(Scope scope, Operand tree
     return new TensorForestCreateTreeVariable(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorForestCreateTreeVariable";
+  
   
   private TensorForestCreateTreeVariable(Operation operation) {
     super(operation);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java
index a7585be7577..5fb704b2361 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java
@@ -48,6 +48,9 @@ public static TensorForestTreeDeserialize create(Scope scope, Operand treeHan
     return new TensorForestTreeDeserialize(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorForestTreeDeserialize";
+  
   
   private TensorForestTreeDeserialize(Operation operation) {
     super(operation);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeIsInitializedOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeIsInitializedOp.java
index d0c39ab0de9..4dfe64cdf19 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeIsInitializedOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeIsInitializedOp.java
@@ -59,6 +59,9 @@ public Output asOutput() {
     return isInitialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorForestTreeIsInitializedOp";
+  
   private Output isInitialized;
   
   private TensorForestTreeIsInitializedOp(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreePredict.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreePredict.java
index 3b8dc79c2d9..3962212c5b7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreePredict.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreePredict.java
@@ -63,6 +63,9 @@ public Output asOutput() {
     return logits;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorForestTreePredict";
+  
   private Output logits;
   
   private TensorForestTreePredict(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeResourceHandleOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeResourceHandleOp.java
index f56d34d8df0..c72860e1ea7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeResourceHandleOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeResourceHandleOp.java
@@ -110,6 +110,9 @@ public Output asOutput() {
     return (Output) resource;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorForestTreeResourceHandleOp";
+  
   private Output resource;
   
   private TensorForestTreeResourceHandleOp(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSerialize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSerialize.java
index 07838bb9028..d46e23a08ab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSerialize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSerialize.java
@@ -59,6 +59,9 @@ public Output asOutput() {
     return treeConfig;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorForestTreeSerialize";
+  
   private Output treeConfig;
   
   private TensorForestTreeSerialize(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSize.java
index 03eddda317e..17cf008d470 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeSize.java
@@ -59,6 +59,9 @@ public Output asOutput() {
     return treeSize;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorForestTreeSize";
+  
   private Output treeSize;
   
   private TensorForestTreeSize(Operation operation) {
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 249e6a07b1d..2f1771797e0 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
@@ -84,6 +84,9 @@ public Output lengths() {
     return lengths;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListConcatV2";
+  
   private Output tensor;
   private Output lengths;
   
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 3d685a10b34..fdca8e2d6cd 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListConcatLists";
+  
   private Output output;
   
   private TensorListConcatLists(Operation operation) {
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 4115dfebda5..2c3e3a5b90c 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return elementShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListElementShape";
+  
   private Output elementShape;
   
   private TensorListElementShape(Operation operation) {
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 8569b6b936c..97a45046767 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListFromTensor";
+  
   private Output outputHandle;
   
   private TensorListFromTensor(Operation operation) {
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 b1c4aa520fb..dbb565a29a6 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListGather";
+  
   private Output values;
   
   private TensorListGather(Operation operation) {
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 1ee5e084768..9af925e1425 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return item;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListGetItem";
+  
   private Output item;
   
   private TensorListGetItem(Operation operation) {
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 c901d022f64..d2dc93a6e06 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return length;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListLength";
+  
   private Output length;
   
   private TensorListLength(Operation operation) {
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 f4fb817b2fc..96fd3433e07 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
@@ -75,6 +75,9 @@ public Output tensor() {
     return tensor;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListPopBack";
+  
   private Output outputHandle;
   private Output tensor;
   
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 216a5d44c4b..3bde4981422 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListPushBack";
+  
   private Output outputHandle;
   
   private TensorListPushBack(Operation operation) {
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 065e7d0b6ed..de772f74891 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return (Output) outputHandles;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListPushBackBatch";
+  
   private Output outputHandles;
   
   private TensorListPushBackBatch(Operation operation) {
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 0c3294795c1..3f798e0f998 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListReserve";
+  
   private Output handle;
   
   private TensorListReserve(Operation operation) {
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 fb0380aa5a7..4b70c31f277 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListResize";
+  
   private Output outputHandle;
   
   private TensorListResize(Operation operation) {
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 12fd2667321..700e3e715a7 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListScatterV2";
+  
   private Output outputHandle;
   
   private TensorListScatter(Operation operation) {
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 4d8d27ed14a..4b91b1bc0b3 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListScatterIntoExistingList";
+  
   private Output outputHandle;
   
   private TensorListScatterIntoExistingList(Operation operation) {
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 d570a3083a4..358397a927e 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListSetItem";
+  
   private Output outputHandle;
   
   private TensorListSetItem(Operation operation) {
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 aed272880fb..e93635d7713 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListSplit";
+  
   private Output outputHandle;
   
   private TensorListSplit(Operation operation) {
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 95075e1bb6d..c0ecf388b3d 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
@@ -108,6 +108,9 @@ public Output asOutput() {
     return tensor;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorListStack";
+  
   private Output tensor;
   
   private TensorListStack(Operation operation) {
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 77ffefde6f5..22c7462b994 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
@@ -126,6 +126,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorScatterAdd";
+  
   private Output output;
   
   private TensorScatterNdAdd(Operation operation) {
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 307a2d4b801..14737a1fd95 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
@@ -126,6 +126,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorScatterSub";
+  
   private Output output;
   
   private TensorScatterNdSub(Operation operation) {
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 ac7d0635b66..7dff39f733f 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
@@ -142,6 +142,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorScatterUpdate";
+  
   private Output output;
   
   private TensorScatterNdUpdate(Operation operation) {
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 d3bf1403073..c8c5e36e3c6 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
@@ -187,6 +187,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorStridedSliceUpdate";
+  
   private Output output;
   
   private TensorStridedSliceUpdate(Operation operation) {
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 abd9d462993..d28588cada5 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
@@ -91,6 +91,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Tile";
+  
   private Output output;
   
   private Tile(Operation operation) {
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 ef460f466cd..cbbf650a32f 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return ts;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Timestamp";
+  
   private Output ts;
   
   private Timestamp(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TryRpc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TryRpc.java
index acb69b45d48..3aa6c3a76ad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TryRpc.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TryRpc.java
@@ -209,6 +209,9 @@ public Output statusMessage() {
     return statusMessage;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TryRpc";
+  
   private Output response;
   private Output statusCode;
   private Output statusMessage;
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 5cb23e99e7e..84d2063ae8c 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
@@ -140,6 +140,9 @@ public Output asOutput() {
     return unbatchedTensor;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Unbatch";
+  
   private Output unbatchedTensor;
   
   private Unbatch(Operation operation) {
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 1309c7e80c8..10062f204fc 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
@@ -136,6 +136,9 @@ public Output asOutput() {
     return batchedGrad;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnbatchGrad";
+  
   private Output batchedGrad;
   
   private UnbatchGrad(Operation operation) {
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 9f203229625..f3b8b04aead 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
@@ -128,6 +128,9 @@ public Output idx() {
     return idx;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UniqueV2";
+  
   private Output y;
   private Output 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 a98e6736594..732d4432333 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
@@ -139,6 +139,9 @@ public Output count() {
     return count;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UniqueWithCountsV2";
+  
   private Output y;
   private Output idx;
   private Output count;
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 e272d05ec2a..ecc073e37a4 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnravelIndex";
+  
   private Output output;
   
   private UnravelIndex(Operation operation) {
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 fcf759828b7..a48f57289ae 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
@@ -117,6 +117,9 @@ public Iterator> iterator() {
     return (Iterator) output.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Unpack";
+  
   private List> output;
   
   @SuppressWarnings("unchecked")
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 806d2d451c4..1878ce6fb88 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
@@ -162,6 +162,9 @@ public Iterator> iterator() {
     return (Iterator) values.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Unstage";
+  
   private List> values;
   
   private Unstage(Operation operation) {
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 7f978707572..c46fbcba4de 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
@@ -103,6 +103,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UpperBound";
+  
   private Output output;
   
   private UpperBound(Operation operation) {
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 93a48a32093..945f05522c3 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
@@ -118,6 +118,9 @@ public Output asOutput() {
     return (Output) resource;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "VarHandleOp";
+  
   private Output resource;
   
   private VarHandleOp(Operation operation) {
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 0aaf43a2f1b..f2c3df0456d 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return isInitialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "VarIsInitializedOp";
+  
   private Output isInitialized;
   
   private VarIsInitializedOp(Operation operation) {
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 4f663493860..7353dfee688 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
@@ -127,6 +127,9 @@ public Output asOutput() {
     return ref;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "VariableV2";
+  
   private Output ref;
   
   private Variable(Operation operation) {
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 76fb3c770d0..6573cb8de11 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "VariableShape";
+  
   private Output output;
   
   private VariableShape(Operation operation) {
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 2e22fe12311..a1af7f9282a 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
@@ -120,6 +120,9 @@ public Output asOutput() {
     return index;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Where";
+  
   private Output index;
   
   private Where(Operation operation) {
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 60767fe78bf..5b9352ef6bd 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ZerosLike";
+  
   private Output y;
   
   private ZerosLike(Operation operation) {
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 d912c335063..bd3d1a400f5 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
@@ -76,6 +76,9 @@ public Output deleter() {
     return deleter;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AnonymousIteratorV2";
+  
   private Output handle;
   private Output deleter;
   
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 d76e74fdf14..4bc4523c1ea 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
@@ -54,6 +54,9 @@ public Output deleter() {
     return deleter;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AnonymousMemoryCache";
+  
   private Output handle;
   private Output deleter;
   
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 58ecad7ddce..bff57b33c8f 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
@@ -81,6 +81,9 @@ public Output deleter() {
     return deleter;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AnonymousMultiDeviceIterator";
+  
   private Output handle;
   private Output deleter;
   
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 0dff0c406cc..c2825e29b93 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
@@ -88,6 +88,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AssertNextDataset";
+  
   private Output handle;
   
   private AssertNextDataset(Operation operation) {
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 ab9d7753834..aca90031261 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
@@ -121,6 +121,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AutoShardDataset";
+  
   private Output handle;
   
   private AutoShardDataset(Operation operation) {
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 f85b08a64c5..b0fd6ef0c0c 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchDatasetV2";
+  
   private Output handle;
   
   private BatchDataset(Operation operation) {
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 a92c52ce5fd..a3b95d92909 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BytesProducedStatsDataset";
+  
   private Output handle;
   
   private BytesProducedStatsDataset(Operation operation) {
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 2374a884850..f6c8f72232d 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CSVDataset";
+  
   private Output handle;
   
   private CSVDataset(Operation operation) {
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 798519589d0..07384fb6b3e 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
@@ -83,6 +83,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CacheDataset";
+  
   private Output handle;
   
   private CacheDataset(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java
index f75ce86e7d0..ba370108e04 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java
@@ -78,6 +78,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CacheDatasetV2";
+  
   private Output handle;
   
   private CacheDatasetV2(Operation operation) {
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 e0acfa0e521..a8d9ce445fe 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ChooseFastestDataset";
+  
   private Output handle;
   
   private ChooseFastestDataset(Operation operation) {
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 0a9b49b8fe6..19cf0b4a706 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ConcatenateDataset";
+  
   private Output handle;
   
   private ConcatenateDataset(Operation operation) {
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 44d118b6d32..d851c211420 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return cardinality;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DatasetCardinality";
+  
   private Output cardinality;
   
   private DatasetCardinality(Operation operation) {
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 fa931c0cd72..6223baa7251 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DatasetFromGraph";
+  
   private Output handle;
   
   private DatasetFromGraph(Operation operation) {
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 908aea9eb42..afaab68330a 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
@@ -114,6 +114,9 @@ public Output asOutput() {
     return graph;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DatasetToGraphV2";
+  
   private Output graph;
   
   private DatasetToGraph(Operation operation) {
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 a37b7e51a96..91fd5032439 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
@@ -77,6 +77,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DatasetToSingleElement";
+  
   private List> components;
   
   private DatasetToSingleElement(Operation operation) {
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 237f73b12a3..41617c9b690 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
@@ -51,6 +51,9 @@ public static DatasetToTfRecord create(Scope scope, Operand inputDataset, Ope
     return new DatasetToTfRecord(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DatasetToTFRecord";
+  
   
   private DatasetToTfRecord(Operation operation) {
     super(operation);
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 5a92fcb5f82..ec3629a8eb7 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
@@ -48,6 +48,9 @@ public static DeleteIterator create(Scope scope, Operand handle, Operand d
     return new DeleteIterator(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeleteIterator";
+  
   
   private DeleteIterator(Operation operation) {
     super(operation);
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 06077aae830..3c0f37dc409 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
@@ -46,6 +46,9 @@ public static DeleteMemoryCache create(Scope scope, Operand handle, Operand multiDevi
     return new DeleteMultiDeviceIterator(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeleteMultiDeviceIterator";
+  
   
   private DeleteMultiDeviceIterator(Operation operation) {
     super(operation);
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 fe69f57646a..32bd135c325 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
@@ -82,6 +82,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DenseToSparseBatchDataset";
+  
   private Output handle;
   
   private DenseToSparseBatchDataset(Operation operation) {
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 a8c05b2d5ad..528fd09bc53 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
@@ -49,6 +49,9 @@ public static DeserializeIterator create(Scope scope, Operand resourceHandle,
     return new DeserializeIterator(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeserializeIterator";
+  
   
   private DeserializeIterator(Operation operation) {
     super(operation);
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 b2031c8fc11..6883e2218d9 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DirectedInterleaveDataset";
+  
   private Output handle;
   
   private DirectedInterleaveDataset(Operation operation) {
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 2adf749ab8a..d6c2b576d7e 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FilterByLastComponentDataset";
+  
   private Output output;
   
   private FilterByLastComponentDataset(Operation operation) {
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 47dbcf7c9ab..d1bfa77177b 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FixedLengthRecordDatasetV2";
+  
   private Output handle;
   
   private FixedLengthRecordDataset(Operation operation) {
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 e7a4c8d69dd..7ffca90d150 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IgnoreErrorsDataset";
+  
   private Output handle;
   
   private IgnoreErrorsDataset(Operation operation) {
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 5ada431831c..45030001714 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IteratorV2";
+  
   private Output handle;
   
   private Iterator(Operation operation) {
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 e394c9b347a..8264419635a 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
@@ -106,6 +106,9 @@ public Output asOutput() {
     return (Output) resourceHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IteratorFromStringHandleV2";
+  
   private Output resourceHandle;
   
   private IteratorFromStringHandle(Operation operation) {
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 d1ac024b6b2..d2aee159583 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
@@ -58,6 +58,9 @@ public Output asOutput() {
     return device;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IteratorGetDevice";
+  
   private Output device;
   
   private IteratorGetDevice(Operation operation) {
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 2b8e80de880..b7be406e7bd 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
@@ -77,6 +77,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IteratorGetNext";
+  
   private List> components;
   
   private IteratorGetNext(Operation operation) {
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 41382765531..682b7ba6f35 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
@@ -75,6 +75,9 @@ public Output asOutput() {
     return (Output) optional;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IteratorGetNextAsOptional";
+  
   private Output optional;
   
   private IteratorGetNextAsOptional(Operation operation) {
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 97f1ee35918..3cb4f072307 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
@@ -82,6 +82,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IteratorGetNextSync";
+  
   private List> components;
   
   private IteratorGetNextSync(Operation operation) {
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 19e8fcf2ed4..d715d8b8f2d 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return stringHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IteratorToStringHandle";
+  
   private Output stringHandle;
   
   private IteratorToStringHandle(Operation operation) {
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 9d8725757db..d0057d60323 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LMDBDataset";
+  
   private Output handle;
   
   private LMDBDataset(Operation operation) {
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 5391e373273..731b70867a7 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LatencyStatsDataset";
+  
   private Output handle;
   
   private LatencyStatsDataset(Operation operation) {
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 9832f573eda..3fb21bd4a6e 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LeakyReluGrad";
+  
   private Output backprops;
   
   private LeakyReluGrad(Operation operation) {
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 a2f380b0a49..685574a92d5 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
@@ -51,6 +51,9 @@ public static MakeIterator create(Scope scope, Operand dataset, Operand it
     return new MakeIterator(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MakeIterator";
+  
   
   private MakeIterator(Operation operation) {
     super(operation);
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 6a83be042c6..2c798a8d807 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatchingFilesDataset";
+  
   private Output handle;
   
   private MatchingFilesDataset(Operation operation) {
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 5f45170d93e..d7c67924b55 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MaxIntraOpParallelismDataset";
+  
   private Output handle;
   
   private MaxIntraOpParallelismDataset(Operation operation) {
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 ca8566ff06f..53b6f10204d 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
@@ -129,6 +129,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ModelDataset";
+  
   private Output handle;
   
   private ModelDataset(Operation operation) {
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 e4de4452636..a3dfeeb5665 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
@@ -85,6 +85,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MultiDeviceIterator";
+  
   private Output handle;
   
   private MultiDeviceIterator(Operation operation) {
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 a80f5d9cdc2..a9b0b8ec07e 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
@@ -108,6 +108,9 @@ public Output asOutput() {
     return (Output) multiDeviceIterator;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MultiDeviceIteratorFromStringHandle";
+  
   private Output multiDeviceIterator;
   
   private MultiDeviceIteratorFromStringHandle(Operation operation) {
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 6f2eeb28daa..4781bc2d56e 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
@@ -83,6 +83,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MultiDeviceIteratorGetNextFromShard";
+  
   private List> components;
   
   private MultiDeviceIteratorGetNextFromShard(Operation operation) {
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 fec8ee78e0b..a8e957c64b5 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return incarnationId;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MultiDeviceIteratorInit";
+  
   private Output incarnationId;
   
   private MultiDeviceIteratorInit(Operation operation) {
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 6f6045a848c..5697c7e7699 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return stringHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MultiDeviceIteratorToStringHandle";
+  
   private Output stringHandle;
   
   private MultiDeviceIteratorToStringHandle(Operation operation) {
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 e42a75dbf83..34043a14f9d 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NonSerializableDataset";
+  
   private Output handle;
   
   private NonSerializableDataset(Operation operation) {
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 b7e557c816d..73e27b3ffc9 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OptimizeDataset";
+  
   private Output handle;
   
   private OptimizeDataset(Operation operation) {
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 7832d3cbd58..a8fc1d4eaea 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return (Output) optional;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OptionalFromValue";
+  
   private Output optional;
   
   private OptionalFromValue(Operation operation) {
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 c38d1177c28..8d3be67da03 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
@@ -77,6 +77,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OptionalGetValue";
+  
   private List> components;
   
   private OptionalGetValue(Operation operation) {
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 d77f53ff5ca..af5900c38a9 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return hasValue;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OptionalHasValue";
+  
   private Output hasValue;
   
   private OptionalHasValue(Operation operation) {
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 ee871daef2e..fa3deabf28f 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
@@ -58,6 +58,9 @@ public Output asOutput() {
     return (Output) optional;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OptionalNone";
+  
   private Output optional;
   
   private OptionalNone(Operation operation) {
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 65da0acf0c8..0685e5e9e74 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
@@ -118,6 +118,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PaddedBatchDatasetV2";
+  
   private Output handle;
   
   private PaddedBatchDataset(Operation operation) {
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 a56c2e70054..78995ad6d20 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
@@ -131,6 +131,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PrefetchDataset";
+  
   private Output handle;
   
   private PrefetchDataset(Operation operation) {
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 d637c1b081a..b06618ce07a 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PrivateThreadPoolDataset";
+  
   private Output handle;
   
   private PrivateThreadPoolDataset(Operation operation) {
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 6549d26c515..2b944e789dc 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomDataset";
+  
   private Output handle;
   
   private RandomDataset(Operation operation) {
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 964d99e90e4..bc83590e03e 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RangeDataset";
+  
   private Output handle;
   
   private RangeDataset(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java
index baa5d56fea3..b5a21c7b6b8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java
@@ -116,6 +116,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RebatchDataset";
+  
   private Output handle;
   
   private RebatchDataset(Operation operation) {
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 85d27c01df8..b832025853c 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RepeatDataset";
+  
   private Output handle;
   
   private RepeatDataset(Operation operation) {
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 b9a584f0ac0..7876fe27587 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
@@ -89,6 +89,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SamplingDataset";
+  
   private Output handle;
   
   private SamplingDataset(Operation operation) {
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 8dc271706f3..f051994e6f5 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
@@ -96,6 +96,9 @@ public Output asOutput() {
     return (Output) serialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SerializeIterator";
+  
   private Output serialized;
   
   private SerializeIterator(Operation operation) {
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 b635c38df18..5181c0b1f71 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SetStatsAggregatorDataset";
+  
   private Output handle;
   
   private SetStatsAggregatorDataset(Operation operation) {
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 71864817d93..62e18f3fadf 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ShardDataset";
+  
   private Output handle;
   
   private ShardDataset(Operation operation) {
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 67bf83b9b5d..9234210b6d6 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ShuffleAndRepeatDataset";
+  
   private Output handle;
   
   private ShuffleAndRepeatDataset(Operation operation) {
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 ccc51d49a37..a31b296950d 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ShuffleDatasetV2";
+  
   private Output handle;
   
   private ShuffleDataset(Operation operation) {
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 7de29fc4976..4e409b5a4ea 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SkipDataset";
+  
   private Output handle;
   
   private SkipDataset(Operation operation) {
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 23f6e214ec4..67605099106 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SleepDataset";
+  
   private Output handle;
   
   private SleepDataset(Operation operation) {
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 2eb9ac29140..89f440efd77 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SlidingWindowDataset";
+  
   private Output handle;
   
   private SlidingWindowDataset(Operation operation) {
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 c166f4a4fd7..f6bc66e8297 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
@@ -363,6 +363,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SnapshotDataset";
+  
   private Output handle;
   
   private SnapshotDataset(Operation operation) {
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 9c45e99c9e3..fa5b61137ab 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseTensorSliceDataset";
+  
   private Output handle;
   
   private SparseTensorSliceDataset(Operation operation) {
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 9c8ef660137..59a0a47cd4d 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SqlDataset";
+  
   private Output handle;
   
   private SqlDataset(Operation operation) {
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 b96fcb2a07e..f510b437c7d 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
@@ -110,6 +110,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatsAggregatorHandle";
+  
   private Output handle;
   
   private StatsAggregatorHandle(Operation operation) {
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 9fb312ddac7..3229f055924 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TakeDataset";
+  
   private Output handle;
   
   private TakeDataset(Operation operation) {
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 35f30f733ae..974f9562859 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorDataset";
+  
   private Output handle;
   
   private TensorDataset(Operation operation) {
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 45fc9c1eef5..0d0ca40de32 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorSliceDataset";
+  
   private Output handle;
   
   private TensorSliceDataset(Operation operation) {
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 614d3bc2b4c..a80851bb2ed 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TextLineDataset";
+  
   private Output handle;
   
   private TextLineDataset(Operation operation) {
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 ba889f8f3af..4795e623f82 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TFRecordDataset";
+  
   private Output handle;
   
   private TfRecordDataset(Operation operation) {
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 b0443de050e..0b1ab263ffa 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ThreadPoolDataset";
+  
   private Output handle;
   
   private ThreadPoolDataset(Operation operation) {
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 9c5ad809be0..6d9434cdff3 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
@@ -139,6 +139,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ThreadPoolHandle";
+  
   private Output handle;
   
   private ThreadPoolHandle(Operation operation) {
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 e92d5a72d41..1bca9b693cc 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnbatchDataset";
+  
   private Output handle;
   
   private UnbatchDataset(Operation operation) {
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 fc7796939c2..817519ef6f8 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UniqueDataset";
+  
   private Output handle;
   
   private UniqueDataset(Operation operation) {
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 1ba2fb16027..d5125db92c8 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
@@ -58,6 +58,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnwrapDatasetVariant";
+  
   private Output outputHandle;
   
   private UnwrapDatasetVariant(Operation operation) {
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 c08069ff65f..d5edcc917d8 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
@@ -131,6 +131,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WindowDataset";
+  
   private Output handle;
   
   private WindowDataset(Operation operation) {
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 94ab283621f..bcea6df7895 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
@@ -58,6 +58,9 @@ public Output asOutput() {
     return (Output) outputHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WrapDatasetVariant";
+  
   private Output outputHandle;
   
   private WrapDatasetVariant(Operation operation) {
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 0829a5435c3..d4f54946f5f 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
@@ -82,6 +82,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ZipDataset";
+  
   private Output handle;
   
   private ZipDataset(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java
index 271026cab6c..96c02bf5fc1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AssertCardinalityDataset";
+  
   private Output handle;
   
   private AssertCardinalityDataset(Operation operation) {
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 3ced6851207..cd0c5300df6 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalAssertNextDataset";
+  
   private Output handle;
   
   private AssertNextDataset(Operation operation) {
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 e1a8ffbffbe..3c1eb053091 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
@@ -121,6 +121,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalAutoShardDataset";
+  
   private Output handle;
   
   private AutoShardDataset(Operation operation) {
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 aaf9e88a544..7fe1290b130 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalBytesProducedStatsDataset";
+  
   private Output handle;
   
   private BytesProducedStatsDataset(Operation operation) {
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 764d02ab240..d0498612cde 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
@@ -86,6 +86,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalCSVDataset";
+  
   private Output handle;
   
   private CSVDataset(Operation operation) {
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 a4335e73817..f731d948490 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalChooseFastestDataset";
+  
   private Output handle;
   
   private ChooseFastestDataset(Operation operation) {
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 290bec84df8..81ca505ca91 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return cardinality;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalDatasetCardinality";
+  
   private Output cardinality;
   
   private DatasetCardinality(Operation operation) {
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 3bb2bc62b4b..ee0f494fa73 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
@@ -51,6 +51,9 @@ public static DatasetToTFRecord create(Scope scope, Operand inputDataset, Ope
     return new DatasetToTFRecord(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalDatasetToTFRecord";
+  
   
   private DatasetToTFRecord(Operation operation) {
     super(operation);
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 550ddde8c54..d464f422836 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
@@ -82,6 +82,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalDenseToSparseBatchDataset";
+  
   private Output handle;
   
   private DenseToSparseBatchDataset(Operation operation) {
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 62ba3a97b7f..63a06a16201 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalDirectedInterleaveDataset";
+  
   private Output handle;
   
   private DirectedInterleaveDataset(Operation operation) {
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 77c750ea775..22d734831da 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalIgnoreErrorsDataset";
+  
   private Output handle;
   
   private IgnoreErrorsDataset(Operation operation) {
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 2e19177a58f..7602eca94fc 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
@@ -58,6 +58,9 @@ public Output asOutput() {
     return device;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalIteratorGetDevice";
+  
   private Output device;
   
   private IteratorGetDevice(Operation operation) {
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 6a54aa3586c..ad901295c28 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalLatencyStatsDataset";
+  
   private Output handle;
   
   private LatencyStatsDataset(Operation operation) {
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 a7680b1cbe9..e6c489833af 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalLMDBDataset";
+  
   private Output handle;
   
   private LmdbDataset(Operation operation) {
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 fcd78e95ee7..e2e29feeba4 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalMatchingFilesDataset";
+  
   private Output handle;
   
   private MatchingFilesDataset(Operation operation) {
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 f7db67ed8a8..fb69729fab0 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalMaxIntraOpParallelismDataset";
+  
   private Output handle;
   
   private MaxIntraOpParallelismDataset(Operation operation) {
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 5d19824576d..9f07f37f804 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalNonSerializableDataset";
+  
   private Output handle;
   
   private NonSerializableDataset(Operation operation) {
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 f87553458b2..4c24cf99558 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
@@ -195,6 +195,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParseExampleDatasetV2";
+  
   private Output handle;
   
   private ParseExampleDataset(Operation operation) {
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 963fb615d65..a52fd41140e 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalPrivateThreadPoolDataset";
+  
   private Output handle;
   
   private PrivateThreadPoolDataset(Operation operation) {
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 aed4a2b7ee4..8f9109ab3d5 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalRandomDataset";
+  
   private Output handle;
   
   private RandomDataset(Operation operation) {
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 cb33dd922e4..6111166128e 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalRebatchDataset";
+  
   private Output handle;
   
   private RebatchDataset(Operation operation) {
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 705753f7835..e2535dcecd7 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalSetStatsAggregatorDataset";
+  
   private Output handle;
   
   private SetStatsAggregatorDataset(Operation operation) {
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 e953bcf3949..97ddeb96999 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalSleepDataset";
+  
   private Output handle;
   
   private SleepDataset(Operation operation) {
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 efe23924930..b8dbded85e9 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
@@ -84,6 +84,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalSlidingWindowDataset";
+  
   private Output handle;
   
   private SlidingWindowDataset(Operation operation) {
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 ca01538ebdb..a68f46a5c08 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalSqlDataset";
+  
   private Output handle;
   
   private SqlDataset(Operation operation) {
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 e3749bfc10b..ec2e57ae4e7 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
@@ -109,6 +109,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatsAggregatorHandleV2";
+  
   private Output handle;
   
   private StatsAggregatorHandle(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java
index 44acd09f14c..ad63ff056d8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java
@@ -47,6 +47,9 @@ public static StatsAggregatorSetSummaryWriter create(Scope scope, Operand sta
     return new StatsAggregatorSetSummaryWriter(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatsAggregatorSetSummaryWriter";
+  
   
   private StatsAggregatorSetSummaryWriter(Operation operation) {
     super(operation);
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 1a4d285dfe3..a24bfdbaada 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
@@ -58,6 +58,9 @@ public Output asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalStatsAggregatorSummary";
+  
   private Output summary;
   
   private StatsAggregatorSummary(Operation operation) {
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 a7daf34b40f..e3fdc2b92cf 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalThreadPoolDataset";
+  
   private Output handle;
   
   private ThreadPoolDataset(Operation operation) {
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 9a2527ec80e..15adc678211 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
@@ -139,6 +139,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalThreadPoolHandle";
+  
   private Output handle;
   
   private ThreadPoolHandle(Operation operation) {
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 7fbcf202d9c..dfa611faa0e 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalUnbatchDataset";
+  
   private Output handle;
   
   private UnbatchDataset(Operation operation) {
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 853152d2760..eb213348e72 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExperimentalUniqueDataset";
+  
   private Output handle;
   
   private UniqueDataset(Operation operation) {
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 1124b625a73..e26417c561d 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CheckNumericsV2";
+  
   private Output output;
   
   private CheckNumerics(Operation operation) {
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 9840b9b1607..4214a50ab41 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DebugGradientIdentity";
+  
   private Output output;
   
   private DebugGradientIdentity(Operation operation) {
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 3746e4891f7..fb4a1d4cfef 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DebugGradientRefIdentity";
+  
   private Output output;
   
   private DebugGradientRefIdentity(Operation operation) {
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 cf3503ffca3..812973efca5 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
@@ -191,6 +191,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DebugIdentityV2";
+  
   private Output output;
   
   private DebugIdentity(Operation operation) {
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 12e011c67ac..30bc6931743 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
@@ -169,6 +169,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DebugNanCount";
+  
   private Output output;
   
   private DebugNanCount(Operation operation) {
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 32e3291a909..85c20b1eef0 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
@@ -241,6 +241,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DebugNumericSummaryV2";
+  
   private Output output;
   
   private DebugNumericsSummary(Operation operation) {
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 6a3cac82067..9d95a0ee6a0 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
@@ -193,6 +193,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AsString";
+  
   private Output output;
   
   private AsString(Operation operation) {
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 5acd9c542f6..49699f07c8c 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
@@ -98,6 +98,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Cast";
+  
   private Output y;
   
   private Cast(Operation operation) {
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 a342009290f..5e8918785a0 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
@@ -82,6 +82,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Complex";
+  
   private Output out;
   
   private Complex(Operation operation) {
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 2130c1279a6..72b3d46d00c 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ToBool";
+  
   private Output output;
   
   private ToBool(Operation operation) {
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 8a89bc639ba..ac772ea4ae0 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return statsSummary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesAggregateStats";
+  
   private Output statsSummary;
   
   private BoostedTreesAggregateStats(Operation operation) {
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 1af298bc2c1..6d57706c19e 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
@@ -71,6 +71,9 @@ public Iterator> iterator() {
     return (Iterator) buckets.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesBucketize";
+  
   private List> buckets;
   
   @SuppressWarnings("unchecked")
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 20de330cd53..41f1d3a6910 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
@@ -154,6 +154,9 @@ public Output splitWithDefaultDirections() {
     return splitWithDefaultDirections;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesCalculateBestFeatureSplit";
+  
   private Output nodeIds;
   private Output gains;
   private Output featureDimensions;
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 69fe748a5cd..903a02fd65b 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
@@ -132,6 +132,9 @@ public Output splitWithDefaultDirections() {
     return splitWithDefaultDirections;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesCalculateBestFeatureSplitV2";
+  
   private Output nodeIds;
   private Output gains;
   private Output featureIds;
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 fdf87628efb..daade3457ae 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
@@ -107,6 +107,9 @@ public List> rightNodeContribsList() {
     return rightNodeContribsList;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesCalculateBestGainsPerFeature";
+  
   private List> nodeIdsList;
   private List> gainsList;
   private List> thresholdsList;
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 e1af20a1f14..7359b6039e2 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return continueCentering;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesCenterBias";
+  
   private Output continueCentering;
   
   private BoostedTreesCenterBias(Operation operation) {
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 c0c9075f784..04613900567 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
@@ -51,6 +51,9 @@ public static BoostedTreesCreateEnsemble create(Scope scope, Operand treeEnse
     return new BoostedTreesCreateEnsemble(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesCreateEnsemble";
+  
   
   private BoostedTreesCreateEnsemble(Operation operation) {
     super(operation);
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 d0ac0b0224d..59362970a58 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
@@ -85,6 +85,9 @@ public static Options maxElements(Long maxElements) {
     return new Options().maxElements(maxElements);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesCreateQuantileStreamResource";
+  
   
   private BoostedTreesCreateQuantileStreamResource(Operation operation) {
     super(operation);
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 8780ca997bd..6fd83d5785d 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
@@ -53,6 +53,9 @@ public static BoostedTreesDeserializeEnsemble create(Scope scope, Operand tre
     return new BoostedTreesDeserializeEnsemble(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesDeserializeEnsemble";
+  
   
   private BoostedTreesDeserializeEnsemble(Operation operation) {
     super(operation);
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 d297ccebdb2..13522dd2fd0 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
@@ -110,6 +110,9 @@ public Output asOutput() {
     return (Output) resource;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesEnsembleResourceHandleOp";
+  
   private Output resource;
   
   private BoostedTreesEnsembleResourceHandleOp(Operation operation) {
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 4902a23c9eb..8618f401ce4 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return examplesDebugOutputsSerialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesExampleDebugOutputs";
+  
   private Output examplesDebugOutputsSerialized;
   
   private BoostedTreesExampleDebugOutputs(Operation operation) {
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 d520766a041..d22acc2ca1b 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
@@ -68,6 +68,9 @@ public Iterator> iterator() {
     return (Iterator) summaries.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesFlushQuantileSummaries";
+  
   private List> summaries;
   
   @SuppressWarnings("unchecked")
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 06ef0f63bfc..36e8eb3c4be 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
@@ -84,6 +84,9 @@ public Output lastLayerNodesRange() {
     return lastLayerNodesRange;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesGetEnsembleStates";
+  
   private Output stampToken;
   private Output numTrees;
   private Output numFinalizedTrees;
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 6bdbd64dd7a..cf4156bb2ce 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
@@ -72,6 +72,9 @@ public Iterator> iterator() {
     return (Iterator) summaries.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesMakeQuantileSummaries";
+  
   private List> summaries;
   
   @SuppressWarnings("unchecked")
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 ed276f08b20..626e05a6f54 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return statsSummary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesMakeStatsSummary";
+  
   private Output statsSummary;
   
   private BoostedTreesMakeStatsSummary(Operation operation) {
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 fc12d1cc2ed..e9c7d4a2be1 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return logits;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesPredict";
+  
   private Output logits;
   
   private BoostedTreesPredict(Operation operation) {
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 08bda03ea19..76480c4be6d 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
@@ -53,6 +53,9 @@ public static BoostedTreesQuantileStreamResourceAddSummaries create(Scope scope,
     return new BoostedTreesQuantileStreamResourceAddSummaries(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesQuantileStreamResourceAddSummaries";
+  
   
   private BoostedTreesQuantileStreamResourceAddSummaries(Operation operation) {
     super(operation);
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 58850d3e981..82066e267d2 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
@@ -51,6 +51,9 @@ public static BoostedTreesQuantileStreamResourceDeserialize create(Scope scope,
     return new BoostedTreesQuantileStreamResourceDeserialize(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesQuantileStreamResourceDeserialize";
+  
   
   private BoostedTreesQuantileStreamResourceDeserialize(Operation operation) {
     super(operation);
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 4f3c4f561b8..359b7b63ff6 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
@@ -94,6 +94,9 @@ public static Options generateQuantiles(Boolean generateQuantiles) {
     return new Options().generateQuantiles(generateQuantiles);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesQuantileStreamResourceFlush";
+  
   
   private BoostedTreesQuantileStreamResourceFlush(Operation operation) {
     super(operation);
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 711e3f6acd6..5d421152254 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
@@ -68,6 +68,9 @@ public Iterator> iterator() {
     return (Iterator) bucketBoundaries.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesQuantileStreamResourceGetBucketBoundaries";
+  
   private List> bucketBoundaries;
   
   @SuppressWarnings("unchecked")
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 72898030449..db925d767f9 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
@@ -110,6 +110,9 @@ public Output asOutput() {
     return (Output) resource;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesQuantileStreamResourceHandleOp";
+  
   private Output resource;
   
   private BoostedTreesQuantileStreamResourceHandleOp(Operation operation) {
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 8bf4df8541e..287c9e9054a 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
@@ -62,6 +62,9 @@ public Output treeEnsembleSerialized() {
     return treeEnsembleSerialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesSerializeEnsemble";
+  
   private Output stampToken;
   private Output treeEnsembleSerialized;
   
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 23ef1f4f01e..3923ac0e905 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
@@ -98,6 +98,9 @@ public Output statsSummaryShape() {
     return statsSummaryShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesSparseAggregateStats";
+  
   private Output statsSummaryIndices;
   private Output statsSummaryValues;
   private Output statsSummaryShape;
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 48afc375b67..b2f2dd1eebf 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
@@ -159,6 +159,9 @@ public Output splitWithDefaultDirections() {
     return splitWithDefaultDirections;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesSparseCalculateBestFeatureSplit";
+  
   private Output nodeIds;
   private Output gains;
   private Output featureDimensions;
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 2dd38c35c59..a81509950b9 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
@@ -87,6 +87,9 @@ public Output nodeIds() {
     return nodeIds;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesTrainingPredict";
+  
   private Output partialLogits;
   private Output treeIds;
   private Output nodeIds;
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 05f2d9c1357..c1b7bb44559 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
@@ -76,6 +76,9 @@ public static BoostedTreesUpdateEnsemble create(Scope scope, Operand treeEnse
     return new BoostedTreesUpdateEnsemble(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesUpdateEnsemble";
+  
   
   private BoostedTreesUpdateEnsemble(Operation operation) {
     super(operation);
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 0e7c81ed3a1..afd9d646c2f 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
@@ -115,6 +115,9 @@ public static Options logitsDimension(Long logitsDimension) {
     return new Options().logitsDimension(logitsDimension);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BoostedTreesUpdateEnsembleV2";
+  
   
   private BoostedTreesUpdateEnsembleV2(Operation operation) {
     super(operation);
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 f7f78393822..7bf185408df 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return isInitialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IsBoostedTreesEnsembleInitialized";
+  
   private Output isInitialized;
   
   private IsBoostedTreesEnsembleInitialized(Operation operation) {
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 6561f2d1eea..66ad4435dfd 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return isInitialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IsBoostedTreesQuantileStreamResourceInitialized";
+  
   private Output isInitialized;
   
   private IsBoostedTreesQuantileStreamResourceInitialized(Operation operation) {
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 acca1abe88b..ab5b3f32e61 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AdjustContrastv2";
+  
   private Output output;
   
   private AdjustContrast(Operation operation) {
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 39d96bec97e..203980f79f8 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AdjustHue";
+  
   private Output output;
   
   private AdjustHue(Operation operation) {
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 3fa15fc4716..393dd196f43 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AdjustSaturation";
+  
   private Output output;
   
   private AdjustSaturation(Operation operation) {
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 1f1926163fc..42bf54e7143 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
@@ -178,6 +178,9 @@ public Output validDetections() {
     return validDetections;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CombinedNonMaxSuppression";
+  
   private Output nmsedBoxes;
   private Output nmsedScores;
   private Output nmsedClasses;
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 19c93f95d4b..f0048c1014b 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return crops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CropAndResize";
+  
   private Output crops;
   
   private CropAndResize(Operation operation) {
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 e29c2a2c159..67263c1e576 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CropAndResizeGradBoxes";
+  
   private Output output;
   
   private CropAndResizeGradBoxes(Operation operation) {
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 30b7f0b7ddf..6a6415f879d 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
@@ -122,6 +122,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CropAndResizeGradImage";
+  
   private Output output;
   
   private CropAndResizeGradImage(Operation operation) {
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 c7191af839a..0c2ac4b1471 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
@@ -232,6 +232,9 @@ public Output asOutput() {
     return image;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeAndCropJpeg";
+  
   private Output image;
   
   private DecodeAndCropJpeg(Operation operation) {
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 23ade8ab9e9..3801822db4e 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
@@ -109,6 +109,9 @@ public Output asOutput() {
     return image;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeBmp";
+  
   private Output image;
   
   private DecodeBmp(Operation operation) {
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 c61b81f21c2..6a06a26ee94 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return image;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeGif";
+  
   private Output image;
   
   private DecodeGif(Operation operation) {
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 4b30ea87bec..d45e802eb9d 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
@@ -229,6 +229,9 @@ public Output asOutput() {
     return image;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeJpeg";
+  
   private Output image;
   
   private DecodeJpeg(Operation operation) {
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 6ff272fc487..eb9ef2a8bee 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
@@ -139,6 +139,9 @@ public Output asOutput() {
     return image;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodePng";
+  
   private Output image;
   
   private DecodePng(Operation operation) {
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 08d460a2985..ba674376d07 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
@@ -82,6 +82,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DrawBoundingBoxesV2";
+  
   private Output output;
   
   private DrawBoundingBoxes(Operation operation) {
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 a08e1d0fbc8..920961e1115 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
@@ -275,6 +275,9 @@ public Output asOutput() {
     return contents;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EncodeJpeg";
+  
   private Output contents;
   
   private EncodeJpeg(Operation operation) {
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 8c9fe1afd49..c07fc341f00 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return contents;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EncodeJpegVariableQuality";
+  
   private Output contents;
   
   private EncodeJpegVariableQuality(Operation operation) {
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 0d01ff0f6f4..cf5b5a0ebc5 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return contents;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EncodePng";
+  
   private Output contents;
   
   private EncodePng(Operation operation) {
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 74ac3be5a05..412daf7387e 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
@@ -199,6 +199,9 @@ public Output asOutput() {
     return glimpse;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExtractGlimpse";
+  
   private Output glimpse;
   
   private ExtractGlimpse(Operation operation) {
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 59b3af03fbb..d02d422a005 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
@@ -92,6 +92,9 @@ public Output asOutput() {
     return patches;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExtractImagePatches";
+  
   private Output patches;
   
   private ExtractImagePatches(Operation operation) {
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 3570c3a6dda..dfa8c4ea7b3 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
@@ -83,6 +83,9 @@ public Output asOutput() {
     return imageShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ExtractJpegShape";
+  
   private Output imageShape;
   
   private ExtractJpegShape(Operation operation) {
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 16d71155a66..1f1563c7d43 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
@@ -123,6 +123,9 @@ public Output roiProbabilities() {
     return roiProbabilities;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GenerateBoundingBoxProposals";
+  
   private Output rois;
   private Output roiProbabilities;
   
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 6a74b96f923..fb752a83518 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "HSVToRGB";
+  
   private Output output;
   
   private HsvToRgb(Operation operation) {
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 478d41f7943..3363d6a9804 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return transformedImages;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ImageProjectiveTransformV2";
+  
   private Output transformedImages;
   
   private ImageProjectiveTransformV2(Operation operation) {
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 55eab58c7fc..f3ad7cb890b 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
@@ -73,6 +73,9 @@ public Output nearestCenterDistances() {
     return nearestCenterDistances;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NearestNeighbors";
+  
   private Output nearestCenterIndices;
   private Output nearestCenterDistances;
   
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 ee83c1d3f06..0745299e34f 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
@@ -153,6 +153,9 @@ public Output validOutputs() {
     return validOutputs;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NonMaxSuppressionV5";
+  
   private Output selectedIndices;
   private Output selectedScores;
   private Output validOutputs;
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 97e14206922..073aee26ff9 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return selectedIndices;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NonMaxSuppressionWithOverlaps";
+  
   private Output selectedIndices;
   
   private NonMaxSuppressionWithOverlaps(Operation operation) {
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 9903ce2c265..7eb6d8a3a92 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
@@ -136,6 +136,9 @@ public Output outMax() {
     return outMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedResizeBilinear";
+  
   private Output resizedImages;
   private Output outMin;
   private Output outMax;
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 855a60036d9..47d03d63187 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
@@ -130,6 +130,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomCrop";
+  
   private Output output;
   
   private RandomCrop(Operation operation) {
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 dd7d7335570..60d1e473ef0 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
@@ -115,6 +115,9 @@ public Output asOutput() {
     return resizedImages;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResizeArea";
+  
   private Output resizedImages;
   
   private ResizeArea(Operation operation) {
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 23fa5034437..2519eaa6ea9 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
@@ -124,6 +124,9 @@ public Output asOutput() {
     return resizedImages;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResizeBicubic";
+  
   private Output resizedImages;
   
   private ResizeBicubic(Operation operation) {
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 d7cc678f8a4..96296cdf33f 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResizeBicubicGrad";
+  
   private Output output;
   
   private ResizeBicubicGrad(Operation operation) {
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 fb01887d6f5..d0c28fed013 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
@@ -124,6 +124,9 @@ public Output asOutput() {
     return resizedImages;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResizeBilinear";
+  
   private Output resizedImages;
   
   private ResizeBilinear(Operation operation) {
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 85fb0ff85e6..b8aef51ba30 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResizeBilinearGrad";
+  
   private Output output;
   
   private ResizeBilinearGrad(Operation operation) {
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 9183dd63544..dd7865841de 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
@@ -123,6 +123,9 @@ public Output asOutput() {
     return resizedImages;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResizeNearestNeighbor";
+  
   private Output resizedImages;
   
   private ResizeNearestNeighbor(Operation operation) {
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 c8fb4f704f8..4897c0f9dc6 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
@@ -122,6 +122,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResizeNearestNeighborGrad";
+  
   private Output output;
   
   private ResizeNearestNeighborGrad(Operation operation) {
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 a0fdcc30ff8..acee7a6061e 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
@@ -83,6 +83,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RGBToHSV";
+  
   private Output output;
   
   private RgbToHsv(Operation operation) {
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 8281880a8b0..7f83b2ee84c 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
@@ -275,6 +275,9 @@ public Output bboxes() {
     return bboxes;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SampleDistortedBoundingBoxV2";
+  
   private Output begin;
   private Output size;
   private Output bboxes;
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 bd4cc964f2f..26bf544be2e 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
@@ -120,6 +120,9 @@ public Output asOutput() {
     return resizedImages;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScaleAndTranslate";
+  
   private Output resizedImages;
   
   private ScaleAndTranslate(Operation operation) {
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 8ab90449e1f..4b8d9b0fc4b 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
@@ -119,6 +119,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScaleAndTranslateGrad";
+  
   private Output output;
   
   private ScaleAndTranslateGrad(Operation operation) {
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 7abe6aaa1f1..db026fd820c 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeBase64";
+  
   private Output output;
   
   private DecodeBase64(Operation operation) {
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 01a55de64ca..745dba6d063 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeCompressed";
+  
   private Output output;
   
   private DecodeCompressed(Operation operation) {
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 4825645c0eb..6b417cb8717 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
@@ -174,6 +174,9 @@ public Iterator> iterator() {
     return (Iterator) output.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeCSV";
+  
   private List> output;
   
   private DecodeCsv(Operation operation) {
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 0f5b155c267..f3da58ca98d 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return binaryExamples;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeJSONExample";
+  
   private Output binaryExamples;
   
   private DecodeJsonExample(Operation operation) {
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 137f69f7015..820b0077ba5 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
@@ -109,6 +109,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodePaddedRaw";
+  
   private Output output;
   
   private DecodePaddedRaw(Operation operation) {
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 d42e9e79d6c..dfdabfdb466 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
@@ -106,6 +106,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DecodeRaw";
+  
   private Output output;
   
   private DecodeRaw(Operation operation) {
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 1d80fd486df..8582681c073 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
@@ -116,6 +116,9 @@ public Output sparseShape() {
     return sparseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeserializeManySparse";
+  
   private Output sparseIndices;
   private Output sparseValues;
   private Output sparseShape;
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 9dbfbb079b2..ddb331b4a48 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
@@ -101,6 +101,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EncodeBase64";
+  
   private Output output;
   
   private EncodeBase64(Operation operation) {
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 95c5bfcd712..842985b49e9 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
@@ -175,6 +175,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FIFOQueueV2";
+  
   private Output handle;
   
   private FifoQueue(Operation operation) {
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 a091f665ba4..3678b8190b9 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
@@ -198,6 +198,9 @@ public Output asOutput() {
     return (Output) readerHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FixedLengthRecordReaderV2";
+  
   private Output readerHandle;
   
   private FixedLengthRecordReader(Operation operation) {
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 af9a6ca34e7..99ae027a82e 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
@@ -119,6 +119,9 @@ public Output asOutput() {
     return (Output) readerHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IdentityReaderV2";
+  
   private Output readerHandle;
   
   private IdentityReader(Operation operation) {
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 aa8c476a0c1..b3b10b2809c 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
@@ -115,6 +115,9 @@ public Output asOutput() {
     return readerHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LMDBReader";
+  
   private Output readerHandle;
   
   private LmdbReader(Operation operation) {
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 5c9d5bcd681..ed2b33adea3 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return filenames;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatchingFiles";
+  
   private Output filenames;
   
   private MatchingFiles(Operation operation) {
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 516ac396ad7..b72d8188038 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
@@ -187,6 +187,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PaddingFIFOQueueV2";
+  
   private Output handle;
   
   private PaddingFifoQueue(Operation operation) {
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 1c0b73c5cca..bd8f0f4a603 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
@@ -166,6 +166,9 @@ public List> raggedRowSplits() {
     return raggedRowSplits;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParseExampleV2";
+  
   private List> sparseIndices;
   private List> sparseValues;
   private List> sparseShapes;
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 d7d83defcca..8720b3d160e 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
@@ -358,6 +358,9 @@ public List> featureListRaggedInnerSplits() {
     return featureListRaggedInnerSplits;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParseSequenceExampleV2";
+  
   private List> contextSparseIndices;
   private List> contextSparseValues;
   private List> contextSparseShapes;
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 95e8f11018b..2c09ba8ac4c 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
@@ -129,6 +129,9 @@ public List> denseValues() {
     return denseValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParseSingleExample";
+  
   private List> sparseIndices;
   private List> sparseValues;
   private List> sparseShapes;
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 4457e099ea8..bb1e1eaa576 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
@@ -239,6 +239,9 @@ public List> featureListDenseValues() {
     return featureListDenseValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParseSingleSequenceExample";
+  
   private List> contextSparseIndices;
   private List> contextSparseValues;
   private List> contextSparseShapes;
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 bf2a8e62c2d..bebdc1b4419 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParseTensor";
+  
   private Output output;
   
   private ParseTensor(Operation operation) {
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 587994bba0f..569d4ae7eb3 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
@@ -161,6 +161,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PriorityQueueV2";
+  
   private Output handle;
   
   private PriorityQueue(Operation operation) {
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 d2bbb349ec0..fb55f708140 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
@@ -88,6 +88,9 @@ public static Options cancelPendingEnqueues(Boolean cancelPendingEnqueues) {
     return new Options().cancelPendingEnqueues(cancelPendingEnqueues);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueCloseV2";
+  
   
   private QueueClose(Operation operation) {
     super(operation);
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 d5c2f67db77..b74fb3ad3e8 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
@@ -116,6 +116,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueDequeueV2";
+  
   private List> components;
   
   private QueueDequeue(Operation operation) {
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 f705e660c1b..2906fe6543c 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
@@ -126,6 +126,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueDequeueManyV2";
+  
   private List> components;
   
   private QueueDequeueMany(Operation operation) {
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 cd1406318ef..51af788104c 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
@@ -130,6 +130,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueDequeueUpToV2";
+  
   private List> components;
   
   private QueueDequeueUpTo(Operation operation) {
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 8bbe35eeada..546981e8abf 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
@@ -93,6 +93,9 @@ public static Options timeoutMs(Long timeoutMs) {
     return new Options().timeoutMs(timeoutMs);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueEnqueueV2";
+  
   
   private QueueEnqueue(Operation operation) {
     super(operation);
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 8f973f62260..48df5d3b9d3 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
@@ -98,6 +98,9 @@ public static Options timeoutMs(Long timeoutMs) {
     return new Options().timeoutMs(timeoutMs);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueEnqueueManyV2";
+  
   
   private QueueEnqueueMany(Operation operation) {
     super(operation);
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 0326250f5a5..895965a3c6c 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return isClosed;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueIsClosedV2";
+  
   private Output isClosed;
   
   private QueueIsClosed(Operation operation) {
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 cf904be8436..cefc1b3fd11 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return size;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QueueSizeV2";
+  
   private Output size;
   
   private QueueSize(Operation operation) {
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 ced52fc58cd..cdde1debc95 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
@@ -238,6 +238,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomShuffleQueueV2";
+  
   private Output handle;
   
   private RandomShuffleQueue(Operation operation) {
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 9ba806c69ae..7109022751a 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return contents;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReadFile";
+  
   private Output contents;
   
   private ReadFile(Operation operation) {
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 51ec23956fb..8e4cb9c5692 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return recordsProduced;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReaderNumRecordsProducedV2";
+  
   private Output recordsProduced;
   
   private ReaderNumRecordsProduced(Operation operation) {
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 848f1602cb3..bbd6fc8075c 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return unitsCompleted;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReaderNumWorkUnitsCompletedV2";
+  
   private Output unitsCompleted;
   
   private ReaderNumWorkUnitsCompleted(Operation operation) {
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 33e1e7135e5..9b7110b10ae 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
@@ -68,6 +68,9 @@ public Output value() {
     return value;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReaderReadV2";
+  
   private Output key;
   private Output value;
   
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 897ca83dc9f..e22d5b95576 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
@@ -72,6 +72,9 @@ public Output values() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReaderReadUpToV2";
+  
   private Output keys;
   private Output values;
   
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 f99a25a836a..6e3de01134b 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
@@ -46,6 +46,9 @@ public static ReaderReset create(Scope scope, Operand readerHandle) {
     return new ReaderReset(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReaderResetV2";
+  
   
   private ReaderReset(Operation operation) {
     super(operation);
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 359c4d63284..b0abea1257c 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
@@ -53,6 +53,9 @@ public static ReaderRestoreState create(Scope scope, Operand readerHandle, Op
     return new ReaderRestoreState(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReaderRestoreStateV2";
+  
   
   private ReaderRestoreState(Operation operation) {
     super(operation);
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 d10ce99d2a8..72b927ed171 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return state;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReaderSerializeStateV2";
+  
   private Output state;
   
   private ReaderSerializeState(Operation operation) {
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 5cb65e873cc..0afbdcd6edd 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
@@ -93,6 +93,9 @@ public Output asOutput() {
     return serializedSparse;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SerializeManySparse";
+  
   private Output serializedSparse;
   
   private SerializeManySparse(Operation operation) {
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 d97317b00d4..2d8fc7838e4 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
@@ -85,6 +85,9 @@ public Output asOutput() {
     return serializedSparse;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SerializeSparse";
+  
   private Output serializedSparse;
   
   private SerializeSparse(Operation operation) {
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 07935a57d3f..d68320b85e3 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return serialized;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SerializeTensor";
+  
   private Output serialized;
   
   private SerializeTensor(Operation operation) {
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 3febe213066..88b422a5f6d 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return filename;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ShardedFilename";
+  
   private Output filename;
   
   private ShardedFilename(Operation operation) {
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 4c414afa0a4..f04c0cf1a58 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return filename;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ShardedFilespec";
+  
   private Output filename;
   
   private ShardedFilespec(Operation operation) {
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 963710a3708..90bf079d2cf 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
@@ -135,6 +135,9 @@ public Output asOutput() {
     return (Output) readerHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TextLineReaderV2";
+  
   private Output readerHandle;
   
   private TextLineReader(Operation operation) {
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 98d58836334..a12145e7972 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
@@ -135,6 +135,9 @@ public Output asOutput() {
     return (Output) readerHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TFRecordReaderV2";
+  
   private Output readerHandle;
   
   private TfRecordReader(Operation operation) {
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 444b36aec72..8cab4f9b09e 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
@@ -119,6 +119,9 @@ public Output asOutput() {
     return (Output) readerHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WholeFileReaderV2";
+  
   private Output readerHandle;
   
   private WholeFileReader(Operation operation) {
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 2d8f1ed4a1b..d9fba243fc3 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
@@ -51,6 +51,9 @@ public static WriteFile create(Scope scope, Operand filename, Operand asOutput() {
     return band;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixBandPart";
+  
   private Output band;
   
   private BandPart(Operation operation) {
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 988d5a23c7f..733139f4359 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchCholesky";
+  
   private Output output;
   
   private BatchCholesky(Operation operation) {
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 71b533674a8..d56f45e8abf 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchCholeskyGrad";
+  
   private Output output;
   
   private BatchCholeskyGrad(Operation operation) {
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 7b0a946e593..8c990a8a71c 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return band;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixBandPart";
+  
   private Output band;
   
   private BatchMatrixBandPart(Operation operation) {
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 c56dcebd836..f513e9f0057 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixDeterminant";
+  
   private Output output;
   
   private BatchMatrixDeterminant(Operation operation) {
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 3cb73f6e451..b3f9071f9f6 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixDiag";
+  
   private Output output;
   
   private BatchMatrixDiag(Operation operation) {
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 99207f83e9c..47f78ed623d 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return diagonal;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixDiagPart";
+  
   private Output diagonal;
   
   private BatchMatrixDiagPart(Operation operation) {
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 bf8ca469f95..36bbee414e9 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
@@ -94,6 +94,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixInverse";
+  
   private Output output;
   
   private BatchMatrixInverse(Operation operation) {
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 7f8508edbb0..d83ee0194e7 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixSetDiag";
+  
   private Output output;
   
   private BatchMatrixSetDiag(Operation operation) {
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 a4b086faa3f..677b8aa0e7b 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
@@ -96,6 +96,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixSolve";
+  
   private Output output;
   
   private BatchMatrixSolve(Operation operation) {
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 c5a71d9481d..ae4a4366b3b 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixSolveLs";
+  
   private Output output;
   
   private BatchMatrixSolveLs(Operation operation) {
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 186d68a8f68..cb1baa772fd 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
@@ -115,6 +115,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatrixTriangularSolve";
+  
   private Output output;
   
   private BatchMatrixTriangularSolve(Operation operation) {
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 d2c56803f3a..e589f5c49fe 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
@@ -95,6 +95,9 @@ public Output v() {
     return v;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchSelfAdjointEigV2";
+  
   private Output e;
   private Output v;
   
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 25b8da69ab5..21db016713a 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
@@ -119,6 +119,9 @@ public Output v() {
     return v;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchSvd";
+  
   private Output s;
   private Output u;
   private Output v;
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 64216a5a5d3..3acf951d5a7 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Cholesky";
+  
   private Output output;
   
   private Cholesky(Operation operation) {
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 e60c7eee5fd..b4171907853 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CholeskyGrad";
+  
   private Output output;
   
   private CholeskyGrad(Operation operation) {
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 a1d82fd5d07..2da45552f35 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ConjugateTranspose";
+  
   private Output y;
   
   private ConjugateTranspose(Operation operation) {
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 1de44ceb714..0afc8a2bf60 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return product;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Cross";
+  
   private Output product;
   
   private Cross(Operation operation) {
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 4ae18c47148..7134ef6ea44 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixDeterminant";
+  
   private Output output;
   
   private Det(Operation operation) {
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 faaf6dd5972..68c33487129 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
@@ -115,6 +115,9 @@ public Output v() {
     return v;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Eig";
+  
   private Output e;
   private Output v;
   
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 7471e13882c..6817270edd1 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
@@ -142,6 +142,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Einsum";
+  
   private Output output;
   
   private Einsum(Operation operation) {
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 eeb65943fa3..f8ce40f62bf 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EuclideanNorm";
+  
   private Output output;
   
   private EuclideanNorm(Operation operation) {
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 46fbed05b63..e482957bdac 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
@@ -112,6 +112,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixInverse";
+  
   private Output output;
   
   private Inv(Operation operation) {
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 58482665ed7..1010c503eba 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
@@ -162,6 +162,9 @@ public Output asOutput() {
     return outputMatrix;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadAndRemapMatrix";
+  
   private Output outputMatrix;
   
   private LoadAndRemapMatrix(Operation operation) {
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 a19e1753007..33781d561b4 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
@@ -75,6 +75,9 @@ public Output logAbsDeterminant() {
     return logAbsDeterminant;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LogMatrixDeterminant";
+  
   private Output sign;
   private Output logAbsDeterminant;
   
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 f243cc902c9..ce37bbcbea2 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
@@ -111,6 +111,9 @@ public Output p() {
     return p;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Lu";
+  
   private Output lu;
   private Output p;
   
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 72466aaceea..8b227e3910c 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
@@ -124,6 +124,9 @@ public Output asOutput() {
     return product;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatMul";
+  
   private Output product;
   
   private MatMul(Operation operation) {
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 97e885f95e8..b187ecc0930 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
@@ -164,6 +164,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixDiagV2";
+  
   private Output output;
   
   private MatrixDiag(Operation operation) {
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 81a80bb0d5c..c4dee3f7d76 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
@@ -138,6 +138,9 @@ public Output asOutput() {
     return diagonal;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixDiagPartV2";
+  
   private Output diagonal;
   
   private MatrixDiagPart(Operation operation) {
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 d4c9adcf553..5803f9251f5 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
@@ -215,6 +215,9 @@ public Output asOutput() {
     return diagonal;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixDiagPartV3";
+  
   private Output diagonal;
   
   private MatrixDiagPartV3(Operation operation) {
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 ef16e3195da..10b57ecc19a 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
@@ -239,6 +239,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixDiagV3";
+  
   private Output output;
   
   private MatrixDiagV3(Operation operation) {
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 ba6adbaf0aa..71d3a2c9575 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
@@ -81,6 +81,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixLogarithm";
+  
   private Output output;
   
   private MatrixLogarithm(Operation operation) {
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 fe7c7b42d35..80367a3670b 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
@@ -219,6 +219,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixSetDiagV3";
+  
   private Output output;
   
   private MatrixSetDiag(Operation operation) {
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 3ed8ddf95d3..633145ce24e 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
@@ -140,6 +140,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixSolveLs";
+  
   private Output output;
   
   private MatrixSolveLs(Operation operation) {
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 e35661a5ae4..cf58f41507f 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
@@ -115,6 +115,9 @@ public Output r() {
     return r;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Qr";
+  
   private Output q;
   private Output r;
   
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 749ba329ea1..445d27e1591 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
@@ -145,6 +145,9 @@ public Output maxOut() {
     return maxOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMatMul";
+  
   private Output out;
   private Output minOut;
   private Output maxOut;
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 48ac255e7a5..30800fc499a 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
@@ -165,6 +165,9 @@ public Output maxOut() {
     return maxOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMatMulWithBias";
+  
   private Output out;
   private Output minOut;
   private Output maxOut;
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 6958b14a7f3..6e584b6b82f 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
@@ -166,6 +166,9 @@ public Output maxOut() {
     return maxOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMatMulWithBiasAndRelu";
+  
   private Output out;
   private Output minOut;
   private Output maxOut;
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 17d2b2a25d0..c6b38ac66af 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
@@ -171,6 +171,9 @@ public Output maxOut() {
     return maxOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMatMulWithBiasAndReluAndRequantize";
+  
   private Output out;
   private Output minOut;
   private Output maxOut;
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 d0d3e8f4f5f..60bbafe6e70 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
@@ -112,6 +112,9 @@ public Output v() {
     return v;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SelfAdjointEigV2";
+  
   private Output e;
   private Output v;
   
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 087b8ef7991..62f1beb11c8 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
@@ -107,6 +107,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixSolve";
+  
   private Output output;
   
   private Solve(Operation operation) {
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 86d747a81a5..35c3b88605c 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
@@ -82,6 +82,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixSquareRoot";
+  
   private Output output;
   
   private Sqrtm(Operation operation) {
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 df0772367fd..4ff72f0e139 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
@@ -149,6 +149,9 @@ public Output v() {
     return v;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Svd";
+  
   private Output s;
   private Output u;
   private Output v;
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 40bf987f815..126a8c5cde7 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Diag";
+  
   private Output output;
   
   private TensorDiag(Operation operation) {
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 c14b82af064..e999ca96a4b 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
@@ -81,6 +81,9 @@ public Output asOutput() {
     return diagonal;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DiagPart";
+  
   private Output diagonal;
   
   private TensorDiagPart(Operation operation) {
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 5ce582563ea..1df98fabe64 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Transpose";
+  
   private Output y;
   
   private Transpose(Operation operation) {
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 ba5ce4f65c2..da86d99b6c6 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
@@ -176,6 +176,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MatrixTriangularSolve";
+  
   private Output output;
   
   private TriangularSolve(Operation operation) {
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 7fb782724f9..2ff1c18fc60 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TridiagonalMatMul";
+  
   private Output output;
   
   private TridiagonalMatMul(Operation operation) {
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 0ad614e24d2..0f581811162 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
@@ -110,6 +110,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TridiagonalSolve";
+  
   private Output output;
   
   private TridiagonalSolve(Operation operation) {
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 01e7c156baf..332382cec08 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
@@ -79,6 +79,9 @@ public Output values() {
     return values;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CSRSparseMatrixComponents";
+  
   private Output rowPtrs;
   private Output colInds;
   private Output values;
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 f221c56fce1..0d8ceba40d3 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return denseOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CSRSparseMatrixToDense";
+  
   private Output denseOutput;
   
   private CSRSparseMatrixToDense(Operation operation) {
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 c9796bf7573..0b5a2d41df8 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
@@ -74,6 +74,9 @@ public Output denseShape() {
     return denseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CSRSparseMatrixToSparseTensor";
+  
   private Output indices;
   private Output values;
   private Output denseShape;
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 93414b7e7f6..0033c9a9760 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return (Output) sparseOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DenseToCSRSparseMatrix";
+  
   private Output sparseOutput;
   
   private DenseToCSRSparseMatrix(Operation operation) {
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 2e7b03b0fb6..d8e676743a1 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return (Output) c;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixAdd";
+  
   private Output c;
   
   private SparseMatrixAdd(Operation operation) {
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 999afbb7a1a..2ee48d29d79 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
@@ -217,6 +217,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixMatMul";
+  
   private Output output;
   
   private SparseMatrixMatMul(Operation operation) {
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 cc6f936e661..ad1571580f5 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixMul";
+  
   private Output output;
   
   private SparseMatrixMul(Operation operation) {
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 613228d6272..e730d181699 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return nnz;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixNNZ";
+  
   private Output nnz;
   
   private SparseMatrixNNZ(Operation operation) {
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 9acf649aa94..6967ebec973 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
@@ -107,6 +107,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixOrderingAMD";
+  
   private Output output;
   
   private SparseMatrixOrderingAMD(Operation operation) {
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 2d62bbb6899..01cec0f84da 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return (Output) softmax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixSoftmax";
+  
   private Output softmax;
   
   private SparseMatrixSoftmax(Operation operation) {
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 0a698bb7929..8ac96d72177 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return (Output) gradient;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixSoftmaxGrad";
+  
   private Output gradient;
   
   private SparseMatrixSoftmaxGrad(Operation operation) {
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 603e4e30c9f..3f52d64f600 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
@@ -137,6 +137,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixSparseCholesky";
+  
   private Output output;
   
   private SparseMatrixSparseCholesky(Operation operation) {
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 2e8bafb9b0b..8e7c545df87 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
@@ -229,6 +229,9 @@ public Output asOutput() {
     return (Output) c;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixSparseMatMul";
+  
   private Output c;
   
   private SparseMatrixSparseMatMul(Operation operation) {
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 6801b45dd6d..90e5ba4294f 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
@@ -100,6 +100,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixTranspose";
+  
   private Output output;
   
   private SparseMatrixTranspose(Operation operation) {
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 eab0d59e8c2..3c5bef9daed 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return (Output) sparseMatrix;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatrixZeros";
+  
   private Output sparseMatrix;
   
   private SparseMatrixZeros(Operation operation) {
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 a14a09c9433..afda1e8b5f1 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return (Output) sparseMatrix;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseTensorToCSRSparseMatrix";
+  
   private Output sparseMatrix;
   
   private SparseTensorToCSRSparseMatrix(Operation operation) {
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 a04d249dc74..7aa760a535b 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Abs";
+  
   private Output y;
   
   private Abs(Operation operation) {
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 733a7546f57..dc15d9f9d81 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return sum;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AccumulateNV2";
+  
   private Output sum;
   
   private AccumulateN(Operation operation) {
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 200fa10daad..43ba8e54334 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Acos";
+  
   private Output y;
   
   private Acos(Operation operation) {
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 e26f402b14e..0d1aaf95237 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Acosh";
+  
   private Output y;
   
   private Acosh(Operation operation) {
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 2c3c69e735f..86d7c82ae38 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Add";
+  
   private Output z;
   
   private Add(Operation operation) {
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 aa6abe36421..16a5e22ce16 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return sum;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AddN";
+  
   private Output sum;
   
   private AddN(Operation operation) {
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 08c203e2625..ce996785568 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
@@ -94,6 +94,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Angle";
+  
   private Output output;
   
   private Angle(Operation operation) {
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 83762aa8117..245c42f269d 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
@@ -96,6 +96,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApproximateEqual";
+  
   private Output z;
   
   private ApproximateEqual(Operation operation) {
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 9670f62b1a5..b45c1268cb2 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
@@ -98,6 +98,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ArgMax";
+  
   private Output output;
   
   private ArgMax(Operation operation) {
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 00e84ed2dc3..5a49adecd22 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
@@ -98,6 +98,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ArgMin";
+  
   private Output output;
   
   private ArgMin(Operation operation) {
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 6dd53582f63..941515b013e 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Asin";
+  
   private Output y;
   
   private Asin(Operation operation) {
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 93131b0b597..c2451727573 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Asinh";
+  
   private Output y;
   
   private Asinh(Operation operation) {
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 ae1c0de475b..a3574d549bc 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Atan";
+  
   private Output y;
   
   private Atan(Operation operation) {
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 d77090da6a1..d49bc324cb3 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Atan2";
+  
   private Output z;
   
   private Atan2(Operation operation) {
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 2d8596be938..6c53c8828c0 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Atanh";
+  
   private Output y;
   
   private Atanh(Operation operation) {
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 b951b555fc9..c68eeadc30c 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselI0e";
+  
   private Output y;
   
   private BesselI0e(Operation operation) {
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 9d92b8a4d66..f61e846e2b6 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselI1e";
+  
   private Output y;
   
   private BesselI1e(Operation operation) {
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 bf42fa10faf..53ecd2ed396 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Betainc";
+  
   private Output z;
   
   private Betainc(Operation operation) {
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 30b96bf1b5d..4217584c4fb 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return bins;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Bincount";
+  
   private Output bins;
   
   private Bincount(Operation operation) {
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 36bcf7ce417..c97e5b5ae5d 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Ceil";
+  
   private Output y;
   
   private Ceil(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CompareAndBitpack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CompareAndBitpack.java
index a00341d467d..2538cc59248 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CompareAndBitpack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CompareAndBitpack.java
@@ -85,6 +85,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CompareAndBitpack";
+  
   private Output output;
   
   private CompareAndBitpack(Operation operation) {
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 f72854aa5ed..317744e519a 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
@@ -83,6 +83,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ComplexAbs";
+  
   private Output y;
   
   private ComplexAbs(Operation operation) {
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 c633957aeb2..b565fe9d322 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
@@ -75,6 +75,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Conj";
+  
   private Output output;
   
   private Conj(Operation operation) {
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 8a61ed1db2a..29f81972b17 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Cos";
+  
   private Output y;
   
   private Cos(Operation operation) {
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 20f70fe2f0c..f65e3e952ea 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Cosh";
+  
   private Output y;
   
   private Cosh(Operation operation) {
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 faab91b5bd9..52154403d72 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
@@ -143,6 +143,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Cumprod";
+  
   private Output out;
   
   private Cumprod(Operation operation) {
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 a1027a8b221..6895cbed39f 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
@@ -143,6 +143,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Cumsum";
+  
   private Output out;
   
   private Cumsum(Operation operation) {
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 82b702e4def..3c8e6f89870 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
@@ -135,6 +135,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CumulativeLogsumexp";
+  
   private Output out;
   
   private CumulativeLogsumexp(Operation operation) {
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 c217acd7f51..2fd494f637c 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Digamma";
+  
   private Output y;
   
   private Digamma(Operation operation) {
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 fb34257a1e8..0cd80db04df 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Div";
+  
   private Output z;
   
   private Div(Operation operation) {
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 373dcff32cb..7a1ea66a50d 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DivNoNan";
+  
   private Output z;
   
   private DivNoNan(Operation operation) {
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 971a44984c6..d67b38e9ca6 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
@@ -109,6 +109,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Equal";
+  
   private Output z;
   
   private Equal(Operation operation) {
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 2f8e2f8c302..9f86126bff4 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Erf";
+  
   private Output y;
   
   private Erf(Operation operation) {
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 a1494ae42a7..b94fecf9ede 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Erfc";
+  
   private Output y;
   
   private Erfc(Operation operation) {
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 16e93c8ec2c..cee48319f26 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Exp";
+  
   private Output y;
   
   private Exp(Operation operation) {
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 6998e3d3fdb..9d76f16b774 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Expm1";
+  
   private Output y;
   
   private Expm1(Operation operation) {
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 7c8f8af6c95..31d78966166 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
@@ -57,6 +57,9 @@ public Output asOutput() {
     return fact;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Fact";
+  
   private Output fact;
   
   private Fact(Operation operation) {
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 fb1955c2e91..ac8d7a8ffba 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Floor";
+  
   private Output y;
   
   private Floor(Operation operation) {
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 b02797cde81..366b88bc6d9 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FloorDiv";
+  
   private Output z;
   
   private FloorDiv(Operation operation) {
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 79881c593bc..715628b57a3 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FloorMod";
+  
   private Output z;
   
   private FloorMod(Operation operation) {
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 a2aef106674..e8ef3811fd1 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Greater";
+  
   private Output z;
   
   private Greater(Operation operation) {
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 6097961d214..11a83743031 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GreaterEqual";
+  
   private Output z;
   
   private GreaterEqual(Operation operation) {
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 e6492c17a8e..a4687ef3ab1 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Igamma";
+  
   private Output z;
   
   private Igamma(Operation operation) {
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 90e5b649dc5..e57b8d886e1 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IgammaGradA";
+  
   private Output z;
   
   private IgammaGradA(Operation operation) {
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 03c9ab28002..1e2cb0cf0f7 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Igammac";
+  
   private Output z;
   
   private Igammac(Operation operation) {
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 dbd5b5b8406..48a8a7107a3 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Imag";
+  
   private Output output;
   
   private Imag(Operation operation) {
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 28d0a80d4ad..de9e9c46932 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InvertPermutation";
+  
   private Output y;
   
   private InvertPermutation(Operation operation) {
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 b8136095909..ffe9bb99f10 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IsFinite";
+  
   private Output y;
   
   private IsFinite(Operation operation) {
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 429e8aee411..3d36e9fbfe9 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IsInf";
+  
   private Output y;
   
   private IsInf(Operation operation) {
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 1c480c08336..b58205a005c 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IsNan";
+  
   private Output y;
   
   private IsNan(Operation operation) {
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 106040ab8b1..3d796296f01 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Less";
+  
   private Output z;
   
   private Less(Operation operation) {
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 094bd19e36c..618cd7a9866 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LessEqual";
+  
   private Output z;
   
   private LessEqual(Operation operation) {
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 42a5baad397..9bc18b1b3b8 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Lgamma";
+  
   private Output y;
   
   private Lgamma(Operation operation) {
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 1ee4bc3c6e2..9db418d1002 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Log";
+  
   private Output y;
   
   private Log(Operation operation) {
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 407cfa649ad..3cc2656ea9b 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Log1p";
+  
   private Output y;
   
   private Log1p(Operation operation) {
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 410cd28dc9d..89bb2837f46 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LogicalAnd";
+  
   private Output z;
   
   private LogicalAnd(Operation operation) {
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 643af8caa45..f59c85fd320 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LogicalNot";
+  
   private Output y;
   
   private LogicalNot(Operation operation) {
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 a9f33397ae1..604e3ea18f5 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LogicalOr";
+  
   private Output z;
   
   private LogicalOr(Operation operation) {
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 998e5fbc3bf..9f72150c5d3 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Maximum";
+  
   private Output z;
   
   private Maximum(Operation operation) {
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 301ff6b1c31..7859b7ce10f 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Mean";
+  
   private Output output;
   
   private Mean(Operation operation) {
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 33f6fe5d7af..e11b6e484fc 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Minimum";
+  
   private Output z;
   
   private Minimum(Operation operation) {
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 8cd9b2cd30d..7ba98b81b39 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Mod";
+  
   private Output z;
   
   private Mod(Operation operation) {
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 d4cf53f8540..20d5f471ba8 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Mul";
+  
   private Output z;
   
   private Mul(Operation operation) {
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 157b5d1ead0..312a3025870 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MulNoNan";
+  
   private Output z;
   
   private MulNoNan(Operation operation) {
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 0330942d8b3..55dcf0c434d 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Ndtri";
+  
   private Output y;
   
   private Ndtri(Operation operation) {
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 14a1544cb82..53079692e32 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Neg";
+  
   private Output y;
   
   private Neg(Operation operation) {
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 4ac1cde3380..8fa53306eed 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NextAfter";
+  
   private Output output;
   
   private NextAfter(Operation operation) {
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 647b596f6be..977688031c5 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NotEqual";
+  
   private Output z;
   
   private NotEqual(Operation operation) {
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 415b5b51837..d0021efc2ac 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Polygamma";
+  
   private Output z;
   
   private Polygamma(Operation operation) {
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 21b22d86fa5..bc721897426 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PopulationCount";
+  
   private Output y;
   
   private PopulationCount(Operation operation) {
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 cd22d351e6e..27f26e431fe 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Pow";
+  
   private Output z;
   
   private Pow(Operation operation) {
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 fd2f5890d47..ccd6d2e5f98 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
@@ -87,6 +87,9 @@ public Output maxZ() {
     return maxZ;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedAdd";
+  
   private Output z;
   private Output minZ;
   private Output maxZ;
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 a629145fa62..e16dc423a63 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
@@ -87,6 +87,9 @@ public Output maxZ() {
     return maxZ;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMul";
+  
   private Output z;
   private Output minZ;
   private Output maxZ;
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 0b619946e0b..e113597afd8 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Real";
+  
   private Output output;
   
   private Real(Operation operation) {
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 32dcc8988fc..ec322c696db 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RealDiv";
+  
   private Output z;
   
   private RealDiv(Operation operation) {
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 b39118351c5..a0b53da3b7c 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Reciprocal";
+  
   private Output y;
   
   private Reciprocal(Operation operation) {
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 9d9a1f03723..dee41220ba9 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReciprocalGrad";
+  
   private Output z;
   
   private ReciprocalGrad(Operation operation) {
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 659dae182cf..feda79c70b2 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
@@ -69,6 +69,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RequantizationRangePerChannel";
+  
   private Output outputMin;
   private Output outputMax;
   
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 793429b9779..53a6201151e 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
@@ -82,6 +82,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RequantizePerChannel";
+  
   private Output output;
   private Output outputMin;
   private Output outputMax;
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 576508d7d30..b7b152248a8 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Rint";
+  
   private Output y;
   
   private Rint(Operation operation) {
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 dbd546baf23..7f892d28ed0 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Round";
+  
   private Output y;
   
   private Round(Operation operation) {
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 43a6886684d..de04c3f1204 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Rsqrt";
+  
   private Output y;
   
   private Rsqrt(Operation operation) {
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 df8cdcfb392..ee0eec068f3 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RsqrtGrad";
+  
   private Output z;
   
   private RsqrtGrad(Operation operation) {
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 99c1bda676b..fdd40054420 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SegmentMax";
+  
   private Output output;
   
   private SegmentMax(Operation operation) {
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 263a550e74c..2fe16ce7e12 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
@@ -91,6 +91,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SegmentMean";
+  
   private Output output;
   
   private SegmentMean(Operation operation) {
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 38a0e75784c..b7ab590e976 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SegmentMin";
+  
   private Output output;
   
   private SegmentMin(Operation operation) {
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 36592e64f85..0f1179072e5 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SegmentProd";
+  
   private Output output;
   
   private SegmentProd(Operation operation) {
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 54287c045b2..fceec1bfe43 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SegmentSum";
+  
   private Output output;
   
   private SegmentSum(Operation operation) {
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 a12d7061324..a54e4ae51ea 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sigmoid";
+  
   private Output y;
   
   private Sigmoid(Operation operation) {
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 c53a0ae603f..125397bfd65 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SigmoidGrad";
+  
   private Output z;
   
   private SigmoidGrad(Operation operation) {
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 6591ed77c71..c9d8609872e 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sign";
+  
   private Output y;
   
   private Sign(Operation operation) {
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 15ef4b31dd2..a17ea9d288e 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sin";
+  
   private Output y;
   
   private Sin(Operation operation) {
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 8785916850b..613d983eef5 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sinh";
+  
   private Output y;
   
   private Sinh(Operation operation) {
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 d66475e2071..131cb7ed792 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
@@ -92,6 +92,9 @@ public Output asOutput() {
     return samples;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SobolSample";
+  
   private Output samples;
   
   private SobolSample(Operation operation) {
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 a4f3a22ebcd..79adcf30d76 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return activations;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Softplus";
+  
   private Output activations;
   
   private Softplus(Operation operation) {
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 f885abcbdeb..90174757bc3 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
@@ -64,6 +64,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SoftplusGrad";
+  
   private Output backprops;
   
   private SoftplusGrad(Operation operation) {
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 315173746b2..de62810d7ce 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sqrt";
+  
   private Output y;
   
   private Sqrt(Operation operation) {
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 5ba9497bbdd..2c4b301a60b 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SqrtGrad";
+  
   private Output z;
   
   private SqrtGrad(Operation operation) {
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 36fdb6bda9c..01ccd098cc8 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Square";
+  
   private Output y;
   
   private Square(Operation operation) {
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 c860747add8..bed2fe9bb77 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SquaredDifference";
+  
   private Output z;
   
   private SquaredDifference(Operation operation) {
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 1489a80202d..3578a962622 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
@@ -66,6 +66,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Sub";
+  
   private Output z;
   
   private Sub(Operation operation) {
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 1b1ddd50ba5..f09d909e8cb 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Tan";
+  
   private Output y;
   
   private Tan(Operation operation) {
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 f2611083984..04d9d1e092c 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Tanh";
+  
   private Output y;
   
   private Tanh(Operation operation) {
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 3ebc6ab598d..273c5a1f76d 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TanhGrad";
+  
   private Output z;
   
   private TanhGrad(Operation operation) {
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 a0a1f6697d1..5cd4b52fbed 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TruncateDiv";
+  
   private Output z;
   
   private TruncateDiv(Operation operation) {
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 cfa0461f460..48c92574eb4 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TruncateMod";
+  
   private Output z;
   
   private TruncateMod(Operation operation) {
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 4c509457c3e..582113e3320 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
@@ -100,6 +100,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnsortedSegmentMax";
+  
   private Output output;
   
   private UnsortedSegmentMax(Operation operation) {
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 bd12cae09b9..397ac5706a0 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
@@ -94,6 +94,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnsortedSegmentMin";
+  
   private Output output;
   
   private UnsortedSegmentMin(Operation operation) {
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 86f2b588cc0..c65fc484e4c 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
@@ -93,6 +93,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnsortedSegmentProd";
+  
   private Output output;
   
   private UnsortedSegmentProd(Operation operation) {
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 95868ce64d0..aaaf5b7bd23 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
@@ -96,6 +96,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnsortedSegmentSum";
+  
   private Output output;
   
   private UnsortedSegmentSum(Operation operation) {
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 5372f4b5c11..1a5e57836fc 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Xdivy";
+  
   private Output z;
   
   private Xdivy(Operation operation) {
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 f0586582e8c..a15f29dab04 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Xlog1py";
+  
   private Output z;
   
   private Xlog1py(Operation operation) {
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 6b303403408..a140c8aa6fe 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Xlogy";
+  
   private Output z;
   
   private Xlogy(Operation operation) {
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 431921f8e2b..0f3cee188fc 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return z;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Zeta";
+  
   private Output z;
   
   private Zeta(Operation operation) {
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 385bd855018..de2a4482f65 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
@@ -60,6 +60,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Erfinv";
+  
   private Output y;
   
   private erfinv(Operation operation) {
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 0855403368a..74388434149 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Dawsn";
+  
   private Output y;
   
   private Dawsn(Operation operation) {
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 1d2aa725fce..b36c55fdeb6 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Expint";
+  
   private Output y;
   
   private Expint(Operation operation) {
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 732cfb1ac20..bb9a9f47e78 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FresnelCos";
+  
   private Output y;
   
   private FresnelCos(Operation operation) {
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 cab6e46cba8..36681c87678 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FresnelSin";
+  
   private Output y;
   
   private FresnelSin(Operation operation) {
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 c313fb84aee..ed613a28b1a 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Spence";
+  
   private Output y;
   
   private Spence(Operation operation) {
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 f759acb0a51..760dd9fe913 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
@@ -207,6 +207,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Dequantize";
+  
   private Output output;
   
   private Dequantize(Operation operation) {
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 16ea096ef9d..1d79edcb24e 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
@@ -167,6 +167,9 @@ public Output asOutput() {
     return outputs;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FakeQuantWithMinMaxArgs";
+  
   private Output outputs;
   
   private FakeQuantWithMinMaxArgs(Operation operation) {
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 71da232b5df..62057eaefed 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
@@ -154,6 +154,9 @@ public Output asOutput() {
     return backprops;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FakeQuantWithMinMaxArgsGradient";
+  
   private Output backprops;
   
   private FakeQuantWithMinMaxArgsGradient(Operation operation) {
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 21113c6a6f3..667c5d60014 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
@@ -136,6 +136,9 @@ public Output asOutput() {
     return outputs;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FakeQuantWithMinMaxVars";
+  
   private Output outputs;
   
   private FakeQuantWithMinMaxVars(Operation operation) {
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 7b4e10d9c21..e9fcd339a75 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
@@ -132,6 +132,9 @@ public Output backpropWrtMax() {
     return backpropWrtMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FakeQuantWithMinMaxVarsGradient";
+  
   private Output backpropsWrtInput;
   private Output backpropWrtMin;
   private Output backpropWrtMax;
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 1302ae47b32..f65ed1735de 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
@@ -137,6 +137,9 @@ public Output asOutput() {
     return outputs;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FakeQuantWithMinMaxVarsPerChannel";
+  
   private Output outputs;
   
   private FakeQuantWithMinMaxVarsPerChannel(Operation operation) {
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 3e104c42c90..4fba9b56115 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
@@ -135,6 +135,9 @@ public Output backpropWrtMax() {
     return backpropWrtMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FakeQuantWithMinMaxVarsPerChannelGradient";
+  
   private Output backpropsWrtInput;
   private Output backpropWrtMin;
   private Output backpropWrtMax;
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 1b6ed2fd791..37f58cfa512 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
@@ -311,6 +311,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizeV2";
+  
   private Output output;
   private Output outputMin;
   private Output outputMax;
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 d90d91706d9..fd75b330e41 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
@@ -163,6 +163,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizeAndDequantizeV3";
+  
   private Output output;
   
   private QuantizeAndDequantize(Operation operation) {
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 3b77c20f70c..362375b40e2 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
@@ -101,6 +101,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizeDownAndShrinkRange";
+  
   private Output output;
   private Output outputMin;
   private Output outputMax;
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 46f73857d91..43839d072de 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
@@ -84,6 +84,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedConcat";
+  
   private Output output;
   private Output outputMin;
   private Output outputMax;
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 42da8ab044f..baa20635c51 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
@@ -151,6 +151,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMatMulWithBiasAndDequantize";
+  
   private Output out;
   
   private QuantizedMatMulWithBiasAndDequantize(Operation operation) {
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 a3ececf8fb3..950221b1b94 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
@@ -157,6 +157,9 @@ public Output maxOut() {
     return maxOut;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "QuantizedMatMulWithBiasAndRequantize";
+  
   private Output out;
   private Output minOut;
   private Output maxOut;
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 85eddcd506a..86ab731bb50 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
@@ -72,6 +72,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RequantizationRange";
+  
   private Output outputMin;
   private Output outputMax;
   
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 987dd660095..5df8ca0b622 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
@@ -90,6 +90,9 @@ public Output outputMax() {
     return outputMax;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Requantize";
+  
   private Output output;
   private Output outputMin;
   private Output outputMax;
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 c200b82da2a..7cc7de6d3db 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
@@ -109,6 +109,9 @@ public Output outputDenseValues() {
     return outputDenseValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedGather";
+  
   private List> outputNestedSplits;
   private Output outputDenseValues;
   
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 8fd3fb45bea..9d8f5594fd9 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
@@ -102,6 +102,9 @@ public Output rtDenseValues() {
     return rtDenseValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedRange";
+  
   private Output rtNestedSplits;
   private Output rtDenseValues;
   
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 3b094d70e0b..c9dcfe54bda 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
@@ -110,6 +110,9 @@ public Output outputDenseValues() {
     return outputDenseValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedTensorFromVariant";
+  
   private List> outputNestedSplits;
   private Output outputDenseValues;
   
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 d4443b915ac..7906048788d 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
@@ -79,6 +79,9 @@ public Output sparseDenseShape() {
     return sparseDenseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedTensorToSparse";
+  
   private Output sparseIndices;
   private Output sparseValues;
   private Output sparseDenseShape;
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 d5b03b37352..e469e6fc020 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
@@ -133,6 +133,9 @@ public Output asOutput() {
     return result;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedTensorToTensor";
+  
   private Output result;
   
   private RaggedTensorToTensor(Operation operation) {
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 b8c1570a573..6c22a0c4529 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return (Output) encodedRagged;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedTensorToVariant";
+  
   private Output encodedRagged;
   
   private RaggedTensorToVariant(Operation operation) {
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 1fca347c024..de24d12678f 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
@@ -152,6 +152,9 @@ public Output sampledExpectedCount() {
     return sampledExpectedCount;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AllCandidateSampler";
+  
   private Output sampledCandidates;
   private Output trueExpectedCount;
   private Output sampledExpectedCount;
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 f0d6d9d77cd..a87026cd7f1 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
@@ -60,6 +60,9 @@ public Output deleter() {
     return deleter;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AnonymousRandomSeedGenerator";
+  
   private Output handle;
   private Output deleter;
   
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 63e2698983b..9bc34d98ebb 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
@@ -46,6 +46,9 @@ public static DeleteRandomSeedGenerator create(Scope scope, Operand handle, O
     return new DeleteRandomSeedGenerator(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeleteRandomSeedGenerator";
+  
   
   private DeleteRandomSeedGenerator(Operation operation) {
     super(operation);
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 8295f36e678..761f945de1a 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
@@ -154,6 +154,9 @@ public Output sampledExpectedCount() {
     return sampledExpectedCount;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LogUniformCandidateSampler";
+  
   private Output sampledCandidates;
   private Output trueExpectedCount;
   private Output sampledExpectedCount;
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 41fb03d9dc2..58cc57d6c52 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
@@ -142,6 +142,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Multinomial";
+  
   private Output output;
   
   private Multinomial(Operation operation) {
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 b251813e265..246974eaf6f 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "NonDeterministicInts";
+  
   private Output output;
   
   private NonDeterministicInts(Operation operation) {
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 8ed64aa14a7..4be50b9cde0 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
@@ -133,6 +133,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ParameterizedTruncatedNormal";
+  
   private Output output;
   
   private ParameterizedTruncatedNormal(Operation operation) {
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 65ae0fbcbb4..13963e09ecb 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
@@ -130,6 +130,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomGamma";
+  
   private Output output;
   
   private RandomGamma(Operation operation) {
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 ba25e19b24e..ce3798cef3f 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
@@ -63,6 +63,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomGammaGrad";
+  
   private Output output;
   
   private RandomGammaGrad(Operation operation) {
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 e7bcb3d6855..d4b516343ac 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomPoissonV2";
+  
   private Output output;
   
   private RandomPoisson(Operation operation) {
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 738d92b7f0e..b08c31031ec 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
@@ -130,6 +130,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomShuffle";
+  
   private Output output;
   
   private RandomShuffle(Operation operation) {
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 48e08f355b3..bdd971cc19d 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
@@ -125,6 +125,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomStandardNormal";
+  
   private Output output;
   
   private RandomStandardNormal(Operation operation) {
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 121a58533c1..5e42c2d9691 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
@@ -126,6 +126,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomUniform";
+  
   private Output output;
   
   private RandomUniform(Operation operation) {
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 b2eafcadf4b..5232135ac1c 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
@@ -132,6 +132,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RandomUniformInt";
+  
   private Output output;
   
   private RandomUniformInt(Operation operation) {
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 a8520fc1144..7e3550cb71c 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
@@ -193,6 +193,9 @@ public Output asOutput() {
     return records;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RecordInput";
+  
   private Output records;
   
   private RecordInput(Operation operation) {
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 af9e90226b4..e3411c3b989 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
@@ -55,6 +55,9 @@ public static RngSkip create(Scope scope, Operand resource, Operand a
     return new RngSkip(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RngSkip";
+  
   
   private RngSkip(Operation operation) {
     super(operation);
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 f6b9ed59a68..b3c2dfce166 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
@@ -88,6 +88,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatefulRandomBinomial";
+  
   private Output output;
   
   private StatefulRandomBinomial(Operation operation) {
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 fd0f1cd16a4..12aabfa2a73 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatefulStandardNormalV2";
+  
   private Output output;
   
   private StatefulStandardNormal(Operation operation) {
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 97ad2eb4f00..86904de711f 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
@@ -88,6 +88,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatefulTruncatedNormal";
+  
   private Output output;
   
   private StatefulTruncatedNormal(Operation operation) {
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 8c6d86dd507..dd9a2c10af0 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatefulUniform";
+  
   private Output output;
   
   private StatefulUniform(Operation operation) {
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 e234af42486..0bf991bd72e 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatefulUniformFullInt";
+  
   private Output output;
   
   private StatefulUniformFullInt(Operation operation) {
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 a5550877593..74337edc44d 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatefulUniformInt";
+  
   private Output output;
   
   private StatefulUniformInt(Operation operation) {
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 d5473395eb3..1dbe0e5a7d0 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
@@ -89,6 +89,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessMultinomial";
+  
   private Output output;
   
   private StatelessMultinomial(Operation operation) {
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 9629ee7620e..03543495413 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
@@ -95,6 +95,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessRandomBinomial";
+  
   private Output output;
   
   private StatelessRandomBinomial(Operation operation) {
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 815e4b8c1ad..2c4eef75ff7 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessRandomGammaV2";
+  
   private Output output;
   
   private StatelessRandomGamma(Operation operation) {
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 028537a3417..07c5298cca0 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
@@ -86,6 +86,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessRandomNormal";
+  
   private Output output;
   
   private StatelessRandomNormal(Operation operation) {
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 e0c7e949dd3..e71c70e2c1f 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessRandomPoisson";
+  
   private Output output;
   
   private StatelessRandomPoisson(Operation operation) {
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 5ea49ccf36d..9eb6edc67e5 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
@@ -87,6 +87,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessRandomUniform";
+  
   private Output output;
   
   private StatelessRandomUniform(Operation operation) {
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 657153d3098..291cce74d19 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessRandomUniformFullInt";
+  
   private Output output;
   
   private StatelessRandomUniformFullInt(Operation operation) {
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 ebb569ea222..4695718a186 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessRandomUniformInt";
+  
   private Output output;
   
   private StatelessRandomUniformInt(Operation operation) {
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 180e5ffa4b5..3d4761fc4df 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
@@ -88,6 +88,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessTruncatedNormal";
+  
   private Output output;
   
   private StatelessTruncatedNormal(Operation operation) {
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 b40ddfb6e47..7b88d720386 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
@@ -128,6 +128,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TruncatedNormal";
+  
   private Output output;
   
   private TruncatedNormal(Operation operation) {
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 e568dd965ba..9e1f2b1abbd 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
@@ -154,6 +154,9 @@ public Output sampledExpectedCount() {
     return sampledExpectedCount;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UniformCandidateSampler";
+  
   private Output sampledCandidates;
   private Output trueExpectedCount;
   private Output sampledExpectedCount;
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 029a9990900..9eaacf4b26a 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchFFT";
+  
   private Output output;
   
   private BatchFft(Operation operation) {
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 c8357878666..551d7c3f139 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchFFT2D";
+  
   private Output output;
   
   private BatchFft2d(Operation operation) {
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 4ad58e855ae..beeb97ee414 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchFFT3D";
+  
   private Output output;
   
   private BatchFft3d(Operation operation) {
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 0e098f94b72..262b02d2bc5 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchIFFT";
+  
   private Output output;
   
   private BatchIfft(Operation operation) {
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 e689c9061d4..2145f201419 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchIFFT2D";
+  
   private Output output;
   
   private BatchIfft2d(Operation operation) {
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 5f23ed1ca7a..6a271795308 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchIFFT3D";
+  
   private Output output;
   
   private BatchIfft3d(Operation operation) {
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 802788288a6..632500fad5e 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FFT";
+  
   private Output output;
   
   private Fft(Operation operation) {
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 aaafdb8392f..201b2e3c8af 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FFT2D";
+  
   private Output output;
   
   private Fft2d(Operation operation) {
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 a7b29547d0c..7e840fbfb62 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FFT3D";
+  
   private Output output;
   
   private Fft3d(Operation operation) {
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 6ba09167aa0..c020956beec 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IFFT";
+  
   private Output output;
   
   private Ifft(Operation operation) {
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 086dd9d2338..c8cac107ff4 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IFFT2D";
+  
   private Output output;
   
   private Ifft2d(Operation operation) {
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 d1d114fc2d5..ce7f87a9aa2 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IFFT3D";
+  
   private Output output;
   
   private Ifft3d(Operation operation) {
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 8cbeb80aec5..80d3bb85291 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
@@ -103,6 +103,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IRFFT";
+  
   private Output output;
   
   private Irfft(Operation operation) {
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 a383b340c45..8acf23a4f23 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IRFFT2D";
+  
   private Output output;
   
   private Irfft2d(Operation operation) {
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 278bf3eac13..c7b9efabfd2 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "IRFFT3D";
+  
   private Output output;
   
   private Irfft3d(Operation operation) {
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 5b3dc8a4199..9764bcbf0f2 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
@@ -86,6 +86,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RFFT";
+  
   private Output output;
   
   private Rfft(Operation operation) {
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 7f47b98f969..91187dced7b 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
@@ -88,6 +88,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RFFT2D";
+  
   private Output output;
   
   private Rfft2d(Operation operation) {
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 7fa5f8f23b7..1eb113e9cf1 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
@@ -88,6 +88,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RFFT3D";
+  
   private Output output;
   
   private Rfft3d(Operation operation) {
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 f3b4e77d1f3..ec66167f7e6 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
@@ -145,6 +145,9 @@ public Output asOutput() {
     return sparseHandles;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AddManySparseToTensorsMap";
+  
   private Output sparseHandles;
   
   private AddManySparseToTensorsMap(Operation operation) {
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 0cc79427ce1..153e326aa9d 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
@@ -136,6 +136,9 @@ public Output asOutput() {
     return sparseHandle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AddSparseToTensorsMap";
+  
   private Output sparseHandle;
   
   private AddSparseToTensorsMap(Operation operation) {
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 7308a8a8ecb..15e62be4fa8 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
@@ -122,6 +122,9 @@ public Output resultShape() {
     return resultShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DenseToDenseSetOperation";
+  
   private Output resultIndices;
   private Output resultValues;
   private Output resultShape;
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 85a490c25a0..107f32524ea 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
@@ -137,6 +137,9 @@ public Output resultShape() {
     return resultShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DenseToSparseSetOperation";
+  
   private Output resultIndices;
   private Output resultValues;
   private Output resultShape;
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 a4fb2ee2e39..a1a6bb2fa49 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
@@ -115,6 +115,9 @@ public Output sparseShape() {
     return sparseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeserializeSparse";
+  
   private Output sparseIndices;
   private Output sparseValues;
   private Output sparseShape;
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 15751d4ca97..3f36812ea57 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
@@ -66,6 +66,9 @@ public static  SparseAccumulatorApplyGradient create(Scope scop
     return new SparseAccumulatorApplyGradient(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseAccumulatorApplyGradient";
+  
   
   private SparseAccumulatorApplyGradient(Operation operation) {
     super(operation);
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 d072e331bbf..87cbd112e57 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
@@ -87,6 +87,9 @@ public Output shape() {
     return shape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseAccumulatorTakeGradient";
+  
   private Output indices;
   private Output values;
   private Output shape;
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 1bab6a714a0..bc8beb287bb 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
@@ -97,6 +97,9 @@ public Output sumShape() {
     return sumShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseAdd";
+  
   private Output sumIndices;
   private Output sumValues;
   private Output sumShape;
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 1709c008119..c3fdf2952a9 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
@@ -80,6 +80,9 @@ public Output bValGrad() {
     return bValGrad;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseAddGrad";
+  
   private Output aValGrad;
   private Output bValGrad;
   
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 1ee35437c40..c6866997e30 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
@@ -122,6 +122,9 @@ public Output outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseConcat";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputShape;
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 7c9eea707df..b38fc0a6c46 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
@@ -148,6 +148,9 @@ public Output asOutput() {
     return handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseConditionalAccumulator";
+  
   private Output handle;
   
   private SparseConditionalAccumulator(Operation operation) {
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 72d7107e2d5..2cc80dcd83d 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
@@ -131,6 +131,9 @@ public Output outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseCross";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputShape;
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 aace49ffa77..40c5fc1446b 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
@@ -79,6 +79,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseDenseCwiseAdd";
+  
   private Output output;
   
   private SparseDenseCwiseAdd(Operation operation) {
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 78e4bcfe8b4..1d88f78e482 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseDenseCwiseDiv";
+  
   private Output output;
   
   private SparseDenseCwiseDiv(Operation operation) {
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 78b37a2306a..b0144601eb3 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseDenseCwiseMul";
+  
   private Output output;
   
   private SparseDenseCwiseMul(Operation operation) {
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 47baf154e30..6c8066061fc 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
@@ -125,6 +125,9 @@ public Output reverseIndexMap() {
     return reverseIndexMap;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseFillEmptyRows";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output emptyRowIndicator;
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 7289cfa1eef..3942e8bc8b3 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
@@ -76,6 +76,9 @@ public Output dDefaultValue() {
     return dDefaultValue;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseFillEmptyRowsGrad";
+  
   private Output dValues;
   private Output dDefaultValue;
   
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 42922e892cd..295063d560a 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
@@ -164,6 +164,9 @@ public Output asOutput() {
     return product;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseMatMul";
+  
   private Output product;
   
   private SparseMatMul(Operation operation) {
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 9e8ffaf3484..5288f7b5b88 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
@@ -119,6 +119,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseReduceMax";
+  
   private Output output;
   
   private SparseReduceMax(Operation operation) {
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 de96c4d2105..93ce28bb66a 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
@@ -125,6 +125,9 @@ public Output outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseReduceMaxSparse";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputShape;
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 b072fb46bfd..138bb1aab5b 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
@@ -118,6 +118,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseReduceSum";
+  
   private Output output;
   
   private SparseReduceSum(Operation operation) {
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 befdc901b28..e27a1a98861 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
@@ -124,6 +124,9 @@ public Output outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseReduceSumSparse";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputShape;
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 88be4106deb..16713d1f767 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
@@ -80,6 +80,9 @@ public Output outputValues() {
     return outputValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseReorder";
+  
   private Output outputIndices;
   private Output outputValues;
   
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 7d2799f8ffe..772b19db9c5 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
@@ -86,6 +86,9 @@ public Output outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseReshape";
+  
   private Output outputIndices;
   private Output outputShape;
   
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 785b1149b0a..867ceffa333 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentMean";
+  
   private Output output;
   
   private SparseSegmentMean(Operation operation) {
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 a0c8e8b8e43..1af1cf8f170 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentMeanGrad";
+  
   private Output output;
   
   private SparseSegmentMeanGrad(Operation operation) {
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 0458eca8621..593f96408c8 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentMeanWithNumSegments";
+  
   private Output output;
   
   private SparseSegmentMeanWithNumSegments(Operation operation) {
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 03b6e015a80..85d8284ca8f 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentSqrtN";
+  
   private Output output;
   
   private SparseSegmentSqrtN(Operation operation) {
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 cbe39991793..5893a8963f9 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentSqrtNGrad";
+  
   private Output output;
   
   private SparseSegmentSqrtNGrad(Operation operation) {
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 ce787acb499..334c7665238 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
@@ -80,6 +80,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentSqrtNWithNumSegments";
+  
   private Output output;
   
   private SparseSegmentSqrtNWithNumSegments(Operation operation) {
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 16e47ab2431..2125bc49719 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentSum";
+  
   private Output output;
   
   private SparseSegmentSum(Operation operation) {
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 569d0c691c6..0e0b0227a06 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSegmentSumWithNumSegments";
+  
   private Output output;
   
   private SparseSegmentSumWithNumSegments(Operation operation) {
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 5c429a40d9a..4ed30d8e2eb 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
@@ -99,6 +99,9 @@ public Output outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSlice";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputShape;
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 172d8bd5816..480631eccbc 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return valGrad;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSliceGrad";
+  
   private Output valGrad;
   
   private SparseSliceGrad(Operation operation) {
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 ee37d13c818..0906213115f 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
@@ -85,6 +85,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSoftmax";
+  
   private Output output;
   
   private SparseSoftmax(Operation operation) {
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 d6d86234578..3cbf1a6ef7d 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
@@ -79,6 +79,9 @@ public Output outputValues() {
     return outputValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSparseMaximum";
+  
   private Output outputIndices;
   private Output outputValues;
   
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 f46065ae9fc..b2f6aedbccb 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
@@ -78,6 +78,9 @@ public Output outputValues() {
     return outputValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSparseMinimum";
+  
   private Output outputIndices;
   private Output outputValues;
   
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 dee18e0e862..e93f6ebe40e 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
@@ -104,6 +104,9 @@ public List> outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseSplit";
+  
   private List> outputIndices;
   private List> outputValues;
   private List> outputShape;
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 86f9d3394d1..9959d57d16b 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseTensorDenseAdd";
+  
   private Output output;
   
   private SparseTensorDenseAdd(Operation operation) {
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 858bce58f73..63f3d3116c0 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
@@ -136,6 +136,9 @@ public Output asOutput() {
     return product;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseTensorDenseMatMul";
+  
   private Output product;
   
   private SparseTensorDenseMatMul(Operation operation) {
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 04b21e5d46e..0f86af1327d 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
@@ -126,6 +126,9 @@ public Output asOutput() {
     return dense;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseToDense";
+  
   private Output dense;
   
   private SparseToDense(Operation operation) {
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 3b606bbd6e9..31cbe67a914 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
@@ -152,6 +152,9 @@ public Output resultShape() {
     return resultShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseToSparseSetOperation";
+  
   private Output resultIndices;
   private Output resultValues;
   private Output resultShape;
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 8b38ac4f936..7fd5242cb20 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
@@ -179,6 +179,9 @@ public Output sparseShape() {
     return sparseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TakeManySparseFromTensorsMap";
+  
   private Output sparseIndices;
   private Output sparseValues;
   private Output sparseShape;
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 448a161166b..633457793a3 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
@@ -104,6 +104,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringJoin";
+  
   private Output output;
   
   private Join(Operation operation) {
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 14ac2b2a660..0b214f47017 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringLower";
+  
   private Output output;
   
   private Lower(Operation operation) {
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 615262737c6..23d90b3a2b1 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
@@ -143,6 +143,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ReduceJoin";
+  
   private Output output;
   
   private ReduceJoin(Operation operation) {
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 62923005059..446166c6e29 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
@@ -77,6 +77,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RegexFullMatch";
+  
   private Output output;
   
   private RegexFullMatch(Operation operation) {
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 39d76d9115b..3eaec903fee 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
@@ -106,6 +106,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RegexReplace";
+  
   private Output output;
   
   private RegexReplace(Operation operation) {
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 fe6714ca733..3aa7b0827eb 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
@@ -69,6 +69,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StaticRegexFullMatch";
+  
   private Output output;
   
   private StaticRegexFullMatch(Operation operation) {
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 e09c93144d4..c1802f48001 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
@@ -101,6 +101,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StaticRegexReplace";
+  
   private Output output;
   
   private StaticRegexReplace(Operation operation) {
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 0e6798c4bf4..3decf1e5c93 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
@@ -135,6 +135,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringFormat";
+  
   private Output output;
   
   private StringFormat(Operation operation) {
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 ff820abbea3..d9fc036ad22 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringLength";
+  
   private Output output;
   
   private StringLength(Operation operation) {
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 e54a46a6b69..6d68c11fe1b 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
@@ -95,6 +95,9 @@ public Output ngramsSplits() {
     return ngramsSplits;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringNGrams";
+  
   private Output ngrams;
   private Output ngramsSplits;
   
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 d1e4b45d745..87debf546cf 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
@@ -127,6 +127,9 @@ public Output shape() {
     return shape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringSplitV2";
+  
   private Output indices;
   private Output values;
   private Output shape;
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 eb8f1a23a4a..fc6f37bbabb 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringStrip";
+  
   private Output output;
   
   private Strip(Operation operation) {
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 9d6e21cbafc..153f6873d03 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
@@ -184,6 +184,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Substr";
+  
   private Output output;
   
   private Substr(Operation operation) {
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 82d26aebe40..11f025a4055 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringToHashBucket";
+  
   private Output output;
   
   private ToHashBucket(Operation operation) {
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 62737da0d0d..b1025fb9ccd 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
@@ -75,6 +75,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringToHashBucketFast";
+  
   private Output output;
   
   private ToHashBucketFast(Operation operation) {
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 c27d7053165..28af44e377f 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringToHashBucketStrong";
+  
   private Output output;
   
   private ToHashBucketStrong(Operation operation) {
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 8c0751ea782..e8e5e4039b9 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringToNumber";
+  
   private Output output;
   
   private ToNumber(Operation operation) {
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 1d5f077d04b..a39b08b1f5a 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
@@ -199,6 +199,9 @@ public Output charValues() {
     return charValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnicodeDecode";
+  
   private Output rowSplits;
   private Output charValues;
   
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 019afa8fe33..ce6977b63ef 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
@@ -213,6 +213,9 @@ public Output charToByteStarts() {
     return charToByteStarts;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnicodeDecodeWithOffsets";
+  
   private Output rowSplits;
   private Output charValues;
   private Output charToByteStarts;
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 1a539366d81..ab83ef9dcda 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
@@ -156,6 +156,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnicodeEncode";
+  
   private Output output;
   
   private UnicodeEncode(Operation operation) {
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 3da3bac675c..6d3600a1de3 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnicodeScript";
+  
   private Output output;
   
   private UnicodeScript(Operation operation) {
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 4b4e03fda8d..8f62db46152 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
@@ -203,6 +203,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnicodeTranscode";
+  
   private Output output;
   
   private UnicodeTranscode(Operation operation) {
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 47043fac5b2..df1bbc68b68 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
@@ -127,6 +127,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UnsortedSegmentJoin";
+  
   private Output output;
   
   private UnsortedSegmentJoin(Operation operation) {
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 343e4c58d5d..e90dc891dd8 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
@@ -99,6 +99,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StringUpper";
+  
   private Output output;
   
   private Upper(Operation operation) {
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 f8382c2cede..6743a4ef4c1 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
@@ -114,6 +114,9 @@ public Output asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AudioSummaryV2";
+  
   private Output summary;
   
   private AudioSummary(Operation operation) {
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 c056b2f4f35..ff9735f0b07 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
@@ -44,6 +44,9 @@ public static CloseSummaryWriter create(Scope scope, Operand writer) {
     return new CloseSummaryWriter(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CloseSummaryWriter";
+  
   
   private CloseSummaryWriter(Operation operation) {
     super(operation);
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 50cfefb2e9f..61e7405f74d 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
@@ -53,6 +53,9 @@ public static CreateSummaryDbWriter create(Scope scope, Operand writer, Opera
     return new CreateSummaryDbWriter(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CreateSummaryDbWriter";
+  
   
   private CreateSummaryDbWriter(Operation operation) {
     super(operation);
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 13130955bca..d113ebcf3f6 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
@@ -54,6 +54,9 @@ public static CreateSummaryFileWriter create(Scope scope, Operand writer, Ope
     return new CreateSummaryFileWriter(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CreateSummaryFileWriter";
+  
   
   private CreateSummaryFileWriter(Operation operation) {
     super(operation);
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 16babb3df73..6b1e610c632 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
@@ -44,6 +44,9 @@ public static FlushSummaryWriter create(Scope scope, Operand writer) {
     return new FlushSummaryWriter(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "FlushSummaryWriter";
+  
   
   private FlushSummaryWriter(Operation operation) {
     super(operation);
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 c98efad5b3b..669cbf5c2fb 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "HistogramSummary";
+  
   private Output summary;
   
   private HistogramSummary(Operation operation) {
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 50cc52f5769..5b0f9f8859f 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
@@ -166,6 +166,9 @@ public Output asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ImageSummary";
+  
   private Output summary;
   
   private ImageSummary(Operation operation) {
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 736aa827d82..9b6dc173abe 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
@@ -47,6 +47,9 @@ public static ImportEvent create(Scope scope, Operand writer, Operand asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MergeSummary";
+  
   private Output summary;
   
   private MergeSummary(Operation operation) {
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 c766d9759ed..416251aa6b1 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScalarSummary";
+  
   private Output summary;
   
   private ScalarSummary(Operation operation) {
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 525db2a64e8..9cc5fe6d83b 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
@@ -58,6 +58,9 @@ public Output asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatsAggregatorSummary";
+  
   private Output summary;
   
   private StatsAggregatorSummary(Operation operation) {
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 f27b996b716..131cb6e4a9d 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
@@ -109,6 +109,9 @@ public Output asOutput() {
     return (Output) writer;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SummaryWriter";
+  
   private Output writer;
   
   private SummaryWriter(Operation operation) {
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 0d6e950a4f3..85e0f8d533b 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return summary;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorSummaryV2";
+  
   private Output summary;
   
   private TensorSummary(Operation operation) {
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 69e42753c7c..306b1d88e6e 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
@@ -89,6 +89,9 @@ public static Options maxOutputs(Long maxOutputs) {
     return new Options().maxOutputs(maxOutputs);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WriteAudioSummary";
+  
   
   private WriteAudioSummary(Operation operation) {
     super(operation);
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 0d6b11f1f6d..fa10196ca72 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
@@ -50,6 +50,9 @@ public static WriteGraphSummary create(Scope scope, Operand writer, Operand WriteHistogramSummary create(Scope scope, Oper
     return new WriteHistogramSummary(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WriteHistogramSummary";
+  
   
   private WriteHistogramSummary(Operation operation) {
     super(operation);
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 26be4538bf0..286d584d695 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
@@ -91,6 +91,9 @@ public static Options maxImages(Long maxImages) {
     return new Options().maxImages(maxImages);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WriteImageSummary";
+  
   
   private WriteImageSummary(Operation operation) {
     super(operation);
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 e781534b31b..524b56bed7a 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
@@ -50,6 +50,9 @@ public static WriteRawProtoSummary create(Scope scope, Operand writer, Operan
     return new WriteRawProtoSummary(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WriteRawProtoSummary";
+  
   
   private WriteRawProtoSummary(Operation operation) {
     super(operation);
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 b3a7b3a6723..2317db7bdeb 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
@@ -54,6 +54,9 @@ public static  WriteScalarSummary create(Scope scope, Operand
     return new WriteScalarSummary(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WriteScalarSummary";
+  
   
   private WriteScalarSummary(Operation operation) {
     super(operation);
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 a538b5a4cfd..6d257f948e8 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
@@ -55,6 +55,9 @@ public static  WriteSummary create(Scope scope, Operand writ
     return new WriteSummary(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WriteSummary";
+  
   
   private WriteSummary(Operation operation) {
     super(operation);
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 615657b1408..9bbac83ac2c 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
@@ -90,6 +90,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AllToAll";
+  
   private Output output;
   
   private AllToAll(Operation operation) {
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 5b298bc1630..bafa9a893f9 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CollectivePermute";
+  
   private Output output;
   
   private CollectivePermute(Operation operation) {
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 73f1bfceb3e..bfdde5b98e2 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
@@ -170,6 +170,9 @@ public Output asOutput() {
     return topology;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ConfigureDistributedTPU";
+  
   private Output topology;
   
   private ConfigureDistributedTPU(Operation operation) {
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 d1fb1fa838d..1905a3082b3 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
@@ -45,6 +45,9 @@ public static ConfigureTPUEmbedding create(Scope scope, String config) {
     return new ConfigureTPUEmbedding(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ConfigureTPUEmbedding";
+  
   
   private ConfigureTPUEmbedding(Operation operation) {
     super(operation);
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 2c257fb6d2f..79dc79410a1 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CrossReplicaSum";
+  
   private Output output;
   
   private CrossReplicaSum(Operation operation) {
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 7b499d87664..4198c38e11c 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
@@ -90,6 +90,9 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
     return new Options().deviceOrdinal(deviceOrdinal);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EnqueueTPUEmbeddingIntegerBatch";
+  
   
   private EnqueueTPUEmbeddingIntegerBatch(Operation operation) {
     super(operation);
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 35185704d89..23288018938 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
@@ -143,6 +143,9 @@ public static Options combiners(List combiners) {
     return new Options().combiners(combiners);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EnqueueTPUEmbeddingSparseBatch";
+  
   
   private EnqueueTPUEmbeddingSparseBatch(Operation operation) {
     super(operation);
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 5e4bf1c6b27..59018e1b3e5 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
@@ -175,6 +175,9 @@ public static Options maxSequenceLengths(List maxSequenceLengths) {
     return new Options().maxSequenceLengths(maxSequenceLengths);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EnqueueTPUEmbeddingSparseTensorBatch";
+  
   
   private EnqueueTPUEmbeddingSparseTensorBatch(Operation operation) {
     super(operation);
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 19a5528dd5d..ad4d5f52fa8 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InfeedDequeue";
+  
   private Output output;
   
   private InfeedDequeue(Operation operation) {
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 3e9fe720ca9..f471da5b5d7 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
@@ -75,6 +75,9 @@ public Iterator> iterator() {
     return (Iterator) outputs.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InfeedDequeueTuple";
+  
   private List> outputs;
   
   private InfeedDequeueTuple(Operation operation) {
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 f40a1b7c5c4..9c79df444e3 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
@@ -132,6 +132,9 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
     return new Options().deviceOrdinal(deviceOrdinal);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InfeedEnqueue";
+  
   
   private InfeedEnqueue(Operation operation) {
     super(operation);
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 cdd475a08ae..b1d32f70ec9 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
@@ -81,6 +81,9 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
     return new Options().deviceOrdinal(deviceOrdinal);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InfeedEnqueuePrelinearizedBuffer";
+  
   
   private InfeedEnqueuePrelinearizedBuffer(Operation operation) {
     super(operation);
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 c97a792ae7d..d2a95d84244 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
@@ -121,6 +121,9 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
     return new Options().deviceOrdinal(deviceOrdinal);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InfeedEnqueueTuple";
+  
   
   private InfeedEnqueueTuple(Operation operation) {
     super(operation);
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 1222247d109..9e60fae350e 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
@@ -132,6 +132,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingADAMParameters";
+  
   
   private LoadTPUEmbeddingADAMParameters(Operation operation) {
     super(operation);
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 53af351f736..58cfa5cf465 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
@@ -134,6 +134,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingADAMParametersGradAccumDebug";
+  
   
   private LoadTPUEmbeddingADAMParametersGradAccumDebug(Operation operation) {
     super(operation);
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 66e2bc9a3d4..e4f4228f0f1 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
@@ -132,6 +132,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingAdadeltaParameters";
+  
   
   private LoadTPUEmbeddingAdadeltaParameters(Operation operation) {
     super(operation);
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 d659eb12ec3..76af15dc0b6 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
@@ -134,6 +134,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingAdadeltaParametersGradAccumDebug";
+  
   
   private LoadTPUEmbeddingAdadeltaParametersGradAccumDebug(Operation operation) {
     super(operation);
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 80b424e073c..dc4f5c62341 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
@@ -130,6 +130,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingAdagradParameters";
+  
   
   private LoadTPUEmbeddingAdagradParameters(Operation operation) {
     super(operation);
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 de11b50f1f9..6551f875f2d 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
@@ -132,6 +132,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingAdagradParametersGradAccumDebug";
+  
   
   private LoadTPUEmbeddingAdagradParametersGradAccumDebug(Operation operation) {
     super(operation);
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 b7bbb92fa90..d4a0103654c 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
@@ -134,6 +134,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingCenteredRMSPropParameters";
+  
   
   private LoadTPUEmbeddingCenteredRMSPropParameters(Operation operation) {
     super(operation);
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 7939230997f..a65301f6348 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
@@ -132,6 +132,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingFTRLParameters";
+  
   
   private LoadTPUEmbeddingFTRLParameters(Operation operation) {
     super(operation);
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 38ebb8518bd..5a1c165428d 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
@@ -134,6 +134,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingFTRLParametersGradAccumDebug";
+  
   
   private LoadTPUEmbeddingFTRLParametersGradAccumDebug(Operation operation) {
     super(operation);
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 7d0f7d014c3..407cf842f19 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
@@ -134,6 +134,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingMDLAdagradLightParameters";
+  
   
   private LoadTPUEmbeddingMDLAdagradLightParameters(Operation operation) {
     super(operation);
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 c705213c9a2..35b8479749b 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
@@ -130,6 +130,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingMomentumParameters";
+  
   
   private LoadTPUEmbeddingMomentumParameters(Operation operation) {
     super(operation);
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 d774094df05..babc2de15fd 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
@@ -132,6 +132,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingMomentumParametersGradAccumDebug";
+  
   
   private LoadTPUEmbeddingMomentumParametersGradAccumDebug(Operation operation) {
     super(operation);
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 57db2202b99..0ebad625abe 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
@@ -130,6 +130,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingProximalAdagradParameters";
+  
   
   private LoadTPUEmbeddingProximalAdagradParameters(Operation operation) {
     super(operation);
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 40eec1594f1..80b05d47203 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
@@ -132,6 +132,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug";
+  
   
   private LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug(Operation operation) {
     super(operation);
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 88e2c035ce8..d0e39d22edb 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
@@ -132,6 +132,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingRMSPropParameters";
+  
   
   private LoadTPUEmbeddingRMSPropParameters(Operation operation) {
     super(operation);
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 6e79a29f987..98f1043a768 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
@@ -134,6 +134,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingRMSPropParametersGradAccumDebug";
+  
   
   private LoadTPUEmbeddingRMSPropParametersGradAccumDebug(Operation operation) {
     super(operation);
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 32b34ea6262..ca881823239 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
@@ -128,6 +128,9 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingStochasticGradientDescentParameters";
+  
   
   private LoadTPUEmbeddingStochasticGradientDescentParameters(Operation operation) {
     super(operation);
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 2e822837449..3be811cd039 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
@@ -105,6 +105,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OutfeedDequeue";
+  
   private Output output;
   
   private OutfeedDequeue(Operation operation) {
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 b7c2f10fcac..6b9110232d8 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
@@ -116,6 +116,9 @@ public Iterator> iterator() {
     return (Iterator) outputs.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OutfeedDequeueTuple";
+  
   private List> outputs;
   
   private OutfeedDequeueTuple(Operation operation) {
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 16e8733bc55..46ee54430d9 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
@@ -46,6 +46,9 @@ public static  OutfeedEnqueue create(Scope scope, Operand in
     return new OutfeedEnqueue(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OutfeedEnqueue";
+  
   
   private OutfeedEnqueue(Operation operation) {
     super(operation);
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 43972c6f64a..25d110f1114 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
@@ -47,6 +47,9 @@ public static OutfeedEnqueueTuple create(Scope scope, Iterable> input
     return new OutfeedEnqueueTuple(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "OutfeedEnqueueTuple";
+  
   
   private OutfeedEnqueueTuple(Operation operation) {
     super(operation);
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 78b0e38f4ae..c5c9573fb75 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
@@ -122,6 +122,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "Prelinearize";
+  
   private Output output;
   
   private Prelinearize(Operation operation) {
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 cc5a77b7fe4..6ff29f7b63a 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
@@ -112,6 +112,9 @@ public Output asOutput() {
     return (Output) output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PrelinearizeTuple";
+  
   private Output output;
   
   private PrelinearizeTuple(Operation operation) {
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 9ed8bdf75bc..e2bacade157 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
@@ -74,6 +74,9 @@ public Iterator> iterator() {
     return (Iterator) outputs.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RecvTPUEmbeddingActivations";
+  
   private List> outputs;
   
   @SuppressWarnings("unchecked")
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 9f14bc5f984..6201ed4b9eb 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
@@ -146,6 +146,9 @@ public Output velocities() {
     return velocities;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingADAMParameters";
+  
   private Output parameters;
   private Output momenta;
   private Output velocities;
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 ba7a9aebf01..423fc97541e 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
@@ -153,6 +153,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingADAMParametersGradAccumDebug";
+  
   private Output parameters;
   private Output momenta;
   private Output velocities;
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 b7235410fa1..9a00080e017 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
@@ -146,6 +146,9 @@ public Output updates() {
     return updates;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingAdadeltaParameters";
+  
   private Output parameters;
   private Output accumulators;
   private Output updates;
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 5b563e92d70..3fec5d6a6f7 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
@@ -153,6 +153,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug";
+  
   private Output parameters;
   private Output accumulators;
   private Output updates;
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 f79703b3de7..07ed32ae1f9 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
@@ -139,6 +139,9 @@ public Output accumulators() {
     return accumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingAdagradParameters";
+  
   private Output parameters;
   private Output accumulators;
   
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 1ebf1ee8bee..39a8a7ab791 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
@@ -146,6 +146,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingAdagradParametersGradAccumDebug";
+  
   private Output parameters;
   private Output accumulators;
   private Output gradientAccumulators;
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 69fc77119ce..800cbd10aff 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
@@ -153,6 +153,9 @@ public Output mg() {
     return mg;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingCenteredRMSPropParameters";
+  
   private Output parameters;
   private Output ms;
   private Output mom;
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 556a2b5faa7..0e7114d3744 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
@@ -146,6 +146,9 @@ public Output linears() {
     return linears;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingFTRLParameters";
+  
   private Output parameters;
   private Output accumulators;
   private Output linears;
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 f80357dd124..2dbff3ea109 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
@@ -153,6 +153,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingFTRLParametersGradAccumDebug";
+  
   private Output parameters;
   private Output accumulators;
   private Output linears;
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 4b1ef14db2b..aa4be2cb318 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
@@ -153,6 +153,9 @@ public Output benefits() {
     return benefits;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingMDLAdagradLightParameters";
+  
   private Output parameters;
   private Output accumulators;
   private Output weights;
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 72732a3da00..7f397adda1c 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
@@ -139,6 +139,9 @@ public Output momenta() {
     return momenta;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingMomentumParameters";
+  
   private Output parameters;
   private Output momenta;
   
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 b8398bf62e9..15aceae7f2a 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
@@ -146,6 +146,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingMomentumParametersGradAccumDebug";
+  
   private Output parameters;
   private Output momenta;
   private Output gradientAccumulators;
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 43c9daa0f1a..4f20964f27f 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
@@ -139,6 +139,9 @@ public Output accumulators() {
     return accumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingProximalAdagradParameters";
+  
   private Output parameters;
   private Output accumulators;
   
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 982e7c8bd44..abde61ec5a9 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
@@ -146,6 +146,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug";
+  
   private Output parameters;
   private Output accumulators;
   private Output gradientAccumulators;
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 393cc2c482d..fcc01589e38 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
@@ -146,6 +146,9 @@ public Output mom() {
     return mom;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingRMSPropParameters";
+  
   private Output parameters;
   private Output ms;
   private Output mom;
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 2e65ab437da..0c3814b23b4 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
@@ -153,6 +153,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug";
+  
   private Output parameters;
   private Output ms;
   private Output mom;
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 c98b2b5f7a8..e69247fa0ce 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
@@ -138,6 +138,9 @@ public Output asOutput() {
     return parameters;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingStochasticGradientDescentParameters";
+  
   private Output parameters;
   
   private RetrieveTPUEmbeddingStochasticGradientDescentParameters(Operation operation) {
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 87b07cd2b8a..25d25c1d5bf 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
@@ -61,6 +61,9 @@ public static SendTPUEmbeddingGradients create(Scope scope, Iterable asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TPUCompilationResult";
+  
   private Output output;
   
   private TPUCompilationResult(Operation operation) {
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 5473e957471..138a7434106 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TPUEmbeddingActivations";
+  
   private Output output;
   
   private TPUEmbeddingActivations(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUOrdinalSelector.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUOrdinalSelector.java
index 156f4b779fe..2df183cb793 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUOrdinalSelector.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUOrdinalSelector.java
@@ -61,6 +61,9 @@ public Output asOutput() {
     return deviceOrdinals;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TPUOrdinalSelector";
+  
   private Output deviceOrdinals;
   
   private TPUOrdinalSelector(Operation operation) {
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 547c12d64e4..4cc6056c8bc 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
@@ -249,6 +249,9 @@ public static Options allowSoftPlacement(Boolean allowSoftPlacement) {
     return new Options().allowSoftPlacement(allowSoftPlacement);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TPUReplicateMetadata";
+  
   
   private TPUReplicateMetadata(Operation operation) {
     super(operation);
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 157cb366d65..a2df9260990 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
@@ -126,6 +126,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TPUReplicatedInput";
+  
   private Output output;
   
   private TPUReplicatedInput(Operation operation) {
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 0c169b3008d..24c9418b0c3 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
@@ -76,6 +76,9 @@ public Iterator> iterator() {
     return (Iterator) outputs.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TPUReplicatedOutput";
+  
   private List> outputs;
   
   @SuppressWarnings("unchecked")
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 bb35afe9d09..49895008bd2 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return response;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "WorkerHeartbeat";
+  
   private Output response;
   
   private WorkerHeartbeat(Operation operation) {
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 c493d6daa72..82583bd691e 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
@@ -55,6 +55,9 @@ public static  AccumulatorApplyGradient create(Scope scope, Ope
     return new AccumulatorApplyGradient(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AccumulatorApplyGradient";
+  
   
   private AccumulatorApplyGradient(Operation operation) {
     super(operation);
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 8146deccf7d..9fca915c550 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return numAccumulated;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AccumulatorNumAccumulated";
+  
   private Output numAccumulated;
   
   private AccumulatorNumAccumulated(Operation operation) {
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 747fcc6b123..b57bb702669 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
@@ -53,6 +53,9 @@ public static AccumulatorSetGlobalStep create(Scope scope, Operand hand
     return new AccumulatorSetGlobalStep(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AccumulatorSetGlobalStep";
+  
   
   private AccumulatorSetGlobalStep(Operation operation) {
     super(operation);
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 23f24d3f675..51de5485845 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
@@ -76,6 +76,9 @@ public Output asOutput() {
     return average;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AccumulatorTakeGradient";
+  
   private Output average;
   
   private AccumulatorTakeGradient(Operation operation) {
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 8153a364508..1b24ac1fe26 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
@@ -119,6 +119,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyAdaMax";
+  
   private Output out;
   
   private ApplyAdaMax(Operation operation) {
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 928e2ae0f4e..7e68618da7d 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
@@ -115,6 +115,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyAdadelta";
+  
   private Output out;
   
   private ApplyAdadelta(Operation operation) {
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 2a88b987503..c8311ac541a 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
@@ -128,6 +128,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyAdagrad";
+  
   private Output out;
   
   private ApplyAdagrad(Operation operation) {
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 e03d521353b..3bb9f9cae4b 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyAdagradDA";
+  
   private Output out;
   
   private ApplyAdagradDa(Operation operation) {
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 aeaaddb103c..da399e31eda 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
@@ -129,6 +129,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyAdagradV2";
+  
   private Output out;
   
   private ApplyAdagradV2(Operation operation) {
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 c6b93126708..31d98fa299b 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
@@ -142,6 +142,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyAdam";
+  
   private Output out;
   
   private ApplyAdam(Operation operation) {
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 d7ca57e1dce..1fe2cd756af 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyAddSign";
+  
   private Output out;
   
   private ApplyAddSign(Operation operation) {
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 fb1735ca92c..22aeeed0d91 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
@@ -135,6 +135,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyCenteredRMSProp";
+  
   private Output out;
   
   private ApplyCenteredRmsProp(Operation operation) {
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 54c9cab7494..fa89d721ca0 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
@@ -124,6 +124,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyFtrlV2";
+  
   private Output out;
   
   private ApplyFtrl(Operation operation) {
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 8377b0594e0..729312860fd 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
@@ -102,6 +102,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyGradientDescent";
+  
   private Output out;
   
   private ApplyGradientDescent(Operation operation) {
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 dbd26f4eb9c..d7885da2e32 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
@@ -136,6 +136,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyMomentum";
+  
   private Output out;
   
   private ApplyMomentum(Operation operation) {
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 c0332c9a840..d508e939714 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyPowerSign";
+  
   private Output out;
   
   private ApplyPowerSign(Operation operation) {
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 0f3e9af018a..bd710eb08ca 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
@@ -112,6 +112,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyProximalAdagrad";
+  
   private Output out;
   
   private ApplyProximalAdagrad(Operation operation) {
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 7a28929d7e7..eb5e9a96dc9 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
@@ -109,6 +109,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyProximalGradientDescent";
+  
   private Output out;
   
   private ApplyProximalGradientDescent(Operation operation) {
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 53ff4e45b87..388fc062c5d 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
@@ -125,6 +125,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ApplyRMSProp";
+  
   private Output out;
   
   private ApplyRmsProp(Operation operation) {
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 6e1ae852143..3b6da5b0811 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
@@ -141,6 +141,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BatchMatMulV2";
+  
   private Output output;
   
   private BatchMatMul(Operation operation) {
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 3708f037741..f35e9f5001f 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
@@ -148,6 +148,9 @@ public Output asOutput() {
     return handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ConditionalAccumulator";
+  
   private Output handle;
   
   private ConditionalAccumulator(Operation operation) {
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 f1d4fb5d792..e91afa44cd8 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
@@ -137,6 +137,9 @@ public Output numPresent() {
     return numPresent;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "GenerateVocabRemapping";
+  
   private Output remapping;
   private Output numPresent;
   
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 7807178f138..4fe4a27171a 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
@@ -93,6 +93,9 @@ public static Options deleteOldDirs(Boolean deleteOldDirs) {
     return new Options().deleteOldDirs(deleteOldDirs);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "MergeV2Checkpoints";
+  
   
   private MergeV2Checkpoints(Operation operation) {
     super(operation);
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 1a625589a1d..f43928961a9 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
@@ -65,6 +65,9 @@ public static NegTrain create(Scope scope, Operand wIn, Operand asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "PreventGradient";
+  
   private Output output;
   
   private PreventGradient(Operation operation) {
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 ee76a499d06..ca29897ca3d 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
@@ -53,6 +53,9 @@ public static  ResourceAccumulatorApplyGradient create(Scope sc
     return new ResourceAccumulatorApplyGradient(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceAccumulatorApplyGradient";
+  
   
   private ResourceAccumulatorApplyGradient(Operation operation) {
     super(operation);
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 3ec9d5dc02c..628a916f659 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return numAccumulated;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceAccumulatorNumAccumulated";
+  
   private Output numAccumulated;
   
   private ResourceAccumulatorNumAccumulated(Operation operation) {
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 d7f8261bc11..e04784aef48 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
@@ -51,6 +51,9 @@ public static ResourceAccumulatorSetGlobalStep create(Scope scope, Operand ha
     return new ResourceAccumulatorSetGlobalStep(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceAccumulatorSetGlobalStep";
+  
   
   private ResourceAccumulatorSetGlobalStep(Operation operation) {
     super(operation);
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 ab334ce4cc0..c27fb1db524 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return average;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceAccumulatorTakeGradient";
+  
   private Output average;
   
   private ResourceAccumulatorTakeGradient(Operation operation) {
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 c22944b05c8..5efab216739 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
@@ -104,6 +104,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyAdaMax";
+  
   
   private ResourceApplyAdaMax(Operation operation) {
     super(operation);
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 8a947bc150e..0121155a2ef 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
@@ -100,6 +100,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyAdadelta";
+  
   
   private ResourceApplyAdadelta(Operation operation) {
     super(operation);
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 33ae02d0f59..4517528d8db 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
@@ -114,6 +114,9 @@ public static Options updateSlots(Boolean updateSlots) {
     return new Options().updateSlots(updateSlots);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyAdagradV2";
+  
   
   private ResourceApplyAdagrad(Operation operation) {
     super(operation);
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 ffb77721112..7f5b26056ac 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
@@ -98,6 +98,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyAdagradDA";
+  
   
   private ResourceApplyAdagradDa(Operation operation) {
     super(operation);
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 8c68669fc92..20a07b4865d 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
@@ -127,6 +127,9 @@ public static Options useNesterov(Boolean useNesterov) {
     return new Options().useNesterov(useNesterov);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyAdam";
+  
   
   private ResourceApplyAdam(Operation operation) {
     super(operation);
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 86dcc2d06ef..ec13f10038d 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
@@ -111,6 +111,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyAdamWithAmsgrad";
+  
   
   private ResourceApplyAdamWithAmsgrad(Operation operation) {
     super(operation);
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 82489d348da..e64354ec3bb 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
@@ -101,6 +101,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyAddSign";
+  
   
   private ResourceApplyAddSign(Operation operation) {
     super(operation);
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 d76224d6022..c4c8d7c9ec7 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
@@ -120,6 +120,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyCenteredRMSProp";
+  
   
   private ResourceApplyCenteredRmsProp(Operation operation) {
     super(operation);
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 7add86848c9..6f321a053b3 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
@@ -109,6 +109,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyFtrlV2";
+  
   
   private ResourceApplyFtrl(Operation operation) {
     super(operation);
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 a57d2e90a18..0e495bdd651 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
@@ -87,6 +87,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyGradientDescent";
+  
   
   private ResourceApplyGradientDescent(Operation operation) {
     super(operation);
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 e58fd2150cd..3a986d617eb 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
@@ -121,6 +121,9 @@ public static Options useNesterov(Boolean useNesterov) {
     return new Options().useNesterov(useNesterov);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyKerasMomentum";
+  
   
   private ResourceApplyKerasMomentum(Operation operation) {
     super(operation);
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 51af89430d2..bfb176edf28 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
@@ -121,6 +121,9 @@ public static Options useNesterov(Boolean useNesterov) {
     return new Options().useNesterov(useNesterov);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyMomentum";
+  
   
   private ResourceApplyMomentum(Operation operation) {
     super(operation);
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 5f035f53935..c1ba8b0ebd7 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
@@ -101,6 +101,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyPowerSign";
+  
   
   private ResourceApplyPowerSign(Operation operation) {
     super(operation);
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 e2197540e94..b51ce4698e1 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
@@ -97,6 +97,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyProximalAdagrad";
+  
   
   private ResourceApplyProximalAdagrad(Operation operation) {
     super(operation);
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 d5b9d063a95..7f9c4f4e52c 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
@@ -94,6 +94,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyProximalGradientDescent";
+  
   
   private ResourceApplyProximalGradientDescent(Operation operation) {
     super(operation);
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 f79a1202f6a..4c400f1aaa1 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
@@ -110,6 +110,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyRMSProp";
+  
   
   private ResourceApplyRmsProp(Operation operation) {
     super(operation);
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 fe27517dee2..2935d3ca6bc 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
@@ -149,6 +149,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceConditionalAccumulator";
+  
   private Output handle;
   
   private ResourceConditionalAccumulator(Operation operation) {
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 d64efcb9474..9a50137d196 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
@@ -98,6 +98,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyAdadelta";
+  
   
   private ResourceSparseApplyAdadelta(Operation operation) {
     super(operation);
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 6ece72cb637..69a3e775622 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
@@ -117,6 +117,9 @@ public static Options updateSlots(Boolean updateSlots) {
     return new Options().updateSlots(updateSlots);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyAdagrad";
+  
   
   private ResourceSparseApplyAdagrad(Operation operation) {
     super(operation);
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 ad007159e6a..4f3189f074c 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
@@ -101,6 +101,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyAdagradDA";
+  
   
   private ResourceSparseApplyAdagradDa(Operation operation) {
     super(operation);
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 f8808aa3980..30e6c19da15 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
@@ -118,6 +118,9 @@ public static Options updateSlots(Boolean updateSlots) {
     return new Options().updateSlots(updateSlots);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyAdagradV2";
+  
   
   private ResourceSparseApplyAdagradV2(Operation operation) {
     super(operation);
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 e9482879729..ab9b9d3c38d 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
@@ -121,6 +121,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyCenteredRMSProp";
+  
   
   private ResourceSparseApplyCenteredRmsProp(Operation operation) {
     super(operation);
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 07f2e12f9b0..3ffcb127a48 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
@@ -113,6 +113,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyFtrlV2";
+  
   
   private ResourceSparseApplyFtrl(Operation operation) {
     super(operation);
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 e1ff036c295..0284564f78c 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
@@ -126,6 +126,9 @@ public static Options useNesterov(Boolean useNesterov) {
     return new Options().useNesterov(useNesterov);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyKerasMomentum";
+  
   
   private ResourceSparseApplyKerasMomentum(Operation operation) {
     super(operation);
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 80c58d282bc..5199932b5bc 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
@@ -126,6 +126,9 @@ public static Options useNesterov(Boolean useNesterov) {
     return new Options().useNesterov(useNesterov);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyMomentum";
+  
   
   private ResourceSparseApplyMomentum(Operation operation) {
     super(operation);
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 75e7ca9e0f1..e235a19f5d1 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
@@ -102,6 +102,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyProximalAdagrad";
+  
   
   private ResourceSparseApplyProximalAdagrad(Operation operation) {
     super(operation);
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 bf48496179c..08a9edc01c4 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
@@ -98,6 +98,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyProximalGradientDescent";
+  
   
   private ResourceSparseApplyProximalGradientDescent(Operation operation) {
     super(operation);
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 0dc980bb6f8..982e1f30eb7 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
@@ -113,6 +113,9 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyRMSProp";
+  
   
   private ResourceSparseApplyRmsProp(Operation operation) {
     super(operation);
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 ecd4a059793..5a2466f501d 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
@@ -93,6 +93,9 @@ public Iterator> iterator() {
     return (Iterator) tensors.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RestoreV2";
+  
   private List> tensors;
   
   private Restore(Operation operation) {
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 e1148129d86..631a127a44f 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return tensor;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RestoreSlice";
+  
   private Output tensor;
   
   private RestoreSlice(Operation operation) {
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 b33f1c1c33b..781714d8121 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
@@ -60,6 +60,9 @@ public static Save create(Scope scope, Operand prefix, Operand
     return new Save(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SaveV2";
+  
   
   private Save(Operation operation) {
     super(operation);
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 25c91540ede..e8e67190e63 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
@@ -86,6 +86,9 @@ public static SaveSlices create(Scope scope, Operand filename, Operand<
     return new SaveSlices(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SaveSlices";
+  
   
   private SaveSlices(Operation operation) {
     super(operation);
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 b5629b59b88..cdee1af05f5 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
@@ -62,6 +62,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SdcaFprint";
+  
   private Output output;
   
   private SdcaFprint(Operation operation) {
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 9cf443dc4d8..a38f6773d7f 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
@@ -163,6 +163,9 @@ public List> outDeltaDenseWeights() {
     return outDeltaDenseWeights;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SdcaOptimizerV2";
+  
   private Output outExampleStateData;
   private List> outDeltaSparseWeights;
   private List> outDeltaDenseWeights;
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 d531030e063..24c6d53ef9d 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
@@ -53,6 +53,9 @@ public static SdcaShrinkL1 create(Scope scope, Iterable> weigh
     return new SdcaShrinkL1(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SdcaShrinkL1";
+  
   
   private SdcaShrinkL1(Operation operation) {
     super(operation);
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 6ed5c2faee3..190449c8ca7 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyAdadelta";
+  
   private Output out;
   
   private SparseApplyAdadelta(Operation operation) {
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 90cbe36a32d..71776f4fd26 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
@@ -133,6 +133,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyAdagradV2";
+  
   private Output out;
   
   private SparseApplyAdagrad(Operation operation) {
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 23c791a6d50..7f13dd080dd 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
@@ -116,6 +116,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyAdagradDA";
+  
   private Output out;
   
   private SparseApplyAdagradDa(Operation operation) {
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 367de145c5e..b73275139d1 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
@@ -136,6 +136,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyCenteredRMSProp";
+  
   private Output out;
   
   private SparseApplyCenteredRmsProp(Operation operation) {
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 defb68856e6..b8bd88a291a 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
@@ -128,6 +128,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyFtrlV2";
+  
   private Output out;
   
   private SparseApplyFtrl(Operation operation) {
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 ebd4d0e7c14..5e8bf197092 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
@@ -141,6 +141,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyMomentum";
+  
   private Output out;
   
   private SparseApplyMomentum(Operation operation) {
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 0a73d0a138c..19ede0d5f71 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyProximalAdagrad";
+  
   private Output out;
   
   private SparseApplyProximalAdagrad(Operation operation) {
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 2a4ef9f900b..14735403f02 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
@@ -113,6 +113,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyProximalGradientDescent";
+  
   private Output out;
   
   private SparseApplyProximalGradientDescent(Operation operation) {
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 5205086b7dd..c0b39b65e5e 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
@@ -128,6 +128,9 @@ public Output asOutput() {
     return out;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseApplyRMSProp";
+  
   private Output out;
   
   private SparseApplyRmsProp(Operation operation) {
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 42d68f0f59b..1bcfde7b183 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TileGrad";
+  
   private Output output;
   
   private TileGrad(Operation operation) {
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 1d8b4fe476b..e06919d04bd 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
@@ -73,6 +73,9 @@ public Output rhsOutput() {
     return rhsOutput;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaBroadcastHelper";
+  
   private Output lhsOutput;
   private Output rhsOutput;
   
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 21a978fc7a8..717b65c931e 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return outputs;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaClusterOutput";
+  
   private Output outputs;
   
   private ClusterOutput(Operation operation) {
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 7727cf1e9ac..05cec5b6d51 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
@@ -81,6 +81,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaConv";
+  
   private Output output;
   
   private Conv(Operation operation) {
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 751e47f4d5b..f8cdec66d1f 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
@@ -73,6 +73,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaDequantize";
+  
   private Output output;
   
   private Dequantize(Operation operation) {
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 0f3e1ef83df..9cb83d061cb 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
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaDot";
+  
   private Output output;
   
   private Dot(Operation operation) {
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 b6ecba31189..b9e2bebf9b8 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaDynamicSlice";
+  
   private Output output;
   
   private DynamicSlice(Operation operation) {
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 b974b64196e..dccbdd10da8 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
@@ -78,6 +78,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaDynamicUpdateSlice";
+  
   private Output output;
   
   private DynamicUpdateSlice(Operation operation) {
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 f5bf706641a..451fb27bc49 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return product;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaEinsum";
+  
   private Output product;
   
   private Einsum(Operation operation) {
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 d5b3298b395..9daa1808620 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaGather";
+  
   private Output output;
   
   private Gather(Operation operation) {
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 9fd5e4c774d..d1cf154bd8a 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
@@ -73,6 +73,9 @@ public Output sortedValues() {
     return sortedValues;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaKeyValueSort";
+  
   private Output sortedKeys;
   private Output sortedValues;
   
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 eafaf001168..c56631c48f2 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
@@ -74,6 +74,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaPad";
+  
   private Output output;
   
   private Pad(Operation operation) {
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 03274eb84e6..fe26ee27587 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
@@ -71,6 +71,9 @@ public Output asOutput() {
     return tensor;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaRecv";
+  
   private Output tensor;
   
   private Recv(Operation operation) {
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 a27b87f6c1a..886cc40b3ab 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
@@ -57,6 +57,9 @@ public Output asOutput() {
     return id;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaReplicaId";
+  
   private Output id;
   
   private ReplicaId(Operation operation) {
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 abbecd3e54b..9ce4468fdfe 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
@@ -82,6 +82,9 @@ public Output v() {
     return v;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaSelfAdjointEig";
+  
   private Output w;
   private Output v;
   
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 3e060842de3..d1172f8e96f 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
@@ -52,6 +52,9 @@ public static  Send create(Scope scope, Operand tensor, Stri
     return new Send(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaSend";
+  
   
   private Send(Operation operation) {
     super(operation);
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 d8d879183d2..dbc255aa607 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
@@ -61,6 +61,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaSharding";
+  
   private Output output;
   
   private Sharding(Operation operation) {
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 abafbd5e286..d7f9aae6449 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
@@ -67,6 +67,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaSort";
+  
   private Output output;
   
   private Sort(Operation operation) {
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 e3571702151..cd0a67f33b4 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
@@ -86,6 +86,9 @@ public Output v() {
     return v;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaSvd";
+  
   private Output s;
   private Output u;
   private Output v;

From 208b84a1a09d38ab9821d66572c1328326685c5a Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 10:42:22 -0400
Subject: [PATCH 09/33] fix dependencies for other Tensorflow Java modules

---
 tensorflow-keras/pom.xml | 29 +++--------------------------
 1 file changed, 3 insertions(+), 26 deletions(-)

diff --git a/tensorflow-keras/pom.xml b/tensorflow-keras/pom.xml
index c314b53bcc0..b33d1201fd9 100644
--- a/tensorflow-keras/pom.xml
+++ b/tensorflow-keras/pom.xml
@@ -27,22 +27,17 @@
     
     tensorflow-keras
     jar
-
     TensorFlow Keras Library
+    Java implementation of the TensorFlow Keras API
+
     
         
     
-    Java implementation of the TensorFlow Keras API
 
     
         
             org.tensorflow
-            tensorflow-core-api
-            ${project.version}
-        
-        
-            org.tensorflow
-            tensorflow-core-generator
+            tensorflow-core-platform
             ${project.version}
         
         
@@ -50,18 +45,6 @@
             tensorflow-framework
             ${project.version}
         
-        
-            org.tensorflow
-            ndarray
-            ${project.version}
-        
-        
-        
-            com.google.protobuf
-            protobuf-java
-            3.11.4
-        
-
         
             org.json
             json
@@ -73,12 +56,6 @@
             commons-csv
             1.8
         
-
-        
-            org.tensorflow
-            tensorflow-core-platform
-            ${project.version}
-        
         
             org.junit.jupiter
             junit-jupiter-api

From 39131619f3a4c970f5f62dacdbaa93ac3f9bf996 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 10:46:20 -0400
Subject: [PATCH 10/33] formatting fix

---
 .../java/org/tensorflow/keras/utils/EagerTestSession.java | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java
index 3bc8091811a..6b7ebf9e2f2 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java
@@ -56,10 +56,10 @@ public Ops getTF() {
     return tf;
   }
 
-    /**
-     * Get the TensorFlow EagerSession instance
-     * @return the TensorFlow EagerSession instance
-     */
+  /**
+   * Get the TensorFlow EagerSession instance
+   * @return the TensorFlow EagerSession instance
+   */
   public EagerSession getSession() {
     return session;
   }

From b5a7c0f9f54acf1fb0f57003027aa0843ae67c82 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 10:48:23 -0400
Subject: [PATCH 11/33] Fix ctors with name to properly pass the name to the
 the super ctor.

---
 .../keras/{optimizer => optimizers}/AdaDelta.java  | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/AdaDelta.java (92%)

diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaDelta.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaDelta.java
similarity index 92%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaDelta.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaDelta.java
index f02d2664759..b0a9dcf7d68 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaDelta.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaDelta.java
@@ -19,7 +19,6 @@
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
-import org.tensorflow.keras.backend.tf.ControlDependencies;
 import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
@@ -33,7 +32,6 @@
  * 
Two accumulation steps are required: 1) the accumulation of gradients squared, 2) the
  * accumulation of updates squared.
  *
- * @param  The Type for the call operation
  */
 public class AdaDelta extends org.tensorflow.framework.optimizers.AdaDelta
     implements OptimizerInterface {
@@ -69,7 +67,7 @@ public AdaDelta(Ops tf) {
    * @param name the name of the Optimizer, defaults to "Adadelta"
    */
   public AdaDelta(Ops tf, String name) {
-    this(tf, LEARNING_RATE_DEFAULT, RHO_DEFAULT, EPSILON_DEFAULT);
+    this(tf, name, LEARNING_RATE_DEFAULT, RHO_DEFAULT, EPSILON_DEFAULT);
   }
 
   /**
@@ -90,7 +88,7 @@ public AdaDelta(Ops tf, float learningRate) {
    * @param learningRate The learning rate
    */
   public AdaDelta(Ops tf, String name, float learningRate) {
-    this(tf, learningRate, RHO_DEFAULT, EPSILON_DEFAULT);
+    this(tf, name, learningRate, RHO_DEFAULT, EPSILON_DEFAULT);
   }
 
   /**
@@ -129,15 +127,14 @@ protected Optional prepare(String name) {
       case 1:
         return Optional.of(initializers.get(0));
       default:
-        return Optional.of(
-            ControlDependencies.addControlDependencies(tf, this.getOptimizerName(), initializers));
+        return Optional.of( tf.withSubScope(name).withControlDependencies(initializers).noOp());
     }
   }
 
   /**
    * Create an Adam Optimizer from a config object
    *
-   * @param graph the tensorflow graph
+   * @param tf the tensorflow Ops
    * @param config a config object to initialize, he config object has keys for "name",
    *     "learning_rate", "rho" and "epsilon". If a key is missing the default value is used.
    */
@@ -148,7 +145,8 @@ public static AdaDelta fromConfig(Ops tf, Map config) {
   /**
    * Create an Adadelta optimizer
    *
-   * @param graph the tensorflow graph @@param config a config object to initialize, the config
+   * @param tf the tensorflow Ops
+   * @param config a config object to initialize, the config
    *     object has keys for "name", "learning_rate", "rho" and "epsilon". If a key is missing the
    *     default value is used.
    */

From fcba0a525d4712fca5210db71c141bc1bce87307 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 13:04:27 -0400
Subject: [PATCH 12/33] change asserts to IllegalArgumentException fix javadoc,
 fix casts

---
 .../{optimizer => optimizers}/Nadam.java      | 47 +++++++++----------
 1 file changed, 22 insertions(+), 25 deletions(-)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/Nadam.java (92%)

diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Nadam.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Nadam.java
similarity index 92%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Nadam.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Nadam.java
index 4772c247ef8..a2eba4ecb49 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Nadam.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Nadam.java
@@ -18,15 +18,15 @@
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
+
+import org.tensorflow.DataType;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
-import org.tensorflow.op.Scope;
 import org.tensorflow.op.core.Assign;
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
@@ -52,7 +52,6 @@ public class Nadam extends org.tensorflow.framework.optimizers.Optimizer
   public static final float BETA_ONE_DEFAULT = 0.9F;
   public static final float BETA_TWO_DEFAULT = 0.999F;
 
-  private Scope scope;
   private final Map config = new HashMap<>();
 
   private float learningRate;
@@ -144,7 +143,6 @@ public Nadam(Ops tf, float learningRate, float betaOne, float betaTwo, float eps
     this.betaOne = betaOne;
     this.betaTwo = betaTwo;
     this.epsilon = epsilon;
-    this.scope = tf.scope();
     initConfig(learningRate, betaOne, betaTwo, epsilon);
   }
 
@@ -165,7 +163,6 @@ public Nadam(
     this.betaOne = betaOne;
     this.betaTwo = betaTwo;
     this.epsilon = epsilon;
-    this.scope = tf.scope();
 
     initConfig(learningRate, betaOne, betaTwo, epsilon);
   }
@@ -228,6 +225,7 @@ protected void createSlots(List> variables) {
 
   /**
    * Create slots for first and second momements and momentum
+   *
    * @param v the variable
    * @param  the data type or the Variable
    */
@@ -247,8 +245,8 @@ private  void createNadamSlot(Output v) {
   /** {@inheritDoc} */
   @Override
   protected Optional prepare(String scopeName) {
-    Constant one = tf.constant(1.0F);
-    Constant point5 = tf.constant(0.5F);
+    Constant one = tf.constant(1.0F);
+    Constant point5 = tf.constant(0.5F);
 
     learningRateConst = tf.constant(learningRate);
     betaOneConst = tf.constant(betaOne);
@@ -310,47 +308,50 @@ protected Optional prepare(String scopeName) {
   /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
+    DataType dType = gradient.dataType();
     Variable m = getSlot(variable, FIRST_MOMENT).get(); // first Moment
     Variable v = getSlot(variable, SECOND_MOMENT).get(); // Second Moment
 
     //  g_prime = grad / coefficients['one_minus_m_schedule_new']
-    Operand g_prime = tf.math.div((Operand) gradient, one_minus_m_schedule_new);
+    Operand g_prime = tf.math.div(gradient, tf.dtypes.cast(one_minus_m_schedule_new, dType));
     // m_t = (coefficients['beta_1_t'] * m + coefficients['one_minus_beta_1_t'] * grad)
-    Operand m_t =
+    Operand m_t =
         tf.math.add(
-            tf.math.mul(betaOneConst, (Operand) m),
-            tf.math.mul(one_minus_beta_1, (Operand) gradient));
+            tf.math.mul(tf.dtypes.cast(betaOneConst, dType), m),
+            tf.math.mul(tf.dtypes.cast(one_minus_beta_1, dType), gradient));
     // m_t = state_ops.assign(m, m_t, use_locking=self._use_locking)
     // update m
     m_t = tf.assign(m, m_t, Assign.useLocking(true));
 
     // m_t_prime = m_t / coefficients['one_minus_m_schedule_next']
-    Operand m_t_prime = tf.math.div(m_t, one_minus_m_schedule_next);
+    Operand m_t_prime = tf.math.div(m_t, tf.dtypes.cast(one_minus_m_schedule_next, dType));
 
     // v_t = (coefficients['beta_2_t'] * v + coefficients['one_minus_beta_2_t'] *
     // math_ops.square(grad))
-    Operand v_t =
+    Operand v_t =
         tf.math.add(
-            tf.math.mul(betaTwoConst, (Operand) v),
-            tf.math.mul(one_minus_beta_2, tf.math.square((Operand) gradient)));
+            tf.math.mul(tf.dtypes.cast(betaTwoConst, dType), v),
+            tf.math.mul(tf.dtypes.cast(one_minus_beta_2, dType), tf.math.square(gradient)));
     // v_t = state_ops.assign(v, v_t, use_locking=self._use_locking)
     // update v
     v_t = tf.assign(v, v_t, Assign.useLocking(true));
 
     // v_t_prime = v_t / coefficients['v_t_prime_denominator']
-    Operand v_t_prime = tf.math.div(v_t, v_t_prime_denominator);
+    Operand v_t_prime = tf.math.div(v_t, tf.dtypes.cast(v_t_prime_denominator, dType));
 
     // m_t_bar = (coefficients['one_minus_m_t'] * g_prime + coefficients['m_t_1'] * m_t_prime)
-    Operand m_t_bar =
-        tf.math.add(tf.math.mul(one_minus_m_t, g_prime), tf.math.mul(m_t_1, m_t_prime));
+    Operand m_t_bar =
+        tf.math.add(
+            tf.math.mul(tf.dtypes.cast(one_minus_m_t, dType), g_prime),
+            tf.math.mul(tf.dtypes.cast(m_t_1, dType), m_t_prime));
     // var_t = var - coefficients['lr_t'] * m_t_bar / (math_ops.sqrt(v_t_prime) +
     // coefficients['epsilon'])
-    Operand var_t =
+    Operand var_t =
         tf.math.sub(
             variable,
             tf.math.div(
-                tf.math.mul(learningRateConst, m_t_bar),
-                tf.math.add(tf.math.sqrt(v_t_prime), epsilonConst)));
+                tf.math.mul(tf.dtypes.cast(learningRateConst, dType), m_t_bar),
+                tf.math.add(tf.math.sqrt(v_t_prime), tf.dtypes.cast(epsilonConst, dType))));
     // assign(var, var_t, use_locking=self._use_locking)
     return tf.assign(variable, var_t, Assign.useLocking(true));
   }
@@ -395,8 +396,4 @@ private void initConfig(float learningRate, float betaOne, float betaTwo, float
     config.put(BETA_ONE_KEY, betaOne);
     config.put(BETA_TWO_KEY, betaTwo);
   }
-
-  private float calcM(int iteration) {
-    return betaOne * (1 - .05F * (float) Math.pow(this.decayBase, this.decay * iteration));
-  }
 }

From 960cfc3ca4e010fca3bd549df6d16a17fb0b22bc Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 13:05:22 -0400
Subject: [PATCH 13/33] change asserts to IllegalArgumentException

---
 .../{optimizer => optimizers}/AdaGrad.java    | 12 +++----
 .../{optimizer => optimizers}/AdaGradDA.java  | 21 ++++++-----
 .../keras/{optimizer => optimizers}/Adam.java |  0
 .../{optimizer => optimizers}/Adamax.java     |  0
 .../keras/{optimizer => optimizers}/Ftrl.java | 36 +++++++++++--------
 .../OptimizerInterface.java                   | 16 +++++----
 .../{optimizer => optimizers}/Optimizers.java | 35 +++++++++---------
 .../{optimizer => optimizers}/RMSProp.java    |  0
 .../keras/{optimizer => optimizers}/SGD.java  |  7 ++--
 9 files changed, 71 insertions(+), 56 deletions(-)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/AdaGrad.java (94%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/AdaGradDA.java (88%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/Adam.java (100%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/Adamax.java (100%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/Ftrl.java (87%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/OptimizerInterface.java (76%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/Optimizers.java (80%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/RMSProp.java (100%)
 rename tensorflow-keras/src/main/java/org/tensorflow/keras/{optimizer => optimizers}/SGD.java (96%)

diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGrad.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGrad.java
similarity index 94%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGrad.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGrad.java
index 6010a95b199..039cf4a0d82 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGrad.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGrad.java
@@ -99,15 +99,15 @@ public AdaGrad(Ops tf, float learningRate, float initialAccumulatorValue) {
    */
   public AdaGrad(Ops tf, String name, float learningRate, float initialAccumulatorValue) {
     super(assertGraph(tf), name, learningRate, initialAccumulatorValue);
-    assert initialAccumulatorValue >= 0.0F
-        : "initial_accumulator_value must be non-negative: " + initialAccumulatorValue;
+    if(initialAccumulatorValue < 0.0F)
+        throw new IllegalArgumentException( "initial_accumulator_value must be non-negative: " + initialAccumulatorValue);
     initConfig(learningRate, initialAccumulatorValue);
   }
 
   /**
    * Create an AdaGrad Optimizer from a config object
    *
-   * @param graph the tensorflow graph
+   * @param tf the TensorFlow Ops
    * @param config a config object to initialize, , the config object has keys for "name",
    *     "learning_rate" and "accumulator". If a key is missing the default value is used.
    */
@@ -118,7 +118,7 @@ public static AdaGrad fromConfig(Ops tf, Map config) {
   /**
    * Create an AdaGrad Optimizer from a config object
    *
-   * @param graph the tensorflow graph
+   * @param tf the TensorFlow Ops
    * @param config a config object to initialize, the config object has keys for "name",
    *     "learning_rate" and "accumulator". If a key is missing the default value is used.
    */
@@ -137,8 +137,8 @@ public static AdaGrad create(Ops tf, Map config) {
   /**
    * Initialize the configuration
    *
-   * @param learningRate
-   * @param initialAccumulatorValue
+   * @param learningRate the learning rate
+   * @param initialAccumulatorValue the initial Accumulator value
    */
   private void initConfig(float learningRate, float initialAccumulatorValue) {
     this.learningRate = learningRate;
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGradDA.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGradDA.java
similarity index 88%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGradDA.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGradDA.java
index d7ee03338c8..2f15024bf56 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/AdaGradDA.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGradDA.java
@@ -85,10 +85,12 @@ public AdaGradDA(
       float l1Strength,
       float l2Strength) {
     super(assertGraph(tf), learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-    assert initialAccumulatorValue >= 0.0F
-        : "initial_accumulator_value must be non-negative: " + initialAccumulatorValue;
-    assert l1Strength >= 0.0F : "l1Strength must be non-negative: " + l1Strength;
-    assert l2Strength >= 0.0F : "l2Strength must be non-negative: " + l2Strength;
+    if( initialAccumulatorValue < 0.0F)
+        throw new IllegalArgumentException("initial_accumulator_value must be non-negative: " + initialAccumulatorValue);
+    if(l1Strength < 0)
+      throw new IllegalArgumentException("l1Strength must be non-negative: " + l1Strength);
+    if(l2Strength < 0)
+      throw new IllegalArgumentException("l2Strength must be non-negative: " + l2Strength);
     initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength);
   }
 
@@ -110,10 +112,13 @@ public AdaGradDA(
       float l1Strength,
       float l2Strength) {
     super(assertGraph(tf), name, learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-    assert initialAccumulatorValue >= 0.0F
-        : "initial_accumulator_value must be non-negative: " + initialAccumulatorValue;
-    assert l1Strength >= 0.0F : "l1Strength must be non-negative: " + l1Strength;
-    assert l2Strength >= 0.0F : "l2Strength must be non-negative: " + l2Strength;
+    if( initialAccumulatorValue < 0.0F)
+      throw new IllegalArgumentException("initial_accumulator_value must be non-negative: " + initialAccumulatorValue);
+    if(l1Strength < 0)
+      throw new IllegalArgumentException("l1Strength must be non-negative: " + l1Strength);
+    if(l2Strength < 0)
+      throw new IllegalArgumentException("l2Strength must be non-negative: " + l2Strength);
+    initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength);
     initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength);
   }
 
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adam.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adam.java
similarity index 100%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adam.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adam.java
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adamax.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adamax.java
similarity index 100%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Adamax.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adamax.java
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Ftrl.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Ftrl.java
similarity index 87%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Ftrl.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Ftrl.java
index aec7af8d6c9..db73f60c77e 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Ftrl.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Ftrl.java
@@ -31,7 +31,7 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TType;
 
-/** Ftrl Optimizer that implements the FTRL algorithm. */
+/** Ftrl (Follow the Regularized Leader) Optimizer that implements the FTRL algorithm. */
 public class Ftrl extends org.tensorflow.framework.optimizers.Optimizer
     implements OptimizerInterface {
 
@@ -140,11 +140,15 @@ public Ftrl(Ops tf, String name, float learningRate) {
    *
    * @param tf the TensorFlow Ops
    * @param learningRate the learning rate
-   * @param learningRatePower
-   * @param initialAccumulatorValue
-   * @param l1Strength
-   * @param l2Strength
-   * @param l2ShrinkageRegularizationStrength
+   * @param learningRatePower Controls how the learning rate decreases during training. Use zero for
+   *     a fixed learning rate.
+   * @param initialAccumulatorValue The starting value for accumulators. Only zero or positive
+   *     values are allowed.
+   * @param l1Strength the L1 Regularization strength, must be greater than or equal to zero.
+   * @param l2Strength the L2 Regularization strength, must be greater than or equal to zero.
+   * @param l2ShrinkageRegularizationStrength This differs from L2 above in that the L2 above is a
+   *     stabilization penalty, whereas this L2 shrinkage is a magnitude penalty. must be greater
+   *     than or equal to zero.
    */
   public Ftrl(
       Ops tf,
@@ -170,13 +174,17 @@ public Ftrl(
    * Create a Ftrl Optimizer
    *
    * @param tf the TensorFlow Ops
-   * @param name the Optmizer name
+   * @param name the name of this Ftrl Optimizer
    * @param learningRate the learning rate
-   * @param learningRatePower
-   * @param initialAccumulatorValue
-   * @param l1Strength
-   * @param l2Strength
-   * @param l2ShrinkageRegularizationStrength
+   * @param learningRatePower Controls how the learning rate decreases during training. Use zero for
+   *     a fixed learning rate.
+   * @param initialAccumulatorValue The starting value for accumulators. Only zero or positive
+   *     values are allowed.
+   * @param l1Strength the L1 Regularization strength, must be greater than or equal to zero.
+   * @param l2Strength the L2 Regularization strength, must be greater than or equal to zero.
+   * @param l2ShrinkageRegularizationStrength This differs from L2 above in that the L2 above is a
+   *     stabilization penalty, whereas this L2 shrinkage is a magnitude penalty. must be greater
+   *     than or equal to zero.
    */
   public Ftrl(
       Ops tf,
@@ -199,8 +207,6 @@ public Ftrl(
     initConfig();
   }
 
-
-
   /**
    * Create a Ftrl Optmizer
    *
@@ -325,7 +331,7 @@ protected  Op applyDense(Output gradient, Output variable
         accumSlot, // accum
         linearSlot, // linear
         gradient, // gradient
-            tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), // lr
+        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), // lr
         tf.dtypes.cast(tf.constant(l1RegularizationStrength), gradient.dataType()), // l1
         tf.dtypes.cast(tf.constant(l2RegularizationStrength), gradient.dataType()), // l2
         tf.dtypes.cast(
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/OptimizerInterface.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/OptimizerInterface.java
similarity index 76%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/OptimizerInterface.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/OptimizerInterface.java
index 9e3223deb80..0074ecb0f0a 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/OptimizerInterface.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/OptimizerInterface.java
@@ -22,17 +22,19 @@
 public interface OptimizerInterface {
 
   /** The value for the name key in the Config object */
-  public static final String NAME_KEY = "name";
+  String NAME_KEY = "name";
 
   /**
    * Get a TensorFlow Graph from the Ops.
    *
    * @param tf the TensorFlow Ops
    * @return the graph
-   * @throws java.lang.AssertionError if the TensorFlow Ops does not represent Graph mode
+   * @throws java.lang.IllegalArgumentException if the TensorFlow Ops does not represent Graph mode
    */
-  public static Graph assertGraph(Ops tf) {
-    assert tf.scope().env().isGraph() : "Optimizers can only be used in Graph Mode";
+  static Graph assertGraph(Ops tf) {
+    if(!tf.scope().env().isGraph()) {
+      throw new IllegalArgumentException("Invalid environment, Optimizers can only be used in Graph Mode");
+    }
     return (Graph) tf.scope().env();
   }
 
@@ -41,19 +43,19 @@ public static Graph assertGraph(Ops tf) {
    *
    * @return the config object used to initialize the Optimizer
    */
-  public Map getConfig();
+  Map getConfig();
 
   /**
    * Return the current learning rate
    *
    * @return the current learning rate
    */
-  public float getLearningRate();
+  float getLearningRate();
 
   /**
    * Set the learning rate
    *
    * @param learningRate the learning rate;
    */
-  public void setLearningRate(float learningRate);
+  void setLearningRate(float learningRate);
 }
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Optimizers.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Optimizers.java
similarity index 80%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Optimizers.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Optimizers.java
index 3892e239dad..1facb307b38 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/Optimizers.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Optimizers.java
@@ -41,15 +41,15 @@ public class Optimizers {
   static Map> map =
       new HashMap>() {
         {
-          put("adadelta", tf -> new AdaDelta(tf));
-          put("adagrad", tf -> new AdaGrad(tf));
-          put("adagrad-da", tf -> new AdaGradDA(tf));
-          put("adam", tf -> new Adam(tf));
-          put("adamax", tf -> new Adamax(tf));
-          put("ftrl", tf -> new Ftrl(tf));
-          put("nadam", tf -> new Nadam(tf));
-          put("rmsprop", tf -> new RMSProp(tf));
-          put("sgd", tf -> new SGD(tf));
+          put("adadelta", AdaDelta::new);
+          put("adagrad", AdaGrad::new);
+          put("adagrad-da", AdaGradDA::new);
+          put("adam", Adam::new);
+          put("adamax", Adamax::new);
+          put("ftrl", Ftrl::new);
+          put("nadam", Nadam::new);
+          put("rmsprop", RMSProp::new);
+          put("sgd", SGD::new);
         }
       };
 
@@ -65,9 +65,9 @@ public static Optimizer get(Ops tf, Object optimizerFunction) {
   }
 
   /**
-   * Get an Initializer
+   * Get an Optimizer
    *
-   * @param si a lamda function
+   * @param func a lamda function that returns the Optimizer
    * @return the Intializer object
    */
   public static Optimizer get(Ops tf, Function func) {
@@ -75,10 +75,11 @@ public static Optimizer get(Ops tf, Function func) {
   }
 
   /**
-   * Get an Initializer
+   * Get an Optimizer
    *
-   * @param optimizerFunction
-   * @param custom_functions a map of Initializer lambdas that will be queried if the Optimizer is
+   * @param optimizerFunction either a String that identifies the Optimizer, an Optimizer class, or
+   *     * an Optimizer object.
+   * @param custom_functions a map of Optimizer lambdas that will be queried if the Optimizer is
    *     not found in the standard keys
    * @return the Optimizer object
    */
@@ -95,10 +96,10 @@ public static Optimizer get(
         }
         return function != null ? function.apply(tf) : null;
       } else if (optimizerFunction instanceof Class) {
-        Class c = (Class) optimizerFunction; // do this for Java 8 rather than Pattern Matching for
-        // instanceof
+        // do this for Java 8 rather than Pattern Matching for instanceof
+        Class c = (Class) optimizerFunction;
         try {
-          Constructor ctor = c.getConstructor(Ops.class);
+          Constructor ctor = c.getConstructor(Ops.class);
           return (Optimizer) ctor.newInstance(tf);
         } catch (NoSuchMethodException
             | InstantiationException
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/RMSProp.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/RMSProp.java
similarity index 100%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/RMSProp.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/RMSProp.java
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/SGD.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/SGD.java
similarity index 96%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/SGD.java
rename to tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/SGD.java
index 2faf777b4ad..f89682f6820 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizer/SGD.java
+++ b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/SGD.java
@@ -16,7 +16,6 @@
 
 import java.util.HashMap;
 import java.util.Map;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
 import org.tensorflow.op.Ops;
 
@@ -103,7 +102,8 @@ public SGD(Ops tf, String name, float learningRate, float momentum) {
    */
   public SGD(Ops tf, float learningRate, float momentum, boolean useNesterov) {
     super(assertGraph(tf), learningRate, momentum, useNesterov);
-    assert momentum >= 0.0F && momentum <= 1.0F : "\"momentum\" must be between [0, 1].";
+    if(momentum < 0 || momentum > 1)
+      throw new IllegalArgumentException("\"momentum\" must be between [0, 1].");
     initConfig(learningRate, momentum, useNesterov);
   }
 
@@ -119,7 +119,8 @@ public SGD(Ops tf, float learningRate, float momentum, boolean useNesterov) {
    */
   public SGD(Ops tf, String name, float learningRate, float momentum, boolean useNesterov) {
     super(assertGraph(tf), name, learningRate, momentum, useNesterov);
-    assert momentum >= 0.0F && momentum <= 1.0F : "\"momentum\" must be between [0, 1].";
+    if(momentum < 0 || momentum > 1)
+      throw new IllegalArgumentException("\"momentum\" must be between [0, 1].");
     initConfig(learningRate, momentum, useNesterov);
   }
 

From d37298a6b9dcb206cdff985b96e340f7f93a075c Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 13:06:58 -0400
Subject: [PATCH 14/33] Moved back to tests

---
 .../java/org/tensorflow/keras/utils/ND.java   | 29 +++++++++++--------
 1 file changed, 17 insertions(+), 12 deletions(-)
 rename tensorflow-keras/src/{main => test}/java/org/tensorflow/keras/utils/ND.java (95%)

diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ND.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/ND.java
similarity index 95%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ND.java
rename to tensorflow-keras/src/test/java/org/tensorflow/keras/utils/ND.java
index f04ed7bcd70..2855af5af25 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ND.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/ND.java
@@ -126,7 +126,8 @@ public static FloatNdArray square(FloatNdArray a) {
    * @return the resulting array from the add operation
    */
   public static FloatNdArray add(FloatNdArray a, FloatNdArray b) {
-    assert (a.shape().size() == b.shape().size());
+    if(a.shape().size() != b.shape().size())
+      throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -175,7 +176,8 @@ public static FloatNdArray add(float scalar, FloatNdArray a) {
    * @return the resulting array from the subtraction operation
    */
   public static FloatNdArray sub(FloatNdArray a, FloatNdArray b) {
-    assert (a.shape().size() == b.shape().size());
+    if(a.shape().size() != b.shape().size())
+      throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -230,9 +232,9 @@ public static FloatNdArray sub(float scalar, FloatNdArray a) {
    * @return the resulting array from the muliply operation
    */
   public static FloatNdArray mul(FloatNdArray a, FloatNdArray b) {
-    assert a.shape().equals(b.shape())
-        : String.format(
-            "ValueError: operands do not have same shapes %s %s ", a.shape(), b.shape());
+    if(!a.shape().equals(b.shape()))
+        throw new IllegalArgumentException(String.format(
+            "ValueError: operands do not have same shapes %s %s ", a.shape(), b.shape()));
     boolean sameSize = a.shape().size() == b.shape().size();
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
@@ -287,7 +289,8 @@ public static FloatNdArray mul(float scalar, FloatNdArray a) {
    * @return the resulting array from the Divide operation
    */
   public static FloatNdArray div(FloatNdArray a, FloatNdArray b) {
-    assert (a.shape().size() == b.shape().size());
+    if(a.shape().size() != b.shape().size())
+      throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -306,7 +309,8 @@ public static FloatNdArray div(FloatNdArray a, FloatNdArray b) {
    * @return the resulting array from the Divide operation
    */
   public static FloatNdArray div(FloatNdArray a, float scalar) {
-    assert (scalar != 0);
+    if(scalar == 0)
+      throw new IllegalArgumentException("Cannot divide by zero");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -344,7 +348,8 @@ public static FloatNdArray div(float scalar, FloatNdArray a) {
    * @return the array result of the power operation
    */
   public static FloatNdArray pow(FloatNdArray a, FloatNdArray b) {
-    assert (a.shape().size() == b.shape().size());
+    if(a.shape().size() != b.shape().size())
+      throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -363,7 +368,6 @@ public static FloatNdArray pow(FloatNdArray a, FloatNdArray b) {
    * @return the array result of the power operation
    */
   public static FloatNdArray pow(FloatNdArray a, float scalar) {
-    assert (scalar != 0);
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -382,7 +386,6 @@ public static FloatNdArray pow(FloatNdArray a, float scalar) {
    * @return the array result of the power operation
    */
   public static FloatNdArray pow(float scalar, FloatNdArray a) {
-    assert (scalar != 0);
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -444,7 +447,8 @@ public static float min(FloatNdArray a) {
    * @throws java.lang.AssertionError if the two arrays are not the same size.
    */
   public static FloatNdArray max(FloatNdArray a, FloatNdArray b) {
-    assert (a.shape().size() == b.shape().size());
+    if(a.shape().size() != b.shape().size())
+      throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -495,7 +499,8 @@ public static FloatNdArray max(float scalar, FloatNdArray a) {
    * @throws java.lang.AssertionError if the two arrays are not the same size.
    */
   public static FloatNdArray min(FloatNdArray a, FloatNdArray b) {
-    assert (a.shape().size() == b.shape().size());
+    if(a.shape().size() != b.shape().size())
+      throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)

From c68812cc9c8815b0ea186f273748078c4907fbaa Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 13:08:44 -0400
Subject: [PATCH 15/33] Moved SoftmaxCrossEntropyWithLogits.java and
 SparseSoftmaxCrossEntropyWithLogits.java to nn.raw, added new versions of
 these to NnOps

---
 .../annotations/org/tensorflow/op/NnOps.java  | 139 ++++++++++++++----
 1 file changed, 108 insertions(+), 31 deletions(-)

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 0c76b961cf4..a0910d4be33 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
@@ -20,6 +20,7 @@
 import java.util.List;
 import org.tensorflow.DataType;
 import org.tensorflow.Operand;
+import org.tensorflow.op.core.NN;
 import org.tensorflow.op.nn.AvgPool;
 import org.tensorflow.op.nn.AvgPool3d;
 import org.tensorflow.op.nn.AvgPool3dGrad;
@@ -84,11 +85,9 @@
 import org.tensorflow.op.nn.Relu6;
 import org.tensorflow.op.nn.Selu;
 import org.tensorflow.op.nn.Softmax;
-import org.tensorflow.op.nn.SoftmaxCrossEntropyWithLogits;
 import org.tensorflow.op.nn.Softsign;
 import org.tensorflow.op.nn.SpaceToBatch;
 import org.tensorflow.op.nn.SpaceToDepth;
-import org.tensorflow.op.nn.SparseSoftmaxCrossEntropyWithLogits;
 import org.tensorflow.op.nn.TopK;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
@@ -102,10 +101,16 @@
  * @see {@link Ops}
  */
 public final class NnOps {
+  public final NnRawOps raw;
+
+  public final NnInternalOps internal;
+
   private final Scope scope;
 
   NnOps(Scope scope) {
     this.scope = scope;
+    raw = new NnRawOps(scope);
+    internal = new NnInternalOps(scope);
   }
 
   /**
@@ -1753,6 +1758,52 @@ public  Selu selu(Operand features) {
     return Selu.create(scope, features);
   }
 
+  /**
+   * Computes sigmoid cross entropy given `logits`.
+   *
+   *  
Measures the probability error in discrete classification tasks in which each class is
+   *  independent and not mutually exclusive. For instance, one could perform multilabel
+   *  classification where a picture can contain both an elephant and a dog at the same time.
+   *
+   *  
For brevity, let `x = logits`, `z = labels`. The logistic loss is
+   *
+   *  
+   *      z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
+   *      = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
+   *      = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
+   *      = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
+   *      = (1 - z) * x + log(1 + exp(-x))
+   *      = x - x * z + log(1 + exp(-x))
+   *  

+   *
+   *  
For x < 0, to avoid overflow in exp(-x), we reformulate the above
+   *
+   *  
+   *       x - x * z + log(1 + exp(-x))
+   *       = log(exp(x)) - x * z + log(1 + exp(-x))
+   *       = - x * z + log(1 + exp(x))
+   *  

+   *
+   *  
Hence, to ensure stability and avoid overflow, the implementation uses this equivalent
+   *  formulation
+   *
+   *  
+   *      max(x, 0) - x * z + log(1 + exp(-abs(x)))
+   *  

+   *
+   *  
`logits` and `labels` must have the same type and shape.
+   *
+   * @param scope The TensorFlow scope
+   * @param labels the labels
+   * @param logits the logits of type float32 or float64
+   * @param  the type of labels and logits
+   * @return the component-wise logistic losses.
+   */
+  public  Operand sigmoidCrossEntropyWithLogits(Operand labels,
+      Operand logits) {
+    return NN.sigmoidCrossEntropyWithLogits(scope, labels, logits);
+  }
+
   /**
    * Computes softmax activations.
    *  

@@ -1769,20 +1820,48 @@ public  Softmax softmax(Operand logits) {
   }
 
   /**
-   * Computes softmax cross entropy cost and gradients to backpropagate.
-   *  

-   *  Inputs are the logits, not probabilities.
+   * Computes softmax cross entropy between `logits` and `labels`.
    *
-   * @param  data type for {@code loss()} output
-   * @param features batch_size x num_classes matrix
-   * @param labels batch_size x num_classes matrix
-   *  The caller must ensure that each batch of labels represents a valid
-   *  probability distribution.
-   * @return a new instance of SoftmaxCrossEntropyWithLogits
+   *  
Measures the probability error in discrete classification tasks in which the classes are
+   *  mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is
+   *  labeled with one and only one label: an image can be a dog or a truck, but not both.
+   *
+   *  
**NOTE:** While the classes are mutually exclusive, their probabilities need not be. All
+   *  that is required is that each row of `labels` is a valid probability distribution. If they are
+   *  not, the computation of the gradient will be incorrect.
+   *
+   *  
If using exclusive `labels` (wherein one and only one class is true at a time), see
+   *  `sparse_softmax_cross_entropy_with_logits`.
+   *
+   *  
Usage:
+   *
+   *  
+   *    >>> logits = [[4.0, 2.0, 1.0], [0.0, 5.0, 1.0]]
+   *    >>> labels = [[1.0, 0.0, 0.0], [0.0, 0.8, 0.2]]
+   *    >>> tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits)
+   *    
+   *  

+   *
+   *  
Backpropagation will happen into both `logits` and `labels`. To disallow backpropagation
+   *  into `labels`, pass label tensors through `tf.stop_gradient` before feeding it to this
+   *  function.
+   *
+   * @param scope current scope
+   * @param labels Each vector along the class dimension should hold a valid probability
+   *      distribution e.g. for the case in which labels are of shape `[batch_size, num_classes]`,
+   *      each row of `labels[i]` must be a valid probability distribution.
+   * @param logits Per-label activations, typically a linear output. These activation energies are
+   *      interpreted as unnormalized log probabilities.
+   * @param axis The class dimension. -1 is the last dimension.
+   * @param  the data type of the logits
+   * @param  the number type of the operands
+   * @return the softmax cross entropy loss. Its type is the same as `logits` and its shape is the
+   *      same as `labels` except that it does not have the last dimension of `labels`.
    */
-  public  SoftmaxCrossEntropyWithLogits softmaxCrossEntropyWithLogits(
-      Operand features, Operand labels) {
-    return SoftmaxCrossEntropyWithLogits.create(scope, features, labels);
+  public  Operand softmaxCrossEntropyWithLogits(
+      Operand labels, Operand logits, int axis) {
+    return NN.softmaxCrossEntropyWithLogits(scope, labels, logits, axis);
   }
 
   /**
@@ -1974,24 +2053,22 @@ public  SpaceToDepth spaceToDepth(Operand input, Long blo
   }
 
   /**
-   * Computes softmax cross entropy cost and gradients to backpropagate.
-   *  

-   *  Unlike `SoftmaxCrossEntropyWithLogits`, this operation does not accept
-   *  a matrix of label probabilities, but rather a single label per row
-   *  of features.  This label is considered to have probability 1.0 for the
-   *  given row.
-   *  

-   *  Inputs are the logits, not probabilities.
+   * Computes sparse softmax cross entropy between `logits` and `labels`.
    *
-   * @param  data type for {@code loss()} output
-   * @param features batch_size x num_classes matrix
-   * @param labels batch_size vector with values in [0, num_classes).
-   *  This is the label for the given minibatch entry.
-   * @return a new instance of SparseSoftmaxCrossEntropyWithLogits
-   */
-  public  SparseSoftmaxCrossEntropyWithLogits sparseSoftmaxCrossEntropyWithLogits(
-      Operand features, Operand labels) {
-    return SparseSoftmaxCrossEntropyWithLogits.create(scope, features, labels);
+   * @param scope current scope
+   * @param labels `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of `labels` and
+   *      result) and dtype `int32` or `int64`. Each entry in `labels` must be an index in `[0,
+   *      num_classes)`. Other values will raise an exception when this op is run on CPU, and return
+   *      `NaN` for corresponding loss and gradient rows on GPU.
+   * @param logits Per-label activations (typically a linear output) of shape `[d_0, d_1, ...,
+   *      d_{r-1}, num_classes]` and dtype `float16`, `float32`, or `float64`. These activation
+   *      energies are interpreted as unnormalized log probabilities.
+   * @return A `Tensor` of the same shape as `labels` and of the same type as `logits` with the
+   *      softmax cross entropy loss.
+   */
+  public  Operand sparseSoftmaxCrossEntropyWithLogits(
+      Operand labels, Operand logits) {
+    return NN.sparseSoftmaxCrossEntropyWithLogits(scope, labels, logits);
   }
 
   /**

From 6b8eb26edafc54a70d6c5a1bd9e21cacf3ac04e7 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 13:50:01 -0400
Subject: [PATCH 16/33] Deleted files that are not necessary yet

---
 .../op/nn/SoftmaxCrossEntropyWithLogits.java  |  83 --
 .../SparseSoftmaxCrossEntropyWithLogits.java  |  87 ---
 .../java/org/tensorflow/keras/backend/K.java  | 713 ------------------
 .../keras/backend/tf/ConfusionMatrix.java     | 193 -----
 .../keras/backend/tf/ControlDependencies.java |  84 ---
 .../org/tensorflow/keras/backend/tf/NN.java   | 134 ----
 .../keras/backend/tf/SparseTensor.java        |  64 --
 .../tensorflow/keras/backend/tf/Tuple.java    | 109 ---
 .../keras/backend/tf/WeightsBroadcastOps.java | 158 ----
 .../keras/utils/PlaceholderStringFormat.java  |  81 --
 .../tensorflow/keras/utils/PrintUtils.java    | 152 ----
 .../tensorflow/keras/utils/ProgressBar.java   | 311 --------
 .../tensorflow/keras/utils/ShapeUtils.java    | 110 ---
 .../org/tensorflow/keras/utils/SmartCond.java | 107 ---
 .../tensorflow/keras/utils/SymbolicShape.java |  92 ---
 .../keras/utils/SymbolicShapeDict.java        |  58 --
 .../org/tensorflow/keras/utils/TypeUtils.java |  98 ---
 .../tensorflow/keras/utils/SmartCondTest.java | 247 ------
 .../tensorflow/keras/utils/TypeUtilTest.java  | 234 ------
 19 files changed, 3115 deletions(-)
 delete mode 100644 tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
 delete mode 100644 tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java
 delete mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java
 delete mode 100644 tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java

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
deleted file mode 100644
index 41281b996ff..00000000000
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
+++ /dev/null
@@ -1,83 +0,0 @@
-/* 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.
-=======================================================================*/
-
-// This class has been generated, DO NOT EDIT!
-
-package org.tensorflow.op.nn;
-
-import org.tensorflow.Operand;
-import org.tensorflow.Operation;
-import org.tensorflow.OperationBuilder;
-import org.tensorflow.Output;
-import org.tensorflow.op.RawOp;
-import org.tensorflow.op.Scope;
-import org.tensorflow.op.annotation.Endpoint;
-import org.tensorflow.op.annotation.Operator;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
-
-/**
- * Computes softmax cross entropy cost and gradients to backpropagate.
- * 

- * Inputs are the logits, not probabilities.
- * 
- * @param  data type for {@code loss()} output
- */
-@Operator(group = "nn")
-public final class SoftmaxCrossEntropyWithLogits extends RawOp {
-  
-  /**
-   * Factory method to create a class wrapping a new SoftmaxCrossEntropyWithLogits operation.
-   * 
-   * @param scope current scope
-   * @param features batch_size x num_classes matrix
-   * @param labels batch_size x num_classes matrix
-   * The caller must ensure that each batch of labels represents a valid
-   * probability distribution.
-   * @return a new instance of SoftmaxCrossEntropyWithLogits
-   */
-  @Endpoint(describeByClass = true)
-  public static  SoftmaxCrossEntropyWithLogits create(Scope scope, Operand features, Operand labels) {
-    OperationBuilder opBuilder = scope.env().opBuilder("SoftmaxCrossEntropyWithLogits", scope.makeOpName("SoftmaxCrossEntropyWithLogits"));
-    opBuilder.addInput(features.asOutput());
-    opBuilder.addInput(labels.asOutput());
-    opBuilder = scope.applyControlDependencies(opBuilder);
-    return new SoftmaxCrossEntropyWithLogits(opBuilder.build());
-  }
-  
-  /**
-   * Per example loss (batch_size vector).
-   */
-  public Output loss() {
-    return loss;
-  }
-  
-  /**
-   * backpropagated gradients (batch_size x num_classes matrix).
-   */
-  public Output backprop() {
-    return backprop;
-  }
-  
-  private Output loss;
-  private Output backprop;
-  
-  private SoftmaxCrossEntropyWithLogits(Operation operation) {
-    super(operation);
-    int outputIdx = 0;
-    loss = operation.output(outputIdx++);
-    backprop = operation.output(outputIdx++);
-  }
-}
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
deleted file mode 100644
index f2434cd4eb8..00000000000
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
+++ /dev/null
@@ -1,87 +0,0 @@
-/* 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.
-=======================================================================*/
-
-// This class has been generated, DO NOT EDIT!
-
-package org.tensorflow.op.nn;
-
-import org.tensorflow.Operand;
-import org.tensorflow.Operation;
-import org.tensorflow.OperationBuilder;
-import org.tensorflow.Output;
-import org.tensorflow.op.RawOp;
-import org.tensorflow.op.Scope;
-import org.tensorflow.op.annotation.Endpoint;
-import org.tensorflow.op.annotation.Operator;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
-
-/**
- * Computes softmax cross entropy cost and gradients to backpropagate.
- * 

- * Unlike `SoftmaxCrossEntropyWithLogits`, this operation does not accept
- * a matrix of label probabilities, but rather a single label per row
- * of features.  This label is considered to have probability 1.0 for the
- * given row.
- * 

- * Inputs are the logits, not probabilities.
- * 
- * @param  data type for {@code loss()} output
- */
-@Operator(group = "nn")
-public final class SparseSoftmaxCrossEntropyWithLogits extends RawOp {
-  
-  /**
-   * Factory method to create a class wrapping a new SparseSoftmaxCrossEntropyWithLogits operation.
-   * 
-   * @param scope current scope
-   * @param features batch_size x num_classes matrix
-   * @param labels batch_size vector with values in [0, num_classes).
-   * This is the label for the given minibatch entry.
-   * @return a new instance of SparseSoftmaxCrossEntropyWithLogits
-   */
-  @Endpoint(describeByClass = true)
-  public static  SparseSoftmaxCrossEntropyWithLogits create(Scope scope, Operand features, Operand labels) {
-    OperationBuilder opBuilder = scope.env().opBuilder("SparseSoftmaxCrossEntropyWithLogits", scope.makeOpName("SparseSoftmaxCrossEntropyWithLogits"));
-    opBuilder.addInput(features.asOutput());
-    opBuilder.addInput(labels.asOutput());
-    opBuilder = scope.applyControlDependencies(opBuilder);
-    return new SparseSoftmaxCrossEntropyWithLogits(opBuilder.build());
-  }
-  
-  /**
-   * Per example loss (batch_size vector).
-   */
-  public Output loss() {
-    return loss;
-  }
-  
-  /**
-   * backpropagated gradients (batch_size x num_classes matrix).
-   */
-  public Output backprop() {
-    return backprop;
-  }
-  
-  private Output loss;
-  private Output backprop;
-  
-  private SparseSoftmaxCrossEntropyWithLogits(Operation operation) {
-    super(operation);
-    int outputIdx = 0;
-    loss = operation.output(outputIdx++);
-    backprop = operation.output(outputIdx++);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java
deleted file mode 100644
index 51a5fdaa5ff..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/K.java
+++ /dev/null
@@ -1,713 +0,0 @@
-/* Copyright 2020 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.keras.backend;
-
-import java.util.Arrays;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.function.Function;
-import org.tensorflow.DataType;
-import org.tensorflow.EagerSession;
-import org.tensorflow.ExecutionEnvironment;
-import org.tensorflow.Graph;
-import org.tensorflow.Operand;
-import org.tensorflow.Session;
-import org.tensorflow.Tensor;
-import org.tensorflow.keras.backend.tf.ConfusionMatrix;
-import org.tensorflow.keras.backend.tf.NN;
-import org.tensorflow.keras.backend.tf.Tuple;
-import org.tensorflow.ndarray.NdArraySequence;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.Ops;
-import org.tensorflow.op.core.ReduceSum;
-import org.tensorflow.op.core.Squeeze;
-import org.tensorflow.op.core.Variable;
-import org.tensorflow.op.math.Mean;
-import org.tensorflow.op.nn.SoftmaxCrossEntropyWithLogits;
-import org.tensorflow.types.TBfloat16;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat16;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TUint8;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
-
-/** Keras backend methods */
-public class K {
-
-  public static final double Epsilon = 1e-7;
-  public static final float EpsilonF = 1e-7F;
-
-  public static final double epsilon() {
-    return Epsilon;
-  }
-
-  public static final Operand epsilonConstant(Ops tf) {
-    return tf.constant(Epsilon);
-  }
-
-  public static final Operand epsilonConstant(Ops tf, DataType dtype) {
-    return tf.dtypes.cast(tf.constant(Epsilon), dtype);
-  }
-
-  public static final Operand one(Ops tf) {
-    return tf.constant(1);
-  }
-
-  public static final Operand one(Ops tf, DataType dtype) {
-    return tf.dtypes.cast(tf.constant(1), dtype);
-  }
-
-  public static final Operand minusOne(Ops tf) {
-    return tf.constant(-1);
-  }
-
-  public static final Operand minusOne(Ops tf, DataType dtype) {
-    return tf.dtypes.cast(tf.constant(-1), dtype);
-  }
-
-  public static final Operand zero(Ops tf) {
-    return tf.constant(0);
-  }
-
-  public static final Operand zero(Ops tf, DataType dtype) {
-    return tf.dtypes.cast(tf.constant(0), dtype);
-  }
-
-  public static final Operand constant(Ops tf, double number, DataType dtype) {
-    return tf.dtypes.cast(tf.constant(number), dtype);
-  }
-
-  public static Operand clip(Ops tf, Operand x, double minValue, double maxValue) {
-    assert x != null : "Operand x must not be null";
-    DataType dtype = x.asOutput().dataType();
-    if (maxValue < minValue) {
-      double tmp = maxValue;
-      maxValue = minValue;
-      minValue = tmp;
-    }
-    Operand minValueConstant = tf.dtypes.cast(tf.constant(minValue), dtype);
-    Operand maxValueConstant = tf.dtypes.cast(tf.constant(maxValue), dtype);
-    return tf.clipByValue(x, minValueConstant, maxValueConstant);
-  }
-
-  public static Operand mean(Ops tf, Operand x) {
-    return mean(tf, x, null, false);
-  }
-
-  public static Operand mean(Ops tf, Operand x, Operand axis) {
-    return mean(tf, x, axis, false);
-  }
-
-  public static Operand mean(Ops tf, Operand x, boolean keepDims) {
-    return mean(tf, x, null, keepDims);
-  }
-
-  public static Operand mean(Ops tf, Operand x, Operand axis, boolean keepDims) {
-    if (x.asOutput().dataType() == TBool.DTYPE) {
-      x = tf.dtypes.cast(x, TFloat32.DTYPE);
-    }
-    if (axis == null) {
-      axis = allAxis(tf, x);
-    }
-    return tf.math.mean(x, axis, Mean.keepDims(keepDims));
-  }
-
-  // alias for mean
-  public static Operand reduceMean(Ops tf, Operand x, Operand axis, boolean keepDims) {
-    return mean(tf, x, axis, keepDims);
-  }
-
-  public static Operand maximum(Ops tf, Operand x, Operand y) {
-    y = tf.dtypes.cast(y, x.asOutput().dataType());
-    return tf.math.maximum(x, y);
-  }
-
-  public static  Operand sqrt(Ops tf, Operand x) {
-    DataType dType = x.asOutput().dataType();
-    Operand zero = tf.dtypes.cast(tf.constant(0), dType);
-    Operand inf = tf.dtypes.cast(tf.constant(Float.POSITIVE_INFINITY), dType);
-    x = tf.clipByValue(x, zero, inf);
-    return tf.math.sqrt(x);
-  }
-
-  public static Shape merge(Shape a, Shape b) {
-    assert a.numDimensions() == b.numDimensions()
-        : String.format("Shapes %s and %s are incompatible", a, b);
-    long[] array = new long[a.numDimensions()];
-    for (int i = 0; i < a.numDimensions(); i++) {
-      if (a.size(i) != Shape.UNKNOWN_SIZE) {
-        if (b.size(i) != Shape.UNKNOWN_SIZE) {
-          assert a.size(i) == b.size(i) : String.format("Shapes %s and %s are incompatible", a, b);
-        }
-        array[i] = a.size(i);
-      } else {
-        array[i] = b.size(i);
-      }
-    }
-    return Shape.of(array);
-  }
-
-  // this is from nn in Python, I could not find it in the Java frameworks.
-  public static Operand sigmoidCrossEntropyWithLogits(Ops tf, Operand labels, Operand logits) {
-    Shape lablesShape = labels.asOutput().shape();
-    Shape logitsShape = logits.asOutput().shape();
-    Shape newShape = merge(lablesShape, logitsShape);
-
-    Operand zeros = tf.dtypes.cast(tf.zerosLike(logits), logits.asOutput().dataType());
-    Operand cond = tf.math.greaterEqual(logits, zeros);
-
-    Operand relu_logits = tf.select(cond, logits, zeros);
-    Operand neg_abs_logits = tf.select(cond, tf.math.neg(logits), logits);
-    return tf.math.add(
-        tf.math.sub(relu_logits, tf.math.mul(logits, labels)),
-        tf.math.log1p(tf.math.exp(neg_abs_logits)));
-  }
-
-  // TODO need to walk back identity until it hits something else
-  // not sure how to get the input nodes for the Operand.
-  private static Operand backtrackIdentity(Operand output) {
-    // while(!output.op().type().equals("Identity"))
-    //    output = output.op().output(0);
-    return output;
-  }
-
-  public static Operand binary_crossentropy(
-      Ops tf, Operand target, Operand output, boolean fromLogits) {
-    if (fromLogits) {
-      return sigmoidCrossEntropyWithLogits(tf, target, output);
-    }
-
-    if (!(output instanceof Variable) && (!tf.scope().env().isEager())) {
-      // output = backtrackIdentity(output); // TODO - this does not work, goes infinite loop
-      if (output.op().type().equals("Sigmoid")) {
-        assert output.op().numOutputs() == 1;
-        output = output.op().output(0);
-        return sigmoidCrossEntropyWithLogits(tf, target, output);
-      }
-    }
-    DataType dtype = output.asOutput().dataType();
-    Operand one = one(tf, dtype);
-    Operand epsilonConst = K.epsilonConstant(tf, dtype);
-    Operand oneMinusEpsilonConst = tf.math.sub(one, epsilonConst);
-    output = tf.clipByValue(output, epsilonConst, oneMinusEpsilonConst);
-
-    // Compute cross entropy from probabilities.
-    Operand bce = tf.math.mul(target, tf.math.log(tf.math.add(output, epsilonConst)));
-    bce =
-        tf.math.add(
-            bce,
-            tf.math.mul(
-                tf.math.sub(one, target),
-                tf.math.log(tf.math.add(tf.math.sub(one, output), epsilonConst))));
-    Operand result = tf.math.neg(bce);
-    return result;
-  }
-
-  public static Operand categorical_crossentropy(
-      Ops tf, Operand target, Operand output, boolean fromLogits) {
-    return categorical_crossentropy(tf, target, output, fromLogits, -1);
-  }
-
-  public static Operand categorical_crossentropy(
-      Ops tf, Operand target, Operand output, boolean fromLogits, int axis) {
-
-    if (fromLogits) {
-      return softmax_cross_entropy_with_logits(tf, target, output);
-    }
-    if (!(output instanceof Variable) && (!tf.scope().env().isEager())) {
-      // TODO output = backtrackIdentity(output); doesn't seem to work with Java version.
-      if (output.op().type().equals("Softmax")) {
-        assert output.op().numOutputs() == 1;
-        output = output.op().output(0);
-        Operand op = softmax_cross_entropy_with_logits(tf, target, output);
-        return op;
-      }
-    }
-    DataType dtype = output.asOutput().dataType();
-    Operand one = one(tf, dtype);
-    Operand epsilonConst = K.epsilonConstant(tf, dtype);
-    Operand oneMinusepsilonConst = tf.math.sub(one, epsilonConst);
-    output =
-        tf.math.div(
-            output, tf.reduceSum(output, tf.constant(axis), ReduceSum.keepDims(Boolean.TRUE)));
-    output = tf.clipByValue(output, epsilonConst, oneMinusepsilonConst);
-
-    // Compute cross entropy from probabilities.
-    Operand cce =
-        tf.reduceSum(
-            tf.math.mul(target, tf.math.log(output)),
-            tf.constant(axis),
-            ReduceSum.keepDims(Boolean.FALSE));
-    return tf.math.neg(cce);
-  }
-
-  public static Operand flatten(Ops tf, Operand t) {
-    Shape shape = Shape.of(1L);
-    return tf.reshape(t, tf.constant(shape));
-  }
-
-  public static Operand sparse_categorical_crossentropy(
-      Ops tf, Operand target, Operand output, boolean fromLogits, int axis) {
-    DataType dType = output.asOutput().dataType();
-    if (!(output instanceof Variable) && (!tf.scope().env().isEager())) {
-      // TODO output = backtrackIdentity(output); doesn't seem to work with Java version.
-      if (output.op().type().equals("Softmax")) {
-        // assert output.op().numOutputs() == 1;
-        // When softmax activation function is used for output operation, we
-        // use logits from the softmax function directly to compute loss in order
-        // to prevent collapsing zero when training.
-        // TODO assert len(output.op.inputs) == 1
-        // TODO output = output.op.inputs[0]
-        fromLogits = true;
-      }
-    }
-    if (!fromLogits) {
-      Operand epsilonConst = epsilonConstant(tf, dType);
-      Operand one = one(tf, dType);
-      Operand oneMinusEpsilonConst = tf.math.sub(one, epsilonConst);
-      output = tf.clipByValue(output, epsilonConst, oneMinusEpsilonConst);
-      output = tf.math.log(output);
-    }
-    Shape outputShape = output.asOutput().shape();
-    int outputRank = outputShape.numDimensions();
-    axis %= outputRank;
-    if (axis < 0) {
-      axis += outputRank;
-    }
-    if (axis != outputRank - 1) {
-      int[] axisNew = moveAxisToEnd(axis, outputRank);
-      output = tf.linalg.transpose(output, tf.constant(axisNew));
-    }
-
-    target = tf.dtypes.cast(target, TInt64.DTYPE);
-    // TODO Try to adjust the shape so that rank of labels = rank of logits - 1.
-    outputShape = output.asOutput().shape();
-    Shape targetShape = target.asOutput().shape();
-    int targetRank = targetShape.numDimensions();
-
-    boolean updateShape = targetRank != outputRank - 1;
-    if (updateShape) { // TODO check to see if this is right
-      target = tf.reshape(target, tf.constant(-1L)); // flatten
-      output =
-          tf.reshape(
-              output,
-              tf.constant(new long[] {-1L, outputShape.size(outputShape.numDimensions() - 1)}));
-    }
-
-    // call nn.nn.sparse_softmax_cross_entropy_with_logits_v2
-    Operand loss = NN.sparse_softmax_cross_entropy_with_logits(tf, target, output);
-    if (updateShape && outputRank >= 3) {
-      long[] dims = outputShape.asArray();
-      long[] newDims = new long[dims.length - 1];
-      System.arraycopy(dims, 0, newDims, 0, newDims.length);
-      loss = tf.reshape(loss, tf.constant(newDims));
-    }
-    return loss;
-  }
-
-  private static int[] allAxis(Operand op) {
-    int rank = op.asOutput().shape().numDimensions();
-    int[] ranks = new int[rank];
-    for (int i = 0; i < rank; i++) {
-      ranks[i] = i;
-    }
-    return ranks;
-  }
-
-  public static Operand allAxis(Ops tf, Operand op) {
-    int[] ranks = allAxis(op);
-    return tf.constant(ranks);
-  }
-
-  // TODO shouldn't these be in tensorflow itself under nn?
-  private static  Operand moveDimToEnd(
-      Ops tf, Operand tensor, int dim_index, Operand rank) {
-    Operand one = one(tf, TInt32.DTYPE);
-    List> concatList =
-        Arrays.asList(
-            tf.range(tf.constant(dim_index), one, one),
-            tf.range(tf.constant(dim_index + 1), rank, one));
-    return tf.linalg.transpose(
-        tensor,
-        (Operand) tf.concat((Iterable>) concatList, (Operand) tf.constant(0)));
-  }
-
-  private static  Operand flattenOuterDims(
-      Ops tf, Operand logits) {
-    Operand zero = zero(tf, TInt64.DTYPE);
-    Operand one = one(tf, TInt64.DTYPE);
-    Operand minusOne = tf.constant(-1);
-
-    // Shape logitsShape = logits.asOutput().shape();
-    // long lastDimSize = logitsShape.size(logitsShape.numDimensions()-1);
-    // if(!tf.scope().env().isEager()) {
-    Shape shape = logits.asOutput().shape();
-    int ndims = shape.numDimensions();
-    if (!shape.hasUnknownDimension()) {
-      long product = 1L;
-      boolean productValid = true;
-      for (int i = ndims - 2; i >= 0; i--) {
-        long d = shape.size(i);
-        if (d == Shape.UNKNOWN_SIZE) {
-          productValid = false;
-          break;
-        }
-        product *= d;
-      }
-      if (productValid) {
-        Shape outputShape = Shape.of(product, shape.size(ndims - 1));
-        return tf.reshape(logits, tf.constant(outputShape.asArray()));
-      }
-    }
-    // }
-
-    Operand rank = tf.dtypes.cast(tf.rank(logits), TInt64.DTYPE);
-    Operand rankMinusOne = tf.math.sub(rank, one);
-
-    Operand last_dim_size = tf.slice(tf.shape(logits), rankMinusOne, tf.constant(1));
-    Operand concat =
-        tf.concat(Arrays.asList(tf.constant(new int[] {-1}), last_dim_size), tf.constant(0));
-    return tf.reshape(zero, concat);
-  }
-
-  private static int[] moveAxisToEnd(int axis, int outputRank) {
-    int[] axisNew = new int[outputRank];
-    for (int i = 0; i < axis; i++) {
-      axisNew[i] = i;
-    }
-    for (int i = axis + 1; i < outputRank; i++) {
-      axisNew[i - 1] = i;
-    }
-    axisNew[outputRank - 1] = axis;
-    return axisNew;
-  }
-
-  // TODO, maybe part of Shape ??
-  private static boolean shapeIsCompatible(Shape a, Shape b) {
-    if (a.numDimensions() != b.numDimensions()) {
-      return false;
-    }
-    for (int i = 0; i < a.numDimensions(); i++) {
-      long aSize = a.size(i);
-      long bSize = b.size(i);
-      if (aSize != Shape.UNKNOWN_SIZE && bSize != Shape.UNKNOWN_SIZE && aSize != bSize) {
-        return false;
-      }
-    }
-    return true;
-  }
-
-  // TODO these are "nn" ops
-  public static Operand softmax_cross_entropy_with_logits(Ops tf, Operand labels, Operand logits) {
-    return softmax_cross_entropy_with_logits(tf, labels, logits, -1);
-  }
-
-  public static Operand softmax_cross_entropy_with_logits(
-      Ops tf, Operand labels, Operand logits, int axis) {
-    axis = axis % logits.asOutput().shape().numDimensions();
-    if (axis < 0) {
-      axis += logits.asOutput().shape().numDimensions();
-    }
-
-    Operand minusOne = tf.constant(-1);
-    Operand precise_logits = logits;
-    Operand one = tf.constant(1L);
-
-    boolean convertToFloat32 =
-        logits.asOutput().dataType() == TFloat16.DTYPE
-            || logits.asOutput().dataType() == TBfloat16.DTYPE;
-    if (convertToFloat32) {
-      precise_logits = tf.dtypes.cast(logits, TFloat32.DTYPE);
-    }
-    DataType dtype = precise_logits.asOutput().dataType();
-    labels = tf.dtypes.cast(labels, dtype);
-    Operand inputRank = tf.dtypes.cast(tf.rank(precise_logits), TInt64.DTYPE);
-    Operand inputRankMinusOne = tf.dtypes.cast(tf.math.sub(inputRank, one), TInt64.DTYPE);
-    Shape shape = logits.asOutput().shape();
-
-    // Move the dim to the end if dim is not the last dimension.
-    if (axis != -1 && axis != precise_logits.asOutput().shape().numDimensions() - 1) {
-      precise_logits = moveDimToEnd(tf, precise_logits, axis, inputRank);
-      labels = moveDimToEnd(tf, labels, axis, inputRank);
-    }
-
-    Shape inputShape = precise_logits.asOutput().shape();
-    precise_logits = flattenOuterDims(tf, precise_logits);
-    labels = flattenOuterDims(tf, labels);
-    SoftmaxCrossEntropyWithLogits smax =
-        tf.nn.softmaxCrossEntropyWithLogits(precise_logits, labels);
-    Operand cost = smax.loss();
-    Operand outputShape =
-        tf.slice(
-            tf.constant(inputShape.asArray()),
-            tf.constant(new long[] {0}),
-            tf.constant(new long[] {inputShape.numDimensions() - 1}));
-    cost = tf.reshape(cost, outputShape);
-    if (tf.scope().env().isGraph() && !shape.hasUnknownDimension()) {
-      long[] array = shape.asArray();
-      long[] newArray = new long[array.length - 1];
-      if (axis < 0) {
-        axis = shape.numDimensions() + axis;
-      }
-      for (int i = 0; i < axis; i++) {
-        newArray[i] = shape.size(i);
-      }
-      for (int i = axis + 1; i < shape.numDimensions(); i++) {
-        newArray[i - 1] = shape.size(i);
-      }
-      Shape newShape = Shape.of(newArray);
-      cost = tf.reshape(cost, tf.constant(newShape.asArray()));
-    }
-
-    if (convertToFloat32) {
-      cost = tf.dtypes.cast(cost, logits.asOutput().dataType());
-    }
-    return cost;
-  }
-
-  public static  Operand map(
-      Operand input, Function, Operand> mapFunc) {
-    return null;
-  }
-
-  public static long[] concatenate(long first, long... remaining) {
-    long[] dims = new long[remaining.length + 1];
-    System.arraycopy(remaining, 0, dims, 1, remaining.length);
-    dims[0] = first;
-    return dims;
-  }
-
-  private static Map> uidMap = new HashMap<>();
-
-  /**
-   * Associates a string prefix with an integer counter in a TensorFlow graph.
-   *
-   * 
Example:
-   *
-   * 
-   * get_uid('dense')
-   * 1
-   * get_uid('dense')
-   * 2
-   * 

-   *
-   * @param tf the TensorFlow Ops
-   * @param prefix String prefix to index.
-   * @return Unique integer ID.
-   */
-  public static int getUid(Ops tf, String prefix) {
-    ExecutionEnvironment env = tf.scope().env();
-    Map uids = uidMap.get(env);
-    if (uids == null) {
-      uids = new HashMap<>();
-      uidMap.put(env, uids);
-    }
-    Integer id = uids.get(prefix);
-    if (id == null) {
-      id = 0;
-    } else {
-      id++;
-    }
-
-    uids.put(prefix, id);
-    return id;
-  }
-
-  /**
-   * returns the larger DataType between the two.
-   *
-   * @param a the first DataType to compare
-   * @param b the second DataType to compare
-   * @return the wider DataType
-   */
-  public DataType wider(DataType a, DataType b) {
-    return a.byteSize() < b.byteSize() ? b : a;
-  }
-
-  /**
-   * returns the smaller DataType between the two.
-   *
-   * @param a the first DataType to compare
-   * @param b the second DataType to compare
-   * @return the smaller DataType
-   */
-  public DataType narrower(DataType a, DataType b) {
-    return a.byteSize() > b.byteSize() ? b : a;
-  }
-
-  public  NdArraySequence getTensorValue(Ops tf, Operand operand) {
-    DataType dtype = operand.asOutput().dataType();
-    if (tf.scope().env().isGraph()) {
-      try (Session session = new Session((Graph) tf.scope().env())) {
-        if (dtype.equals(TInt32.DTYPE)) {
-          try (Tensor result =
-              session.runner().fetch(operand).run().get(0).expect(TInt32.DTYPE)) {
-            return result.data().scalars();
-          }
-        } else if (dtype.equals(TInt64.DTYPE)) {
-          try (Tensor result =
-              session.runner().fetch(operand).run().get(0).expect(TInt64.DTYPE)) {
-            return result.data().scalars();
-          }
-        } else if (dtype.equals(TUint8.DTYPE)) {
-          try (Tensor result =
-              session.runner().fetch(operand).run().get(0).expect(TUint8.DTYPE)) {
-            return result.data().scalars();
-          }
-        } else if (dtype.equals(TBfloat16.DTYPE)) {
-          try (Tensor result =
-              session.runner().fetch(operand).run().get(0).expect(TBfloat16.DTYPE)) {
-            return result.data().scalars();
-          }
-        } else if (dtype.equals(TFloat16.DTYPE)) {
-          try (Tensor result =
-              session.runner().fetch(operand).run().get(0).expect(TFloat16.DTYPE)) {
-            return result.data().scalars();
-          }
-        } else if (dtype.equals(TFloat32.DTYPE)) {
-          try (Tensor result =
-              session.runner().fetch(operand).run().get(0).expect(TFloat32.DTYPE)) {
-            return result.data().scalars();
-          }
-        } else if (dtype.equals(TFloat64.DTYPE)) {
-          try (Tensor result =
-              session.runner().fetch(operand).run().get(0).expect(TFloat64.DTYPE)) {
-            return result.data().scalars();
-          }
-        } else {
-          return null;
-        }
-      }
-    } else {
-      try (EagerSession session = EagerSession.create()) {
-        if (dtype.equals(TInt32.DTYPE)) {
-          return ((Operand) operand).data().scalars();
-        } else if (dtype.equals(TInt64.DTYPE)) {
-          return ((Operand) operand).data().scalars();
-        } else if (dtype.equals(TUint8.DTYPE)) {
-          return ((Operand) operand).data().scalars();
-        } else if (dtype.equals(TBfloat16.DTYPE)) {
-          return ((Operand) operand).data().scalars();
-        } else if (dtype.equals(TFloat16.DTYPE)) {
-          return ((Operand) operand).data().scalars();
-        } else if (dtype.equals(TFloat32.DTYPE)) {
-          return ((Operand) operand).data().scalars();
-        } else if (dtype.equals(TFloat64.DTYPE)) {
-          return ((Operand) operand).data().scalars();
-        } else {
-          return null;
-        }
-      }
-    }
-  }
-
-  /**
-   * Squeeze or expand last dimension if needed. 1. Squeezes last dim of `y_pred` or `y_true` if
-   * their rank differs by 1 (using `confusion_matrix.remove_squeezable_dimensions`). 2. Squeezes or
-   * expands last dim of `sample_weight` if its rank differs by 1 from the new rank of `y_pred`. If
-   * `sample_weight` is scalar, it is kept scalar.
-   *
-   * @param tf the TensorVlow Ops
-   * @param yPred Predicted values, a `Tensor` of arbitrary dimensions.
-   * @param yTrue Optional label `Tensor` whose dimensions match `y_pred`.
-   * @return Tuple of `y_pred`, `y_true` and `sample_weight`. Each of them possibly has the last
-   *     dimension squeezed, `sample_weight` could be extended by one dimension. If `sample_weight`
-   *     is null, (y_pred, y_true) is returned.
-   */
-  public static Tuple squeezeOrExpandDimensions(Ops tf, Operand yTrue, Operand yPred) {
-    return squeezeOrExpandDimensions(tf, yTrue, yPred, null);
-  }
-
-  /**
-   * Squeeze or expand last dimension if needed. 1. Squeezes last dim of `y_pred` or `y_true` if
-   * their rank differs by 1 (using `confusion_matrix.remove_squeezable_dimensions`). 2. Squeezes or
-   * expands last dim of `sample_weight` if its rank differs by 1 from the new rank of `y_pred`. If
-   * `sample_weight` is scalar, it is kept scalar.
-   *
-   * @param tf the TensorVlow Ops
-   * @param yPred Predicted values, a `Tensor` of arbitrary dimensions.
-   * @param yTrue Optional label `Tensor` whose dimensions match `y_pred`.
-   * @param sampleWeight Optional weight scalar or `Tensor` whose dimensions match `y_pred`.
-   * @return Tuple of `y_pred`, `y_true` and `sample_weight`. Each of them possibly has the last
-   *     dimension squeezed, `sample_weight` could be extended by one dimension. If `sample_weight`
-   *     is null, (y_pred, y_true) is returned.
-   */
-  public static Tuple squeezeOrExpandDimensions(
-      Ops tf, Operand yTrue, Operand yPred, Operand sampleWeight) {
-    Tuple tuple = new Tuple(yTrue, yPred);
-    Shape ypredShape = yPred.asOutput().shape();
-    long ypredRank = ypredShape.numDimensions();
-
-    if (yTrue != null) {
-      Shape ytrueShape = yTrue.asOutput().shape();
-      long ytrueRank = ytrueShape.numDimensions();
-      if (ytrueRank != Shape.UNKNOWN_SIZE && ypredRank != Shape.UNKNOWN_SIZE) {
-        // Use static rank for `y_true` and `y_pred`.
-        if (ypredRank - ytrueRank != 1 || ypredShape.size(-1) == 1) {
-          // y_true, y_pred = confusion_matrix.remove_squeezable_dimensions(y_true, y_pred)
-          tuple = ConfusionMatrix.removeSqueezableDimensions(tf, yTrue, yPred);
-        }
-      } else { // use dynamic rank
-        tuple = ConfusionMatrix.removeSqueezableDimensions(tf, yTrue, yPred);
-      }
-    }
-    if (sampleWeight == null) {
-      return tuple;
-    }
-    Shape weightsShape = sampleWeight.asOutput().shape();
-    long weightsRank = weightsShape.numDimensions();
-    if (weightsRank == 0) { // scalar
-      return new Tuple(yTrue, yPred, sampleWeight);
-    }
-
-    if (ypredRank != Shape.UNKNOWN_SIZE && weightsRank != Shape.UNKNOWN_SIZE) {
-
-      if (weightsRank - ypredRank == 1) {
-        sampleWeight = tf.squeeze(sampleWeight);
-      } else if (ypredRank - weightsRank == 1) {
-        sampleWeight = tf.expandDims(sampleWeight, tf.constant(-1L));
-      }
-      return new Tuple(yTrue, yPred, sampleWeight);
-    }
-    // Use dynamic rank.
-    Operand weightsRankTensor = tf.rank(sampleWeight);
-    Operand rankDiff = tf.math.sub(weightsRankTensor, tf.rank(yPred));
-    sampleWeight =
-        tf.select(
-            tf.math.equal(weightsRankTensor, tf.constant(0)),
-            sampleWeight,
-            maybeAdjustWeights(tf, sampleWeight, rankDiff));
-    return new Tuple(yTrue, yPred, sampleWeight);
-  }
-
-  private static Operand maybeAdjustWeights(Ops tf, Operand sampleWeight, Operand rankDiff) {
-    return tf.select(
-        tf.math.equal(rankDiff, tf.constant(1)),
-        tf.squeeze(sampleWeight, Squeeze.axis(Arrays.asList(-1L))),
-        maybeExpandWeights(tf, sampleWeight, rankDiff));
-  }
-
-  private static Operand maybeExpandWeights(Ops tf, Operand sampleWeight, Operand rankDiff) {
-    return tf.select(
-        tf.math.equal(rankDiff, tf.constant(-1)),
-        tf.expandDims(sampleWeight, tf.constant(-1)),
-        sampleWeight);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java
deleted file mode 100644
index 2860adb9d8b..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ConfusionMatrix.java
+++ /dev/null
@@ -1,193 +0,0 @@
-/* Copyright 2020 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.keras.backend.tf;
-
-import org.tensorflow.keras.backend.*;
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.List;
-import org.tensorflow.DataType;
-import org.tensorflow.Operand;
-import org.tensorflow.keras.utils.ShapeUtils;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-import org.tensorflow.op.core.Squeeze;
-import org.tensorflow.op.core.Stack;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
-
-/** ConfusionMatrix operations */
-public class ConfusionMatrix {
-
-  /**
-   * Squeeze last dim if ranks differ from expected by exactly 1.
-   *
-   * @param tf the TensorFlowOps
-   * @param labels Label values, a `Tensor` whose dimensions match `predictions`.
-   * @param predictions Predicted values, a `Tensor` of arbitrary dimensions.
-   * @return `labels` and `predictions`, possibly with last dim squeezed.
-   */
-  public static Tuple removeSqueezableDimensions(Ops tf, Operand labels, Operand predictions) {
-    return removeSqueezableDimensions(tf, labels, predictions, 0);
-  }
-
-  /**
-   * Squeeze last dim if ranks differ from expected by exactly 1.
-   *
-   * @param tf the TensorFlowOps
-   * @param labels Label values, a `Tensor` whose dimensions match `predictions`.
-   * @param predictions Predicted values, a `Tensor` of arbitrary dimensions.
-   * @param expectedRankDiff Expected result of `rank(predictions) - rank(labels)`.
-   * @return `labels` and `predictions`, possibly with last dim squeezed.
-   */
-  public static Tuple removeSqueezableDimensions(
-      Ops tf, Operand labels, Operand predictions, int expectedRankDiff) {
-
-    tf = tf.withSubScope("removeSqueezableDimensions");
-    Shape predictionsShape = predictions.asOutput().shape();
-    int predictionsRank = predictionsShape.numDimensions();
-    Shape labelsShape = labels.asOutput().shape();
-    int labelsRank = labelsShape.numDimensions();
-
-    if (predictionsRank != Shape.UNKNOWN_SIZE && labelsRank != Shape.UNKNOWN_SIZE) {
-      // Use static rank.
-      int rankDiff = predictionsRank - labelsRank;
-      if (rankDiff == expectedRankDiff + 1
-          && ShapeUtils.isCompatible(predictionsShape.size(-1), 1)) {
-        predictions = tf.squeeze(predictions);
-      } else if (rankDiff == expectedRankDiff - 1
-          && ShapeUtils.isCompatible(labelsShape.size(-1), 1)) {
-        labels = tf.squeeze(labels);
-      }
-      return new Tuple(labels, predictions);
-    }
-    // Use dynamic rank.
-    Operand rankDiff = tf.math.sub(tf.rank(predictions), tf.rank(labels));
-    if (predictionsRank == Shape.UNKNOWN_SIZE
-        && ShapeUtils.isCompatible(predictionsShape.size(-1), 1)) {
-      /**
-       * TODO, if we ever get a select that does lazy evaluation, but for now do the tf.squeeze
-       * predictions = tf.select( tf.math.equal(tf.constant(expectedRankDiff+1),rankDiff ),
-       * tf.squeeze(predictions, Squeeze.axis(Arrays.asList(-1L))), predictions ); *
-       */
-      predictions = tf.squeeze(predictions, Squeeze.axis(Arrays.asList(-1L)));
-    }
-    if (labelsRank == Shape.UNKNOWN_SIZE && ShapeUtils.isCompatible(labelsShape.size(-1), 1)) {
-      /**
-       * TODO, if we ever get a select that does lazy evaluation labels = tf.select(
-       * tf.math.equal(tf.constant(expectedRankDiff+1),rankDiff ), tf.squeeze(labels,
-       * Squeeze.axis(Arrays.asList(-1L))), predictions ); *
-       */
-      labels = tf.squeeze(labels, Squeeze.axis(Arrays.asList(-1L)));
-    }
-    return new Tuple(labels, predictions);
-  }
-
-  /**
-   * Computes the confusion matrix from predictions and labels.
-   *
-   * @param tf the TensorFlow Ops
-   * @param labels 1-D `Tensor` of real labels for the classification task.
-   * @param predictions 1-D `Tensor` of predictions for a given classification.
-   * @param numClasses The possible number of labels the classification task can have.
-   * @param weights optional weights to be applied to the confusion matris
-   * @param dtype Data type of the confusion matrix.
-   * @param  the type of Operands
-   * @param  the data type.
-   * @return A `Tensor` of type `dtype` with shape `[n, n]` representing the confusion matrix, where
-   *     `n` is the number of possible labels in the classification task.
-   * @throws IllegalArgumentException If both predictions and labels are not 1-D vectors and have
-   *     mismatched shapes, or if `weights` is not `None` and its shape doesn't match `predictions`.
-   */
-  public static  Operand confusionMatrix(
-      Ops tf,
-      Operand labels,
-      Operand predictions,
-      Operand numClasses,
-      Operand weights,
-      DataType dtype) {
-    tf = tf.withSubScope("confusion_matrix");
-    Tuple ops = K.squeezeOrExpandDimensions(tf, predictions, labels, null);
-    predictions = tf.dtypes.cast(ops.getPredictions(), TInt64.DTYPE);
-    labels = tf.dtypes.cast(ops.getLabels(), TInt64.DTYPE);
-
-    List labelControls = new ArrayList<>();
-    List predictionControls = new ArrayList<>();
-
-    labelControls.add(
-        tf.assertThat(
-            tf.reduceAny(
-                tf.math.greaterEqual((Operand) labels, tf.constant(0L)),
-                K.allAxis(tf, labels)),
-            Arrays.asList(tf.constant("`labels` contains negative values"))));
-
-    predictionControls.add(
-        tf.assertThat(
-            tf.reduceAny(
-                tf.math.greaterEqual((Operand) predictions, tf.constant(0L)),
-                K.allAxis(tf, labels)),
-            Arrays.asList(tf.constant("`predictions` contains negative values"))));
-    if (numClasses == null) {
-      numClasses =
-          tf.math.maximum(
-              tf.reduceMax(predictions, K.allAxis(tf, predictions)),
-              tf.reduceMax(labels, K.allAxis(tf, labels)));
-    } else {
-      labelControls.add(
-          tf.assertThat(
-              tf.reduceAny(
-                  tf.math.less((Operand) labels, numClasses), K.allAxis(tf, labels)),
-              Arrays.asList(tf.constant("``labels` out of bound"))));
-      predictionControls.add(
-          tf.assertThat(
-              tf.reduceAny(
-                  tf.math.less((Operand) predictions, numClasses),
-                  K.allAxis(tf, predictions)),
-              Arrays.asList(tf.constant("``predictions` out of bound"))));
-    }
-
-    if (weights != null) {
-      if (!ShapeUtils.isCompatibleWith(
-          predictions.asOutput().shape(), weights.asOutput().shape())) {
-        throw new IllegalArgumentException(
-            String.format(
-                "Prediction shape %s is not compatible with weights shaope %s",
-                predictions.asOutput().shape(), weights.asOutput().shape()));
-      }
-    }
-    final Operand labelsFinal = labels;
-    labels =
-        ControlDependencies.addControlDependencies(
-            tf, tfc -> tfc.identity(labelsFinal), "confusionMatrix", labelControls);
-    final Operand predictionsFinal = predictions;
-    predictions =
-        ControlDependencies.addControlDependencies(
-            tf, tfc -> tfc.identity(predictionsFinal), "confusionMatrix", labelControls);
-
-    Operand shape = tf.stack(Arrays.asList(numClasses, numClasses));
-    Operand indices = tf.stack(Arrays.asList(labels, predictions), Stack.axis(1L));
-    Operand values =
-        weights == null
-            ? tf.dtypes.cast(tf.onesLike(predictions), dtype)
-            : tf.dtypes.cast(weights, dtype);
-    SparseTensor cmSparse = new SparseTensor(indices, values, shape);
-    Operand zeroMatrix = tf.zeros(shape, dtype);
-
-    return tf.sparse.sparseTensorDenseAdd(
-        cmSparse.getIndices(), cmSparse.getValues(), cmSparse.getDenseShape(), zeroMatrix);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java
deleted file mode 100644
index 5b323a79ea9..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/ControlDependencies.java
+++ /dev/null
@@ -1,84 +0,0 @@
-/* Copyright 2020 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.keras.backend.tf;
-
-import org.tensorflow.keras.backend.*;
-import java.util.Arrays;
-import java.util.List;
-import java.util.function.Function;
-import org.tensorflow.Operand;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-import org.tensorflow.types.family.TType;
-
-/** Container for ControlDepencies, so that the primary Operand is remembered. */
-public class ControlDependencies {
-
-  /**
-   * Create a control dependency for the operand;
-   *
-   * @param tf the TensorFlow Ops
-   * @param createOperand a function that creates an operand with the control dependency context
-   * @param name the scope name to use
-   * @param dependencies a list of control ops.
-   * @param  the type of Operand
-   * @return the Operand with control dependency scope
-   */
-  public static  Operand addControlDependencies(
-      Ops tf, Function> createOperand, String name, Op... dependencies) {
-    return addControlDependencies(tf, createOperand, name, Arrays.asList(dependencies));
-  }
-
-  /**
-   * Create a control dependency for an operand.
-   *
-   * @param tf the TensorFlow Ops
-   * @param createOperand function that creates an operand with the control dependency context
-   * @param name the scope name to use
-   * @param dependencies a list of control ops.
-   * @param  the type of Operand
-   * @return the Operand with control dependency scope
-   */
-  public static  Operand addControlDependencies(
-      Ops tf, Function> createOperand, String name, List dependencies) {
-    tf = tf.withSubScope(name).withControlDependencies(dependencies);
-    return createOperand.apply(tf);
-  }
-
-  /**
-   * Create a control dependency as a NoOp
-   *
-   * @param tf the TensorFlow Ops
-   * @param name the scope name to use
-   * @param dependencies a list of control ops.
-   * @return NoOp with control dependency scope
-   */
-  public static Op addControlDependencies(Ops tf, String name, Op... dependencies) {
-    return addControlDependencies(tf, name, Arrays.asList(dependencies));
-  }
-
-  /**
-   * Create a control dependency as a NoOp
-   *
-   * @param tf the TensorFlow Ops
-   * @param name the scope name to use
-   * @param dependencies a list of control ops.
-   * @return NoOp with control dependency scope
-   */
-  public static Op addControlDependencies(Ops tf, String name, List dependencies) {
-    tf = tf.withSubScope(name).withControlDependencies(dependencies);
-    return tf.noOp();
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java
deleted file mode 100644
index e49fed5ba95..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/NN.java
+++ /dev/null
@@ -1,134 +0,0 @@
-/* Copyright 2020 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.keras.backend.tf;
-
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.List;
-import org.tensorflow.Operand;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-import org.tensorflow.op.nn.SparseSoftmaxCrossEntropyWithLogits;
-import org.tensorflow.types.TBfloat16;
-import org.tensorflow.types.TFloat16;
-import org.tensorflow.types.TFloat32;
-
-/** NN Operations */
-public class NN {
-
-  /**
-   * Computes sparse softmax cross entropy between `logits` and `labels`.
-   *
-   * @param tf
-   * @param labels `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of `labels` and
-   *     result) and dtype `int32` or `int64`. Each entry in `labels` must be an index in `[0,
-   *     num_classes)`. Other values will raise an exception when this op is run on CPU, and return
-   *     `NaN` for corresponding loss and gradient rows on GPU.
-   * @param logits Per-label activations (typically a linear output) of shape `[d_0, d_1, ...,
-   *     d_{r-1}, num_classes]` and dtype `float16`, `float32`, or `float64`. These activation
-   *     energies are interpreted as unnormalized log probabilities.
-   * @return A `Tensor` of the same shape as `labels` and of the same type as `logits` with the
-   *     softmax cross entropy loss.
-   */
-  public static Operand sparse_softmax_cross_entropy_with_logits(
-      Ops tf, Operand labels, Operand logits) {
-    // assert shapeIsCompatible(labels.asOutput().shape(), logits.asOutput().shape()):
-    //        String.format("Shapes %s and %s are incompatible",
-    //                labels.asOutput().shape(), logits.asOutput().shape());
-    tf = tf.withSubScope("SparseSoftmaxCrossEntropyWithLogits");
-    Operand precise_logits = logits;
-    boolean convertToFloat32 =
-        logits.asOutput().dataType() == TFloat16.DTYPE
-            || logits.asOutput().dataType() == TBfloat16.DTYPE;
-    if (convertToFloat32) {
-      precise_logits = tf.dtypes.cast(logits, TFloat32.DTYPE);
-    }
-    Shape labelsStaticShape = labels.asOutput().shape();
-    org.tensorflow.op.core.Shape labelsShape = tf.shape(labels);
-    Shape logitsShape = logits.asOutput().shape();
-    Operand labels_shape = tf.shape(labels);
-    Shape logitsShortened = logitsShape.take(logitsShape.numDimensions() - 1);
-
-    boolean staticShapesFullyDefined =
-        !labelsStaticShape.hasUnknownDimension() && !logitsShortened.hasUnknownDimension();
-    if (logitsShape.numDimensions() == 0) {
-      throw new IllegalArgumentException(
-          String.format("Logits cannot be scalars - received shape %s.", logitsShape));
-    }
-    if (!logitsShape.hasUnknownDimension()
-        && !labelsStaticShape.hasUnknownDimension()
-        && labelsStaticShape.numDimensions() != logitsShape.numDimensions() - 1) {
-      throw new IllegalArgumentException(
-          String.format(
-              "Rank mismatch: Rank of labels (received %s) should equal rank of logits minus 1 (received %s).",
-              labelsStaticShape.toString(), logitsShape.toString()));
-    }
-
-    if (staticShapesFullyDefined && !labelsStaticShape.equals(logitsShortened)) {
-      throw new IllegalArgumentException(
-          String.format(
-              "Shape mismatch: The shape of labels (received %s) "
-                  + "should equal the shape of logits except for the last "
-                  + "dimension (received %s).",
-              labelsStaticShape.toString(), logitsShape.toString()));
-    }
-    // Check if no reshapes are required.
-    if (logitsShape.numDimensions() == 2) {
-      SparseSoftmaxCrossEntropyWithLogits smax =
-          tf.nn.sparseSoftmaxCrossEntropyWithLogits(precise_logits, labels);
-      Operand loss = smax.loss();
-      if (logits.asOutput().dataType() == TFloat16.DTYPE) {
-        loss = tf.dtypes.cast(loss, TFloat16.DTYPE);
-      }
-      return loss;
-    }
-
-    List shapeChecks = new ArrayList<>();
-
-    if (!staticShapesFullyDefined) {
-      shapeChecks.add(
-          tf.assertThat(
-              tf.math.equal(tf.shape(labels), tf.shape.take(tf.shape(logits), tf.constant(-1))),
-              Arrays.asList(
-                  tf.constant(
-                      "Shape mismatch: The shape of labels  "
-                          + "should equal the shape of logits except for the last "
-                          + "dimension "))));
-    }
-
-    // Reshape logits to 2 dim, labels to 1 dim.
-    long numClassses = logitsShape.size(logitsShape.numDimensions() - 1);
-
-    precise_logits = tf.reshape(precise_logits, tf.constant(new long[] {-1, numClassses}));
-    labels = tf.reshape(labels, tf.constant(-1));
-    SparseSoftmaxCrossEntropyWithLogits smax =
-        tf.nn.sparseSoftmaxCrossEntropyWithLogits(precise_logits, labels);
-
-    return ControlDependencies.addControlDependencies(
-        tf,
-        tfc -> {
-          Operand cost = smax.loss();
-
-          cost = tfc.reshape(cost, labels_shape);
-          if (logits.asOutput().dataType() == TFloat16.DTYPE) {
-            cost = tfc.dtypes.cast(cost, TFloat16.DTYPE);
-          }
-          return cost;
-        },
-        "sparse_softmax_cross_entropy_with_logits",
-        shapeChecks);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java
deleted file mode 100644
index 45d9ec5b071..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/SparseTensor.java
+++ /dev/null
@@ -1,64 +0,0 @@
-/* Copyright 2020 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.keras.backend.tf;
-
-import org.tensorflow.Operand;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TType;
-
-/**
- * Represents a sparse tensor.
- *
- * @param  the type of the SparseTensor
- */
-public class SparseTensor {
-
-  private final Operand indices;
-  private final Operand values;
-  private final Operand denseShape;
-
-  /**
-   * Create a SparseTensor
-   *
-   * @param indices A 2-D int64 tensor of shape `[N, ndims]`, which specifies the indices of the
-   *     elements in the sparse tensor that contain nonzero values
-   * @param values A 1-D tensor of any type and shape `[N]`, which supplies the values for each
-   *     element in `indices`.
-   * @param denseShape A 1-D int64 tensor of shape `[ndims]`, which specifies the dense_shape of the
-   *     sparse tensor
-   * @throws IllegalArgumentException When building an eager SparseTensor if `dense_shape` is
-   *     unknown or contains unknown elements (None or -1).
-   */
-  public SparseTensor(Operand indices, Operand values, Operand denseShape) {
-    this.indices = indices;
-    this.values = values;
-    this.denseShape = denseShape;
-  }
-
-  /** @return the indices */
-  public Operand getIndices() {
-    return indices;
-  }
-
-  /** @return the values */
-  public Operand getValues() {
-    return values;
-  }
-
-  /** @return the denseShape */
-  public Operand getDenseShape() {
-    return denseShape;
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java
deleted file mode 100644
index 9f2f11285b4..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/Tuple.java
+++ /dev/null
@@ -1,109 +0,0 @@
-/* Copyright 2020 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.keras.backend.tf;
-
-import org.tensorflow.Operand;
-import org.tensorflow.types.family.TType;
-
-/**
- * Returns labels, losses or predictions and sample weights as a Tuple
- *
- * @param  the type of Operand
- */
-public class Tuple {
-
-  private final Operand labels;
-  private final Operand lossesOrPredictions;
-  private final Operand sampleWeights;
-
-  /**
-   * Creates a Tuple of Operands for labels, predictions, and sampleWeights
-   *
-   * @param labels the labels
-   * @param lossesOrPredictions the losses or predictions
-   */
-  public Tuple(Operand labels, Operand lossesOrPredictions) {
-    this(labels, lossesOrPredictions, null);
-  }
-
-  /**
-   * Creates a Tuple of Operands for labels, predictions, and sampleWeights
-   *
-   * @param labels the labels
-   * @param lossesOrPredictions the losses or predictions
-   * @param sampleWeights the sample weights
-   */
-  public Tuple(Operand labels, Operand lossesOrPredictions, Operand sampleWeights) {
-    this.labels = labels;
-    this.lossesOrPredictions = lossesOrPredictions;
-    this.sampleWeights = sampleWeights;
-  }
-
-  /**
-   * Indicates whether this Tuple contains Labels
-   *
-   * @return true is this Tuple contains Labels
-   */
-  public boolean containsLabels() {
-    return this.labels != null;
-  }
-
-  /**
-   * Indicates whether this Tuple contains Labels
-   *
-   * @return true is this Tuple contains Labels
-   */
-  public boolean containsPredictions() {
-    return this.lossesOrPredictions != null;
-  }
-
-  /**
-   * Indicates whether this Tuple contains Labels
-   *
-   * @return true is this Tuple contains Labels
-   */
-  public boolean containsLosses() {
-    return this.lossesOrPredictions != null;
-  }
-
-  /**
-   * Indicates whether this Tuple contains Labels
-   *
-   * @return true is this Tuple contains Labels
-   */
-  public boolean containsSampleWeights() {
-    return this.sampleWeights != null;
-  }
-
-  /** @return the labels */
-  public Operand getLabels() {
-    return labels;
-  }
-
-  /** @return the predictions */
-  public Operand getPredictions() {
-    return lossesOrPredictions;
-  }
-
-  /** @return the predictions */
-  public Operand getLosses() {
-    return lossesOrPredictions;
-  }
-
-  /** @return the sampleWeights */
-  public Operand getSampleWeights() {
-    return sampleWeights;
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java
deleted file mode 100644
index 391436ff8bd..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/backend/tf/WeightsBroadcastOps.java
+++ /dev/null
@@ -1,158 +0,0 @@
-/* Copyright 2020 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.keras.backend.tf;
-
-import java.util.Arrays;
-import java.util.List;
-import org.tensorflow.Operand;
-import org.tensorflow.keras.utils.ShapeUtils;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
-
-
-/** Weights Broadcast Ops */
-public class WeightsBroadcastOps {
-
-  private static final String ASSERT_BROADCASTABLE_ERROR_PREFIX =
-      "weights can not be broadcast to values.";
-
-  /**
-   * Asserts `weights` can be broadcast to `values`
-   *
-   * @param 
-   * @param tf the TensorFlow Ops
-   * @param weights `Tensor` of weights.
-   * @param values `Tensor` of values to which weights are applied.
-   * @return `Operation` raising `InvalidArgumentError` if `weights` has incorrect shape. `no_op` if
-   *     static checks determine `weights` has correct shape.
-   * @param  the type of Operand
-   * @throws IllegalArgumentException If static checks determine `weights` has incorrect shape.
-   */
-  public static  Op assertBroadcastable(
-      Ops tf, Operand weights, Operand values) {
-    Operand weightsShape = tf.shape(weights);
-    Operand weightsRank = tf.rank(weights);
-    Shape weightsShapeStatic = weights.asOutput().shape();
-    int weightsRankStatic = weightsShapeStatic.numDimensions();
-
-    Operand valuesShape = tf.shape(values);
-    Operand valuesRank = tf.rank(values);
-    Shape valuesShapeStatic = values.asOutput().shape();
-    int valuesRankStatic = valuesShapeStatic.numDimensions();
-
-    if (weightsRankStatic != -1 && valuesRankStatic != -1) {
-      if (weightsRankStatic == 0) {
-        return ControlDependencies.addControlDependencies(tf, "static_scalar_check_success");
-      }
-      if (weightsRankStatic != valuesRankStatic) {
-        throw new IllegalArgumentException(
-            String.format(
-                "",
-                "%s values.rank=%d. weights.rank=%d.  values.shape=%s. weights.shape=%s.",
-                ASSERT_BROADCASTABLE_ERROR_PREFIX,
-                valuesRankStatic,
-                weightsRankStatic,
-                valuesShapeStatic.toString(),
-                weightsShapeStatic.toString()));
-      }
-
-      for (int i = 0; i < valuesRankStatic; i++) {
-        if (valuesShapeStatic.size(i) != weightsShapeStatic.size(i)) {
-          throw new IllegalArgumentException(
-              String.format(
-                  "",
-                  "%s Mismatch at dim %s. values.shape=%s weights.shape=%s.",
-                  ASSERT_BROADCASTABLE_ERROR_PREFIX,
-                  i,
-                  valuesShapeStatic.toString(),
-                  weightsShapeStatic.toString()));
-        }
-      }
-      return ControlDependencies.addControlDependencies(tf, "static_dims_check_success");
-    }
-    // Dynamic checks.
-    Operand is_scalar = tf.math.equal(weightsRank, tf.constant(0));
-    List> data =
-        Arrays.asList(
-            tf.constant(ASSERT_BROADCASTABLE_ERROR_PREFIX),
-            tf.constant("weights.shape="),
-            weightsShape,
-            tf.constant("values.shape="),
-            valuesShape,
-            tf.constant("is_scalar="),
-            is_scalar);
-
-    Operand isValidShape =
-        tf.select(
-            is_scalar,
-            is_scalar,
-            hasValidNonscalarShape(tf, weightsRank, weightsShape, valuesRank, valuesShape));
-
-    return tf.assertThat(isValidShape, data);
-  }
-
-  private static  Operand hasValidNonscalarShape(
-      Ops tf,
-      Operand weightsRank,
-      Operand weightsShape,
-      Operand valuesRank,
-      Operand valuesShape) {
-    tf = tf.withSubScope("has_valid_nonscalar_shape");
-    Operand isSameRank = tf.math.equal(valuesRank, weightsRank);
-    return tf.select(isSameRank, hasValidDims(tf, weightsShape, valuesShape), isSameRank);
-  }
-
-  private static  Operand hasValidDims(
-      Ops tf, Operand weightsShape, Operand valuesShape) {
-    tf = tf.withSubScope("has_invalid_dims");
-    Operand diff = tf.reduceSum(tf.math.sub(weightsShape, valuesShape), tf.constant(0));
-    return tf.math.equal(tf.constant(0), diff);
-  }
-
-  /**
-   * Broadcast `weights` to the same shape as `values`.
-   *
-   * @param tf the TensorFlow ops
-   * @param weights `Tensor` whose shape is broadcastable to `values`
-   * @param values Tensor` of any shape
-   * @param  the type of Operand
-   * @return `weights` broadcast to `values` shape
-   */
-  public static  Operand broadcastWeights(
-      Ops tf, Operand weights, Operand values) {
-    tf = tf.withSubScope("broadcast_weights");
-    values = tf.dtypes.cast(values, weights.asOutput().dataType());
-
-    Shape weightsShape = weights.asOutput().shape();
-    Shape valuesShape = values.asOutput().shape();
-
-    if (!weightsShape.hasUnknownDimension()
-        && !valuesShape.hasUnknownDimension()
-        && ShapeUtils.isCompatibleWith(weightsShape, valuesShape)) {
-      return weights;
-    }
-
-    weights = tf.math.mul(weights, tf.onesLike(values));
-    Op dependencies = assertBroadcastable(tf, weights, values);
-    final Operand weightsFinal = weights;
-    return ControlDependencies.addControlDependencies(
-        tf, tfc -> tfc.identity(weightsFinal), "assertBroadcastable", dependencies);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java
deleted file mode 100644
index ef2f20e648a..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PlaceholderStringFormat.java
+++ /dev/null
@@ -1,81 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.regex.Matcher;
-import java.util.regex.Pattern;
-
-/** Utility that handles Python style placholder formats, used in Callbacks */
-public class PlaceholderStringFormat {
-  private static final Pattern PYTHON_MATCH = Pattern.compile("\\{(\\w+):([\\w\\.]+)\\}");
-
-  /**
-   * Convert a Python style placeholder file path format to file path
-   *
-   * @param filename the placeholder file path format
-   * @param epoch the epoch number to place into the filename format
-   * @param logs a Dictionary of log values that are replaced into the filename format
-   * @return the resulting filename after applying all placeholders.
-   */
-  public static String convertFilePath(String filename, int epoch, Map logs) {
-    List vars = new ArrayList<>();
-    Map valMap = new HashMap<>();
-    String format = getFilePath(filename, vars);
-    List objects = new ArrayList<>();
-    vars.forEach(
-        key -> {
-          if (key.equals("epoch")) objects.add(epoch);
-          else objects.add((Number) logs.get(key));
-        });
-    return String.format(format, objects.toArray(new Number[objects.size()]));
-  }
-
-  /**
-   * Get the variable identifiers from the placeholder filename string
-   *
-   * @param filename the filename name in Placeholder format.
-   * @param vars the list of variables from the caller, with added variables parsed from the
-   *     filename
-   * @return a string in String.format style
-   */
-  private static String getFilePath(String filename, List vars) {
-    Matcher m = PYTHON_MATCH.matcher(filename);
-    StringBuilder sb = new StringBuilder();
-    int beginIndex = 0;
-    Map indexMap = new HashMap<>();
-    int lastIndex = 1;
-    while (m.find()) {
-      int start = m.start(0);
-      int end = m.end(0);
-      String variable = m.group(1);
-      vars.add(variable);
-      String format = m.group(2);
-      Integer index = indexMap.get(variable);
-      if (index == null) {
-        indexMap.put(variable, lastIndex);
-        index = lastIndex++;
-      }
-      sb.append(filename.substring(beginIndex, start));
-      sb.append('%').append(index).append('$').append(format);
-      beginIndex = end;
-    }
-    sb.append(filename.substring(beginIndex));
-    return sb.toString();
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java
deleted file mode 100644
index 9a21c50893f..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/PrintUtils.java
+++ /dev/null
@@ -1,152 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import org.tensorflow.DataType;
-import org.tensorflow.Tensor;
-import org.tensorflow.types.TFloat16;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TUint8;
-import org.tensorflow.types.TBfloat16;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TString;
-
-/**
- *  Utility to print Tensor values
- */
-public class PrintUtils {
-
-    /**
-     * Print a tensor's values
-     * @param tensor the tensor to print
-     */
-    public static void print(Tensor tensor) {
-        switch(tensor.dataType().name()) {
-            case "BFLOAT16":
-                printTBfloat16(tensor);
-                break;
-            case "FLOAT16":
-                 printTFloat16(tensor);
-                break;
-            case "FLOAT":
-                 printTFloat32(tensor);
-                break;
-            case "DOUBLE":
-                 printTFloat64(tensor);
-                break;
-            case "INT32":
-                 printTInt32(tensor);
-                break;
-            case "INT64":
-                 printTInt64(tensor);
-                break;
-            case "UINT8":
-                 printTUint8(tensor);
-                break;
-            case "BOOL":
-                 printTBool(tensor);
-                break;
-            case "STRING":
-                 printTString(tensor);
-                break;
-            default:
-                break;
-        }
-        
-    }
-
-    /**
-     * Print a boolean Tensot
-     * @param t the tensor to print
-     */
-    public static void printTBool(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(s.getBoolean() + ", "));
-        System.out.println();
-    }
-
-    /**
-     * Print a String Tensot
-     * @param t the tensor to print
-     */
-    public static void printTString(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print("\"" + s.getObject() + "\", "));
-        System.out.println();
-    }
-
-    /**
-     * Print a TBfloat16 Tensor
-     * @param t the tensor to print
-     */
-    public static void printTBfloat16(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(s.getFloat() + ", "));
-        System.out.println();
-    }
-
-    /**
-     * Print a uint8 Tensor
-     * @param t the tensor to print
-     */
-    public static void printTUint8(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(String.format("0x%x",s.getByte()) + ", "));
-        System.out.println();
-    }
-
-    /**
-     * Print an int32 Tensor
-     * @param t the tensor to print
-     */
-     public static void printTInt32(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(s.getInt() + ", "));
-        System.out.println();
-    }
-
-    /**
-     * Print an int64 Tensor
-     * @param t the tensor to print
-     */
-     public static void printTInt64(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(s.getLong() + ", "));
-        System.out.println();
-    }
-
-    /**
-     * Print a Float16 tensor.
-     * @param t the tensor to print
-     */
-    public static void printTFloat16(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(s.getFloat() + "F, "));
-        System.out.println();
-    }
-
-    /**
-     * Print a Float32 tensor.
-     * @param t the tensor to print
-     */
-    public static void printTFloat32(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(s.getFloat() + "F, "));
-        System.out.println();
-    }
-    /**
-     * Print a Float64 tensor.
-     * @param t the tensor to print
-     */
-    public static void printTFloat64(Tensor t) {
-        t.data().scalars().forEach(s -> System.out.print(s.getDouble() + ", "));
-        System.out.println();
-    }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java
deleted file mode 100644
index 9dd3de4e1a2..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ProgressBar.java
+++ /dev/null
@@ -1,311 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import java.io.Console;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Map.Entry;
-
-/**
- * Display a progess bar either to the Console or System.out.
- * 
- * @author jbclarke
- */
-public class ProgressBar {
-    private final static double MICRO_SECONDS = 1E-3;
-    private final static long MILLI_SECOND = 1l;
-    private final static long SECOND = 1000L;
-    private final static long MINUTE = 60L * SECOND;
-    private final static long HOUR = 60L * MINUTE;
-    
-    private Integer target;
-    private int width;
-    private boolean verbose;
-    private long interval;
-    private List statefulMetrics;
-    private String unit;
-    
-    private int totalWidth;
-    private int seenSoFar;
-    private final Map values = new HashMap<>();
-    private final List valuesOrder = new ArrayList<>();
-    
-    private final long start = System.currentTimeMillis();
-    private long lastUpdate = 0;
-    
-    // will be null if console is not present
-    private final Console console = System.console();
-    
-    /**
-     * Create a ProgressBar
-     */
-    public ProgressBar() {
-        this(null, 30, true, 50, "step", null );
-        
-    }
-    
-    /**
-     * Create a ProgressBar
-     * 
-     * @param target Total number of steps expected, null if unknown.
-     */
-    public ProgressBar(Integer target) {
-        this(target, 30, true, 50, "step", null );
-        
-    }
-    
-    /**
-     * Create a ProgressBar
-     * 
-     * @param target Total number of steps expected, null if unknown.
-     * @param verbose Verbosity mode
-     * @param unit Display name for step counts (usually "step" or "sample").
-     * @param statefulMetrics 
-     */
-    public ProgressBar(Integer target, boolean verbose, String unit, List statefulMetrics) {
-        this(target, 30, verbose, 50, unit, statefulMetrics );
-        
-    }
-    
-    
-    
-    /**
-     * Create a ProgressBar
-     * 
-     * @param target Total number of steps expected, null if unknown.
-     * @param width Progress bar width on screen.
-     * @param verbose Verbosity mode
-     * @param interval Minimum visual progress update interval (in milliseconds).
-     * @param unit Display name for step counts (usually "step" or "sample").
-     * @param statefulMetrics 
-     */
-    public ProgressBar(Integer target, int width, boolean verbose, long interval, String unit, List statefulMetrics) {
-        this.target = target;
-        this.width = width;
-        this.verbose = verbose;
-        this.interval = interval;
-        this.unit = unit;
-        this.statefulMetrics = statefulMetrics == null ? Collections.EMPTY_LIST : statefulMetrics;
-    }
-    
-    /**
-     * Updates the progress bar.
-     * 
-     * @param current Index of current step.
-     * @param values List of Pairs: `(name, value_for_last_step)`. If `name` is in
-     * `statefulMetrics`, `value_for_last_step` will be displayed as-is.
-     * Else, an average of the metric over time will be displayed.
-     */
-    public void update(Integer current, List> values) {
-        update(current, values, null);
-    }
-    
-    /**
-     * Updates the progress bar.
-     * 
-     * @param current  Index of current step.
-     * @param values  List of Entry: `(name, value_for_last_step)`. If `name` is in
-     * `statefulMetrics`, `value_for_last_step` will be displayed as-is.
-     * Else, an average of the metric over time will be displayed.
-     * @param finalize Whether this is the last update for the progress bar. If
-     * `None`, defaults to `current >= self.target`.
-     */
-    public void update(Integer current, List> values, Boolean finalize) {
-        if(finalize == null) {
-            if(this.getTarget() == null) {
-                finalize = false;
-            }else {
-                finalize = current >= this.getTarget();
-            }
-        }
-        values = values == null ? Collections.EMPTY_LIST : values;
-        
-        values.forEach(e -> {
-            if(!this.valuesOrder.contains(e.getKey())) {
-                this.valuesOrder.add(e.getKey());
-            }
-            if(!this.statefulMetrics.contains(e.getKey())) {
-                int valueBase = Math.max(current - this.seenSoFar, 1);
-                if(!this.values.containsKey(e.getKey())) {
-                    this.values.put(e.getKey(), new Number[] { e.getValue().doubleValue() * valueBase, valueBase});
-                }else {
-                    Number[] n = this.values.get(e.getKey());
-                    n[0] = n[0].doubleValue() + e.getValue().doubleValue() * valueBase;
-                    n[1] = n[1].doubleValue() + valueBase;
-                }
-            }else {
-                this.values.put(e.getKey(),new Number[] { e.getValue().doubleValue(), 1});
-            }
-            
-        });
-        
-        this.seenSoFar = current;
-        long now = System.currentTimeMillis();
-        
-        StringBuilder info = new StringBuilder(String.format(" - %.0fs", (double)(now - this.start)/(double)SECOND));
-        
-        if(this.verbose) {
-            if(now - this.lastUpdate < this.interval && !finalize) {
-                return;
-            }
-        }
-        int prevTotalWidth = this.totalWidth;
-        if (this.console != null) {
-            for(int i = 0; i < prevTotalWidth; i++) {
-                this.console.printf("\b");
-            }
-            this.console.printf("\r");
-        } else {
-            System.out.println();
-        }
-        StringBuilder bar = new StringBuilder();
-        if(this.getTarget() != null) {
-            int numDigits = (int)Math.log10(this.getTarget()) + 1;
-            bar.append(String.format("%" + numDigits + "d/%d [", current, this.getTarget()));
-            double prog = (double)current / this.getTarget();
-            int progWidth = (int)(this.width * prog);
-            if(progWidth >= 0) {
-                for(int i = 0; i < progWidth-1; i++) 
-                    bar.append('=');
-                if(current < this.getTarget())
-                    bar.append('>');
-                else
-                    bar.append('=');
-                for(int i = 0; i < this.width - progWidth; i++)
-                    bar.append('.');
-                bar.append(']');
-            }
-        }else {
-            bar.append(String.format("%7d/Unknown", current));
-        }
-        this.totalWidth = bar.length();
-        if(this.console != null) {
-            this.console.printf(bar.toString());
-        }else {
-            System.out.print(bar.toString());
-        }
-        // in millis
-        double timePerUnit = current != null ? (double)(now - this.start) / current: 0.0;
-        if(this.getTarget() == null || finalize) {
-            if(timePerUnit >= SECOND || timePerUnit == 0.0) { // seconds
-                info.append(String.format(" %.0fs/%s", timePerUnit/SECOND, this.unit));
-            }else if(timePerUnit >= 1) { // milliseconds
-                info.append(String.format(" %.0fms/%s", timePerUnit, this.unit));
-            }else { // microseconds
-                info.append(String.format(" %.0fus/%s", timePerUnit*SECOND, this.unit));
-            }
-        }else {
-           double eta = timePerUnit * (this.getTarget() - current); 
-           String etaFormat;
-           if(eta >= HOUR) { // greater than an hour
-               etaFormat = String.format("%d:%02d:%02d",  // hh:mm:ss
-                       (int) (eta / HOUR), 
-                       (int) (eta / HOUR /  MINUTE), 
-                       (int) (eta % MINUTE)/SECOND);
-           }else if(eta >= MINUTE) { 
-               etaFormat = String.format("%d:%02d",  // mm:ss
-                       (int) (eta / MINUTE), 
-                       (int) (eta % MINUTE)/SECOND);
-           }else {
-               etaFormat = String.format("%ds", (int)(eta/SECOND));
-           }
-           info.append(" - ETA: ").append(etaFormat);
-        }
-           
-        this.valuesOrder.forEach(key -> {
-            info.append(String.format(" - %s:", key));
-            Number[] val = this.values.get(key);
-            double avg = val[0].doubleValue() / Math.max(1.0, val[1].doubleValue());
-            if(Math.abs(avg) > 1e-3)
-                 info.append(String.format(" %.4f", avg));
-             else
-                info.append(String.format(" %.4e", avg));
-        });
-        this.totalWidth += info.length();
-        if(prevTotalWidth > this.totalWidth) 
-            for(int i = 0; i < prevTotalWidth - this.totalWidth; i++)
-                info.append(' ');
-        if(finalize) {
-            info.append('\n');
-        }
-
-        if(this.console != null) {
-           console.printf(info.toString());
-           console.flush();
-       }else {
-           System.out.print(info.toString());
-           System.out.flush();
-       }
-        this.lastUpdate = now;
-    }
-    
-    /**
-     * updates the progress bar by one unit
-     */
-    public void increment() {
-        add(1);
-    }
-    
-    /**
-     * updates the progress bar by one unit
-     * 
-     * @param values List of Entry: `(name, value_for_last_step)`. If `name` is in
-     * `statefulMetrics`, `value_for_last_step` will be displayed as-is.
-     * Else, an average of the metric over time will be displayed.
-     */
-    public void increment(List> values) {
-        add(1, values);
-    }
-    
-    /**
-     * update the progress bar 
-     * 
-     * @param n the number of units to add to the current number
-     */
-    public void add(int n) {
-        add(n, null);
-    }
-    
-    /**
-     * update the progress bar 
-     * 
-     * @param n the number of units to add to the current number
-     * @param values List of Entry: `(name, value_for_last_step)`. If `name` is in
-     * `statefulMetrics`, `value_for_last_step` will be displayed as-is.
-     * Else, an average of the metric over time will be displayed.
-     */
-    public void add(int n, List> values) {
-        this.update(this.seenSoFar + n, values);
-    }
-
-    /**
-     * @return the target
-     */
-    public Integer getTarget() {
-        return target;
-    }
-
-    /**
-     * @param target the target to set
-     */
-    public void setTarget(Integer target) {
-        this.target = target;
-    }
-}
-
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java
deleted file mode 100644
index 4fa69d0e537..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/ShapeUtils.java
+++ /dev/null
@@ -1,110 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import java.util.ArrayList;
-import java.util.List;
-import org.tensorflow.Operand;
-import org.tensorflow.Tensor;
-import org.tensorflow.ndarray.NdArray;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.types.TInt64;
-
-/**
- *
- * @author Jim Clarke
- */
-public class ShapeUtils {
-
-    /**
-     * Convert shape operand back to a Shape object
-     *
-     * @param dims the Operand containing the shape values
-     * @return
-     */
-    public static Shape getShape(Operand dims) {
-        // TODO is there a better way?
-        final List dimList = new ArrayList<>();
-        dims.data().scalars().forEach(s -> dimList.add(s.getLong()));
-        long[] longDims = new long[dimList.size()];
-        for (int i = 0; i < dimList.size(); i++) {
-            longDims[i] = dimList.get(i);
-        }
-        return Shape.of(longDims);
-    }
-
-    /**
-     * get the shape for the data within a Tensor
-     *
-     * @param tensor the tensor
-     * @return the Shape of the tensor's data;
-     */
-    public static Shape getShape(Tensor tensor) {
-        NdArray data = (NdArray) tensor.data();
-        return data.shape();
-
-    }
-
-    public static boolean isCompatibleWith(Shape a, Shape b) {
-        if (!isUnknownShape(a) && !isUnknownShape(b)) {
-            if (a.numDimensions() != b.numDimensions()) {
-                return false;
-            }
-            for (int i = 0; i < a.numDimensions(); i++) {
-                if (a.size(i) != Shape.UNKNOWN_SIZE
-                        && b.size(i) != Shape.UNKNOWN_SIZE
-                        && b.size(i) != a.size(i)) {
-                    return false;
-                }
-            }
-        }
-        return true;
-    }
-
-    public static boolean isUnknownShape(Shape a) {
-        return a.size() == 0;
-    }
-
-    /**
-     * Reshapes the shape by eliminating trailing Dimensions.
-     *
-     * @param oldShape
-     * @param axis
-     * @return the new shape
-     */
-    public static Shape squeeze(Shape oldShape, int axis) {
-        axis %= oldShape.numDimensions();
-        if (axis < 0) {
-            axis = oldShape.numDimensions() + axis;
-        }
-        long[] array = oldShape.asArray();
-        long[] newArray = new long[axis];
-        for (int i = 0; i < axis - 1; i++) {
-            newArray[i] = array[i];
-        }
-        long sum = array[axis - 1];
-        for (int i = axis; i < array.length; i++) {
-            sum *= array[i];
-        }
-        newArray[axis - 1] = sum;
-        return Shape.of(newArray);
-    }
-
-    public static boolean isCompatible(long dim, long otherDim) {
-        return dim == Shape.UNKNOWN_SIZE
-                || otherDim == Shape.UNKNOWN_SIZE
-                || dim == otherDim;
-    }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java
deleted file mode 100644
index 3dff11c513e..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SmartCond.java
+++ /dev/null
@@ -1,107 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import java.util.function.Supplier;
-import org.tensorflow.Operand;
-import org.tensorflow.op.Ops;
-import org.tensorflow.types.TBool;
-
-/** Implements a select Operation using Lambdas */
-public class SmartCond {
-
-  /**
-   * Creates a select operation
-   *
-   * @param pred the predicate (boolean) used to select
-   * @param then_fn the function to execute if the predicate is true
-   * @param else_fn the function to execute if the predicate is false
-   * @return the result of the select on the condition
-   */
-  public static Operand select(Boolean pred, Supplier then_fn, Supplier else_fn) {
-    assert pred != null : "pred must not be null";
-    assert then_fn != null : "then_fn must not be null";
-    assert else_fn != null : "else_fn must not be null";
-    return pred ? then_fn.get() : else_fn.get();
-  }
-
-  /**
-   * Creates a select operation
-   *
-   * @param pred the predicate ( true == 1) used to select
-   * @param then_fn the function to execute if the predicate is true
-   * @param else_fn the function to execute if the predicate is false
-   * @return the result of the select on the condition
-   */
-  public static Operand select(Number pred, Supplier then_fn, Supplier else_fn) {
-    assert pred != null : "pred must not be null";
-    assert then_fn != null : "then_fn must not be null";
-    assert else_fn != null : "else_fn must not be null";
-    return pred.intValue() == 1 ? then_fn.get() : else_fn.get();
-  }
-
-  /**
-   * Creates a select operation
-   *
-   * @param pred the predicate ( true if the string argument is not null and is equal, ignoring
-   *     case, to the string "true") used to select
-   * @param then_fn the function to execute if the predicate is true
-   * @param else_fn the function to execute if the predicate is false
-   * @return the result of the select on the condition
-   */
-  public static Operand select(String pred, Supplier then_fn, Supplier else_fn) {
-    assert pred != null : "pred must not be null";
-    assert then_fn != null : "then_fn must not be null";
-    assert else_fn != null : "else_fn must not be null";
-    return Boolean.valueOf(pred) ? then_fn.get() : else_fn.get();
-  }
-
-  /**
-   * Create a Select operation
-   *
-   * @param tf the tensorFlow Ops
-   * @param pred the operand that evaluates to true or false
-   * @param then_fn the function to execute if the predicate is true
-   * @param else_fn the function to execute if the predicate is false
-   * @return a Select Operation if in graph mode, else return the result of the select
-   */
-  public static Operand select(
-      Ops tf, Operand pred, Supplier then_fn, Supplier else_fn) {
-    assert pred != null : "pred must not be null";
-    assert then_fn != null : "then_fn must not be null";
-    assert else_fn != null : "else_fn must not be null";
-    if (tf.scope().env().isEager()) {
-      return pred.asOutput().data().getBoolean() ? then_fn.get() : else_fn.get();
-    } else { // TODO, maybe some day handle Supplier in the c interface
-      return tf.select(pred, then_fn.get(), else_fn.get());
-    }
-  }
-
-  /**
-   * Creates a slect operation
-   *
-   * @param tf the tensorFlow Ops
-   * @param pred the operand that evaluates to true or false
-   * @param then_fn the function to execute if the predicate is true
-   * @param else_fn the function to execute if the predicate is false
-   * @return the Select opertion
-   */
-  public static Operand select(Ops tf, Operand pred, Operand true_op, Operand false_op) {
-    assert pred != null : "pred must not be null";
-    assert true_op != null : "true_op must not be null";
-    assert false_op != null : "false_op must not be null";
-    return tf.select(pred, true_op, false_op);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java
deleted file mode 100644
index b2e63fe1cff..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShape.java
+++ /dev/null
@@ -1,92 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.List;
-import org.tensorflow.Operand;
-
-/**
- * Utility class that handles sybmolic shapes so that the shapes can be resolved during runtime and
- * stay consistent across operands.
- *
- * 
The same symbols accros variaous shapes should have the same dimension values.
- *
- * 
shape1 = Shape("N","L")
- *
- * 
shape2 = Shape("L", "T")
- *
- * 
For exmple, for Symbol "L" 
- * shape1.size(2) == shape2.size(1)
- *
- * 
Example:
- *
- * 
- * List symbols = new ArrayList<>(); symbols.add(new SymbolicShape(yTrue, "N", "L"));
- * if (this.isMultiLabel()) { symbols.add(new SymbolicShape(this.truePositives, "T", "L"));
- * symbols.add(new SymbolicShape(this.falsePositives, "T", "L")); symbols.add(new
- * SymbolicShape(this.trueNegatives, "T", "L")); symbols.add(new SymbolicShape(this.falseNegatives,
- * "T", "L")); } if (this.getLabelWeights() != null) { symbols.add(new
- * SymbolicShape(this.getLabelWeights(), "L", "")); }
- * updateOperations.addAll(Metrics.assert_shapes(tf, symbols, "Number of labels is not
- * consistent."));
- * 

- */
-public class SymbolicShape {
-
-  private Operand operand;
-  private List symbols = new ArrayList<>();
-
-  /**
-   * Create a SymbolicShape for an Operand.
-   *
-   * @param operand the Operand
-   * @param symbols the symbols
-   */
-  public SymbolicShape(Operand operand, String... symbols) {
-    this.operand = operand;
-    this.symbols.addAll(Arrays.asList(symbols));
-  }
-
-  /** @return the operand */
-  public Operand getOperand() {
-    return operand;
-  }
-
-  /** @param operand the operand to set */
-  public void setOperand(Operand operand) {
-    this.operand = operand;
-  }
-
-  /** @return the symbols */
-  public List getSymbols() {
-    return symbols;
-  }
-
-  /** @param symbols the symbols to set */
-  public void setSymbols(List symbols) {
-    this.symbols = symbols;
-  }
-
-  /**
-   * Get the rank of the symbol list
-   *
-   * @return the rank of the symbol list
-   */
-  public int rank() {
-    return this.symbols.size();
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java
deleted file mode 100644
index e7c9acf1c5e..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/SymbolicShapeDict.java
+++ /dev/null
@@ -1,58 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import java.util.HashMap;
-import java.util.Map;
-
-/**
- * Utility class that contains a dictionary of Symbols. The map is updated with symbols and their
- * dimension values. Used in creating matching shapes that depend on other shapes' dimensions.
- */
-public class SymbolicShapeDict {
-
-  /** Dictionary containing the sybmols and their associated dimensions sizes. */
-  private final Map map = new HashMap<>();
-
-  /**
-   * Add a symbol with its associated dimensions size.
-   *
-   * @param symbol the symbol name
-   * @param size the shape dimension to associate with the symbol
-   */
-  public void put(String symbol, Long size) {
-    this.map.put(symbol, size);
-  }
-
-  /**
-   * Get the dimention size for a symbol
-   *
-   * @param symbol the symbol name
-   * @return the dimension size for the symbol or null if not found.
-   */
-  public Long get(String symbol) {
-    return this.map.get(symbol);
-  }
-
-  /**
-   * Determine if the symbol is contained in the dictionary.
-   *
-   * @param symbol the symbol name
-   * @return true, if the dictionary contains the symbol.
-   */
-  public boolean contains(String symbol) {
-    return map.containsKey(symbol);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java
deleted file mode 100644
index a2629ef07b1..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/utils/TypeUtils.java
+++ /dev/null
@@ -1,98 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import org.tensorflow.DataType;
-import org.tensorflow.types.TBfloat16;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat16;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TString;
-import org.tensorflow.types.TUint8;
-
-
-/**
- *
- * @author Jim Clarke
- */
-public class TypeUtils {
-    
-    //TODO
-    public static boolean isComplex(DataType dtype) {
-        return false;
-    }
-    
-    public static boolean isFloating(DataType dtype) {
-        switch(dtype.name()) {
-            case "BFLOAT16":
-            case "FLOAT16":
-            case "FLOAT":
-            case "DOUBLE":
-                return true;
-            default: return false;
-        }
-    }
-    public static boolean isInteger(DataType dtype) {
-        switch(dtype.name()) {
-            case "INT32":
-            case "INT64":
-            case "UINT8":
-                return true;
-            default: return false;
-        }
-    }
-    
-    public static boolean isNumeric(DataType dtype) {
-        return isFloating(dtype) || isInteger(dtype);
-    }
-    
-    public static boolean isBoolean(DataType dtype) {
-        return dtype.name().equals("BOOL");
-    }
-    
-    public static boolean isString(DataType dtype) {
-        return dtype.name().equals("STRING");
-    }
-    
-    public static DataType of(String name) {
-        switch(name) {
-            case "BFLOAT16":
-                return TBfloat16.DTYPE;
-            case "FLOAT16":
-                return TFloat16.DTYPE;
-            case "FLOAT":
-                return TFloat32.DTYPE;
-            case "DOUBLE":
-                return TFloat64.DTYPE;
-            case "UINT8":
-                return TUint8.DTYPE;
-            case "INT32":
-                return TInt32.DTYPE;
-            case "INT64":
-                return TInt64.DTYPE;
-            case "BOOL":
-                return TBool.DTYPE;
-            case "STRING":
-                return TString.DTYPE;
-            default:
-                throw new IllegalArgumentException(String.format("%s is an unknown DataType", name));
-                
-        }
-    }
-    
-}
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java
deleted file mode 100644
index 1aaa4aa7af4..00000000000
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/SmartCondTest.java
+++ /dev/null
@@ -1,247 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import java.util.function.Supplier;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
-import org.tensorflow.Graph;
-import org.tensorflow.Operand;
-import org.tensorflow.Session;
-import org.tensorflow.Tensor;
-import org.tensorflow.op.Ops;
-import org.tensorflow.op.core.Constant;
-import org.tensorflow.types.TBool;
-
-/**
- *
- * @author Jim Clarke
- */
-public class SmartCondTest {
-
-    public SmartCondTest() {
-    }
-
-    @BeforeAll
-    public static void setUpClass() {
-    }
-
-    @AfterAll
-    public static void tearDownClass() {
-    }
-
-    @BeforeEach
-    public void setUp() {
-    }
-
-    @AfterEach
-    public void tearDown() {
-    }
-
-    /**
-     * Test of cond method, of class SmartCond.
-     */
-    @Test
-    public void testCondOp() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            Constant pred = tf.constant(true);
-            sess.run(pred);
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = true;
-            Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-
-        }
-    }
-
-    @Test
-    public void testCondOp2() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            Constant pred = tf.constant(true);
-            sess.run(pred);
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = true;
-            Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-
-        }
-    }
-
-    @Test
-    public void testCondOpPoint1() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            Operand pred = tf.math.equal(tf.constant(0.1), tf.constant(1.0));
-            sess.run(pred);
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = false;
-            Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-        }
-    }
-
-    @Test
-    public void testCondOpString() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            Operand pred = tf.math.equal(tf.constant("TRUE"), tf.constant("TRUE"));
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = true;
-            Operand resultOp = SmartCond.select(tf, pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-        }
-    }
-
-    /**
-     * Test of cond method, of class SmartCond.
-     */
-    @Test
-    public void testCondBoolean() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            boolean pred = false;
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = false;
-            Operand resultOp = SmartCond.select(pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-
-        }
-    }
-
-    /**
-     * Test of cond method, of class SmartCond.
-     */
-    @Test
-    public void testCondInt() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            int pred = 1;
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = true;
-            Operand resultOp = SmartCond.select(pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-
-        }
-    }
-
-    /**
-     * Test of cond method, of class SmartCond.
-     */
-    @Test
-    public void testCondFloat1() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            float pred = 1.0F;
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = true;
-            Operand resultOp = SmartCond.select(pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-
-        }
-    }
-
-    /**
-     * Test of cond method, of class SmartCond.
-     */
-    @Test
-    public void testCondFloat0_1() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            float pred = 0.1F;
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = false;
-            Operand resultOp = SmartCond.select(pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-
-        }
-    }
-
-    /**
-     * Test of cond method, of class SmartCond.
-     */
-    @Test
-    public void testCondString() {
-        try (Graph graph = new Graph(); Session sess = new Session(graph)) {
-            Ops tf = Ops.create(graph).withName("test");
-            String pred = "true";
-
-            Supplier true_fn = () -> tf.constant(true);
-            Supplier false_fn = () -> tf.constant(false);
-            boolean expResult = true;
-            Operand resultOp = SmartCond.select(pred, true_fn, false_fn);
-            boolean actualResult;
-            try (Tensor result = sess.runner().fetch(resultOp).run().get(0).expect(TBool.DTYPE)) {
-                actualResult = result.data().getBoolean();
-                assertEquals(expResult, actualResult);
-            }
-
-        }
-    }
-
-}
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java
deleted file mode 100644
index 18442961ac5..00000000000
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TypeUtilTest.java
+++ /dev/null
@@ -1,234 +0,0 @@
-/* Copyright 2020 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.keras.utils;
-
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
-import org.tensorflow.DataType;
-import org.tensorflow.types.TBfloat16;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat16;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TString;
-import org.tensorflow.types.TUint8;
-
-/**
- *
- * @author Jim Clarke
- */
-public class TypeUtilTest {
-
-    public TypeUtilTest() {
-    }
-
-    @BeforeAll
-    public static void setUpClass() {
-    }
-
-    @AfterAll
-    public static void tearDownClass() {
-    }
-
-    @BeforeEach
-    public void setUp() {
-    }
-
-    @AfterEach
-    public void tearDown() {
-    }
-
-    /**
-     * Test of isFloating method, of class TypeUtils.
-     */
-    @Test
-    public void testIsFloating() {
-        DataType dtype = TFloat32.DTYPE;
-        boolean expResult = true;
-        boolean result = TypeUtils.isFloating(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TInt32.DTYPE;
-        expResult = false;
-        result = TypeUtils.isFloating(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TString.DTYPE;
-        expResult = false;
-        result = TypeUtils.isFloating(dtype);
-        assertEquals(expResult, result);
-    }
-
-    /**
-     * Test of isInteger method, of class TypeUtils.
-     */
-    @Test
-    public void testIsInteger() {
-        DataType dtype = TFloat32.DTYPE;
-        boolean expResult = false;
-        boolean result = TypeUtils.isInteger(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TInt32.DTYPE;
-        expResult = true;
-        result = TypeUtils.isInteger(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TString.DTYPE;
-        expResult = false;
-        result = TypeUtils.isInteger(dtype);
-        assertEquals(expResult, result);
-    }
-
-    /**
-     * Test of isNumeric method, of class TypeUtils.
-     */
-    @Test
-    public void testIsNumeric() {
-        DataType dtype = TFloat16.DTYPE;
-        boolean expResult = true;
-        boolean result = TypeUtils.isNumeric(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TInt64.DTYPE;
-        expResult = true;
-        result = TypeUtils.isNumeric(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TUint8.DTYPE;
-        expResult = true;
-        result = TypeUtils.isNumeric(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TBool.DTYPE;
-        expResult = false;
-        result = TypeUtils.isNumeric(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TString.DTYPE;
-        expResult = false;
-        result = TypeUtils.isNumeric(dtype);
-        assertEquals(expResult, result);
-    }
-
-    /**
-     * Test of isBoolean method, of class TypeUtils.
-     */
-    @Test
-    public void testIsBoolean() {
-        DataType dtype = TFloat16.DTYPE;
-        boolean expResult = false;
-        boolean result = TypeUtils.isBoolean(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TInt64.DTYPE;
-        expResult = false;
-        result = TypeUtils.isBoolean(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TBool.DTYPE;
-        expResult = true;
-        result = TypeUtils.isBoolean(dtype);
-        assertEquals(expResult, result);
-    }
-
-    /**
-     * Test of isString method, of class TypeUtils.
-     */
-    @Test
-    public void testIsString() {
-        DataType dtype = TFloat16.DTYPE;
-        boolean expResult = false;
-        boolean result = TypeUtils.isString(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TBool.DTYPE;
-        expResult = false;
-        result = TypeUtils.isString(dtype);
-        assertEquals(expResult, result);
-
-        dtype = TString.DTYPE;
-        expResult = true;
-        result = TypeUtils.isString(dtype);
-        assertEquals(expResult, result);
-    }
-
-    /**
-     * Test of of method, of class TypeUtils.
-     */
-    @Test
-    public void testOf() {
-        String name = "BFLOAT16";
-        DataType expResult = TBfloat16.DTYPE;
-        DataType result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "FLOAT16";
-        expResult = TFloat16.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "FLOAT";
-        expResult = TFloat32.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "DOUBLE";
-        expResult = TFloat64.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "UINT8";
-        expResult = TUint8.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "INT32";
-        expResult = TInt32.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "INT64";
-        expResult = TInt64.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "BOOL";
-        expResult = TBool.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "STRING";
-        expResult = TString.DTYPE;
-        result = TypeUtils.of(name);
-        assertEquals(expResult, result);
-
-        name = "FOO";
-        try {
-            TypeUtils.of(name);
-            fail("IllegalArgumentException not thrown.");
-        } catch (IllegalArgumentException expected) {
-
-        }
-
-    }
-
-}

From 6515c248ddd8f6911f267bee0972d44ca20f0038 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 13:51:04 -0400
Subject: [PATCH 17/33] Added nn.raw group for softmaxCrossEntropyWithLogits()
 and sparseSoftmaxCrossEntropyWithLogits()

---
 .../org/tensorflow/op/NnRawOps.java           | 74 +++++++++++++++++++
 1 file changed, 74 insertions(+)
 create mode 100644 tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnRawOps.java

diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnRawOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnRawOps.java
new file mode 100644
index 00000000000..d9147af3934
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnRawOps.java
@@ -0,0 +1,74 @@
+// Copyright 2020 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.
+// ==============================================================================
+//
+// This class has been generated, DO NOT EDIT!
+//
+package org.tensorflow.op;
+
+import org.tensorflow.Operand;
+import org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits;
+import org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits;
+import org.tensorflow.types.family.TNumber;
+
+/**
+ * An API for building {@code nn.raw} operations as {@link Op Op}s
+ *
+ * @see {@link Ops}
+ */
+public final class NnRawOps {
+  private final Scope scope;
+
+  NnRawOps(Scope scope) {
+    this.scope = scope;
+  }
+
+  /**
+   * Computes softmax cross entropy cost and gradients to backpropagate.
+   *  

+   *  Inputs are the logits, not probabilities.
+   *
+   * @param  data type for {@code loss()} output
+   * @param features batch_size x num_classes matrix
+   * @param labels batch_size x num_classes matrix
+   *  The caller must ensure that each batch of labels represents a valid
+   *  probability distribution.
+   * @return a new instance of SoftmaxCrossEntropyWithLogits
+   */
+  public  SoftmaxCrossEntropyWithLogits softmaxCrossEntropyWithLogits(
+      Operand features, Operand labels) {
+    return SoftmaxCrossEntropyWithLogits.create(scope, features, labels);
+  }
+
+  /**
+   * Computes softmax cross entropy cost and gradients to backpropagate.
+   *  

+   *  Unlike `SoftmaxCrossEntropyWithLogits`, this operation does not accept
+   *  a matrix of label probabilities, but rather a single label per row
+   *  of features.  This label is considered to have probability 1.0 for the
+   *  given row.
+   *  

+   *  Inputs are the logits, not probabilities.
+   *
+   * @param  data type for {@code loss()} output
+   * @param features batch_size x num_classes matrix
+   * @param labels batch_size vector with values in [0, num_classes).
+   *  This is the label for the given minibatch entry.
+   * @return a new instance of SparseSoftmaxCrossEntropyWithLogits
+   */
+  public  SparseSoftmaxCrossEntropyWithLogits sparseSoftmaxCrossEntropyWithLogits(
+      Operand features, Operand labels) {
+    return SparseSoftmaxCrossEntropyWithLogits.create(scope, features, labels);
+  }
+}

From 76d0fe553559176a33040b4bdb8e07d8e033b08e Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 20 Aug 2020 14:30:16 -0400
Subject: [PATCH 18/33] Added nn.raw group for softmaxCrossEntropyWithLogits()
 and sparseSoftmaxCrossEntropyWithLogits()

---
 .../src/gen/annotations/org/tensorflow/op/NnOps.java           | 3 ---
 1 file changed, 3 deletions(-)

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 a0910d4be33..aa34027cdc5 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
@@ -103,14 +103,11 @@
 public final class NnOps {
   public final NnRawOps raw;
 
-  public final NnInternalOps internal;
-
   private final Scope scope;
 
   NnOps(Scope scope) {
     this.scope = scope;
     raw = new NnRawOps(scope);
-    internal = new NnInternalOps(scope);
   }
 
   /**

From ab379d1b49d90bb42c8654f2e0cf0c258e0d3406 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 10:21:27 -0400
Subject: [PATCH 19/33] Refactor NN into individual operations under
 org.tensorflow.op.nn. Fix JavaDoc. Change from snake case to camel case.

---
 .../op/nn/SigmoidCrossEntropyWithLogits.java  |  83 +++++++
 .../op/nn/SoftmaxCrossEntropyWithLogits.java  | 215 ++++++++++++++++++
 .../SparseSoftmaxCrossEntropyWithLogits.java  | 161 +++++++++++++
 3 files changed, 459 insertions(+)
 create mode 100644 tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
 create mode 100644 tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
 create mode 100644 tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
new file mode 100644
index 00000000000..1e8f3dd7907
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
@@ -0,0 +1,83 @@
+package org.tensorflow.op.nn;
+
+import org.tensorflow.Operand;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.op.core.Select;
+import org.tensorflow.op.core.ZerosLike;
+import org.tensorflow.op.dtypes.Cast;
+import org.tensorflow.op.math.*;
+import org.tensorflow.types.TBool;
+import org.tensorflow.types.family.TNumber;
+
+@Operator(group = "nn")
+public class SigmoidCrossEntropyWithLogits {
+
+  /**
+   * Computes sigmoid cross entropy given logits.
+   *
+   * 
Measures the probability error in discrete classification tasks in which each class is
+   * independent and not mutually exclusive. For instance, one could perform multilabel
+   * classification where a picture can contain both an elephant and a dog at the same time.
+   *
+   * 
For brevity, let x = logits, z = labels. The logistic loss in
+   * pseudo-code is
+   *
+   * 
+   * z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
+   *  = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
+   *  = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
+   *  = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
+   *  = (1 - z) * x + log(1 + exp(-x))
+   *  = x - x * z + log(1 + exp(-x))
+   * 

+   *
+   * 
For x < 0, to avoid overflow in exp(-x), we reformulate the above
+   *
+   * 
+   * x - x * z + log(1 + exp(-x))
+   *  = log(exp(x)) - x * z + log(1 + exp(-x))
+   *  = - x * z + log(1 + exp(x))
+   * 

+   *
+   * 
Hence, to ensure stability and avoid overflow, the implementation uses this equivalent
+   * formulation
+   *
+   * 
+   *   max(x, 0) - x * z + log(1 + exp(-abs(x)))
+   * 

+   *
+   * 
logits and labels must have the same type and shape.
+   *
+   * 

+   *
+   * @param scope The TensorFlow scope
+   * @param labels the labels
+   * @param logits the logits of type float32 or float64
+   * @param  the type of labels and logits
+   * @return the component-wise logistic losses.
+   * @throws IllegalArgumentException if logits' and labels' do not have the same shape
+   */
+  @Endpoint(name = "sigmoidCrossEntropyWithLogits")
+  public static  Operand sigmoidCrossEntropyWithLogits(
+      Scope scope, Operand labels, Operand logits) {
+    if (!labels.asOutput().shape().equals(logits.asOutput().shape())) {
+      throw new IllegalArgumentException(
+          String.format(
+              "logits and labels must have the same shape (%s vs %s)",
+              labels.asOutput().shape().toString(), logits.asOutput().shape()));
+    }
+
+    Operand zeros =
+        Cast.create(scope, ZerosLike.create(scope, logits), logits.asOutput().dataType());
+    Operand cond = GreaterEqual.create(scope, logits, zeros);
+
+    Operand relu_logits = Select.create(scope, cond, logits, zeros);
+    Operand neg_abs_logits = Select.create(scope, cond, Neg.create(scope, logits), logits);
+    return Add.create(
+        scope,
+        Sub.create(scope, relu_logits, Mul.create(scope, logits, labels)),
+        Log1p.create(scope, Exp.create(scope, neg_abs_logits)));
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
new file mode 100644
index 00000000000..6d8f5ef6f78
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
@@ -0,0 +1,215 @@
+package org.tensorflow.op.nn;
+
+import org.tensorflow.DataType;
+import org.tensorflow.Operand;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.op.core.*;
+import org.tensorflow.op.dtypes.Cast;
+import org.tensorflow.op.linalg.Transpose;
+import org.tensorflow.op.math.Sub;
+import org.tensorflow.types.TBfloat16;
+import org.tensorflow.types.TFloat16;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TNumber;
+import org.tensorflow.types.family.TType;
+
+import java.util.Arrays;
+import java.util.List;
+
+@Operator(group = "nn")
+public class SoftmaxCrossEntropyWithLogits {
+
+  /**
+   * Computes softmax cross entropy between logits and labels.
+   *
+   * 
Measures the probability error in discrete classification tasks in which the classes are
+   * mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is
+   * labeled with one and only one label: an image can be a dog or a truck, but not both.
+   *
+   * 
NOTE:
+   *
+   * 
While the classes are mutually exclusive, their probabilities need not be. All that is
+   * required is that each row of labels is a valid probability distribution. If they
+   * are not, the computation of the gradient will be incorrect.
+   *
+   * 
If using exclusive labels (wherein one and only one class is true at a time),
+   * see {@link org.tensorflow.op.NnOps#sparseSoftmaxCrossEntropyWithLogits}
+   *
+   * 
Usage:
+   *
+   * 
+   *   Operand<TFloat32> logits =
+   *       tf.constant(new float[][] {{4.0F, 2.0F, 1.0F}, {0.0F, 5.0F, 1.0F}} );
+   *   Operand<TFloat32> labels =
+   *       tf.constant(new float[][] {{1.0F, 0.0F, 0.0F}, {0.0F, 0.8F, 0.2F}} );
+   *   Operand<TFloat32> output =
+   *       tf.nn.softmaxCrossEntropyWithLogits(labels, logits, -1);
+   *   // output Shape = [2]
+   *   // dataType = FLOAT (1)
+   *   // values { 0.169846, 0.824745 }
+   * 

+   *
+   * 
Backpropagation will happen into both logits and labels. To
+   * disallow backpropagation into labels, pass label tensors through 
+   * tf.stopGradient before feeding it to this function.
+   *
+   * @param scope current scope
+   * @param labels Each vector along the class dimension should hold a valid probability
+   *     distribution e.g. for the case in which labels are of shape [batch_size, num_classes]
+   *     , each row of labels[i] must be a valid probability distribution.
+   * @param logits Per-label activations, typically a linear output. These activation energies are
+   *     interpreted as unnormalized log probabilities.
+   * @param axis The class dimension. -1 is the last dimension.
+   * @param  the data type of the logits
+   * @param  the number type of the operands
+   * @return the softmax cross entropy loss. Its type is the same as logits and its
+   *     shape is the same as labels except that it does not have the last dimension of
+   *     labels.
+   */
+  @Endpoint(name = "softmaxCrossEntropyWithLogits")
+  public static  Operand softmaxCrossEntropyWithLogits(
+      Scope scope, Operand labels, Operand logits, int axis) {
+    axis = axis % logits.asOutput().shape().numDimensions();
+    if (axis < 0) {
+      axis += logits.asOutput().shape().numDimensions();
+    }
+
+    Operand preciseLogits =
+        (Operand)
+            logits; // cannot use generics cause logits of bool gets cast to TFloat32
+
+    boolean convertToFloat32 =
+        logits.asOutput().dataType() == TFloat16.DTYPE
+            || logits.asOutput().dataType() == TBfloat16.DTYPE;
+    if (convertToFloat32) {
+      preciseLogits = Cast.create(scope, logits, TFloat32.DTYPE);
+    }
+    /* cannot use generics on DataType because preciseLogits may have been cast. */
+    DataType dtype = preciseLogits.asOutput().dataType();
+    Operand castLabels = Cast.create(scope, labels, dtype);
+    Operand inputRank = Cast.create(scope, Rank.create(scope, preciseLogits), TInt64.DTYPE);
+    Shape shape = logits.asOutput().shape();
+
+    // Move the dim to the end if dim is not the last dimension.
+    if (axis != -1 && axis != preciseLogits.asOutput().shape().numDimensions() - 1) {
+      preciseLogits = moveDimToEnd(scope, preciseLogits, axis, inputRank);
+      castLabels = moveDimToEnd(scope, castLabels, axis, inputRank);
+    }
+
+    Shape inputShape = preciseLogits.asOutput().shape();
+    preciseLogits = flattenOuterDims(scope, preciseLogits);
+    castLabels = flattenOuterDims(scope, castLabels);
+
+    org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits smax =
+        org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits.create(
+            scope, preciseLogits, castLabels);
+    /* cannot use generic on cost, because cost may be recast later. */
+    Operand cost = smax.loss();
+    Operand outputShape =
+        Slice.create(
+            scope,
+            Constant.vectorOf(scope, inputShape.asArray()),
+            Constant.vectorOf(scope, new long[] {0}),
+            Constant.vectorOf(scope, new long[] {inputShape.numDimensions() - 1}));
+    cost = Reshape.create(scope, cost, outputShape);
+    if (scope.env().isGraph() && !shape.hasUnknownDimension()) {
+      long[] array = shape.asArray();
+      long[] newArray = new long[array.length - 1];
+      if (axis < 0) {
+        axis = shape.numDimensions() + axis;
+      }
+      for (int i = 0; i < axis; i++) {
+        newArray[i] = shape.size(i);
+      }
+      for (int i = axis + 1; i < shape.numDimensions(); i++) {
+        newArray[i - 1] = shape.size(i);
+      }
+      Shape newShape = Shape.of(newArray);
+      cost = Reshape.create(scope, cost, Constant.vectorOf(scope, newShape.asArray()));
+    }
+
+    if (convertToFloat32) {
+      cost = Cast.create(scope, cost, logits.asOutput().dataType());
+    }
+    return cost;
+  }
+
+  /**
+   * Flattens logits' outer dimensions and keep its last dimension.
+   *
+   * @param scope the TensorFlow scope
+   * @param logits the logits
+   * @param  the type of logits
+   * @return the flattened logits
+   */
+  private static  Operand flattenOuterDims(Scope scope, Operand logits) {
+    Operand one = Constant.scalarOf(scope, 1L);
+
+    org.tensorflow.ndarray.Shape shape = logits.asOutput().shape();
+    int ndims = shape.numDimensions();
+    if (!shape.hasUnknownDimension()) {
+      long product = 1L;
+      boolean productValid = true;
+      for (int i = ndims - 2; i >= 0; i--) {
+        long d = shape.size(i);
+        if (d == org.tensorflow.ndarray.Shape.UNKNOWN_SIZE) {
+          productValid = false;
+          break;
+        }
+        product *= d;
+      }
+      if (productValid) {
+        return Reshape.create(
+            scope, logits, Constant.vectorOf(scope, new long[] {product, shape.size(-1)}));
+      }
+    }
+
+    Operand rank = Cast.create(scope, Rank.create(scope, logits), TInt64.DTYPE);
+    Operand rankMinusOne = Sub.create(scope, rank, one);
+
+    Operand lastDimSize =
+        Slice.create(
+            scope,
+            org.tensorflow.op.core.Shape.create(scope, logits, TInt64.DTYPE),
+            rankMinusOne,
+            one);
+    Operand concat =
+        Concat.create(
+            scope,
+            Arrays.asList(Constant.arrayOf(scope, -1L), lastDimSize),
+            Constant.scalarOf(scope, 0));
+    return Reshape.create(scope, logits, concat);
+  }
+
+  /**
+   * Move the dim to the end if dimIndex is not the last dimension.
+   *
+   * @param scope The TensorFlow Scope
+   * @param input the input to reshape
+   * @param dimIndex the index to move
+   * @param rank the number of Dimensions in the tensor
+   * @param  the data type of the tensor.
+   * @param  the data type of the rank
+   * @return the reshaped input
+   */
+  private static  Operand moveDimToEnd(
+      Scope scope, Operand input, int dimIndex, Operand rank) {
+    DataType rankDType = rank.asOutput().dataType();
+    Operand one = Cast.create(scope, Constant.scalarOf(scope, 1), rankDType);
+    List> concatList =
+        Arrays.asList(
+            Range.create(
+                scope, Cast.create(scope, Constant.scalarOf(scope, dimIndex), rankDType), one, one),
+            Range.create(
+                scope,
+                Cast.create(scope, Constant.scalarOf(scope, dimIndex + 1), rankDType),
+                one,
+                one));
+    return Transpose.create(
+        scope, input, Concat.create(scope, concatList, Constant.scalarOf(scope, 0)));
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
new file mode 100644
index 00000000000..8d125235719
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
@@ -0,0 +1,161 @@
+package org.tensorflow.op.nn;
+
+import org.tensorflow.Operand;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Op;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.op.core.AssertThat;
+import org.tensorflow.op.core.Constant;
+import org.tensorflow.op.core.Reshape;
+import org.tensorflow.op.core.Shapes;
+import org.tensorflow.op.dtypes.Cast;
+import org.tensorflow.op.math.Equal;
+import org.tensorflow.types.TBfloat16;
+import org.tensorflow.types.TFloat16;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.TInt32;
+import org.tensorflow.types.family.TNumber;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+
+@Operator(group = "nn")
+public class SparseSoftmaxCrossEntropyWithLogits {
+
+  /**
+   * Computes sparse softmax cross entropy between logits and labels.
+   *
+   * 
Measures the probability error in discrete classification tasks in which the classes are
+   * mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is
+   * labeled with one and only one label: an image can be a dog or a truck, but not both.
+   *
+   * 
NOTE:
+   *
+   * 
For this operation, the probability of a given label is considered exclusive. That is, soft
+   * classes are not allowed, and the labels vector must provide a single specific
+   * index for the true class for each row of logits (each minibatch entry). For soft
+   * softmax classification with a probability distribution for each entry, {@link
+   * org.tensorflow.op.NnOps#softmaxCrossEntropyWithLogits}.
+   *
+   * 
WARNING:
+   *
+   * 
This op expects unscaled logits, since it performs a softmax on logits
+   *  internally for efficiency. Do not call this op with the output of softmax,
+   * as it will produce incorrect results.
+   *
+   * 
A common use case is to have logits of shape [batchSize, numClasses] and have
+   * labels of shape [batchSize], but higher dimensions are supported, in which case
+   * the dim-th dimension is assumed to be of size numClasses. 
+   * logits must have the dataType of TFloat16, TFloat32
+   * , or TFloat64, and labels must have the dtype of TInt32
+   * or TInt64.
+   *
+   * @param scope current scope
+   * @param labels Tensor of shape [d_0, d_1, ..., d_{r-1}] (where r
+   *      is rank of labels and result) and the dataType is TInt32
+   *     or TInt64. Each entry in labels must be an index in [0,
+   *     numClasses). Other values will raise an exception when this op is run on CPU, and
+   *     return NaN for corresponding loss and gradient rows on GPU.
+   * @param logits Per-label activations (typically a linear output) of shape [d_0, d_1, ...,
+   *     d_{r-1}, numClasses] and dataType of TFloat16, TFloat32,
+   *     or TFloat64. These activation energies are interpreted as unnormalized log
+   *     probabilities.
+   * @return A Tensor of the same shape as labels and of the same type as
+   *     logits with the softmax cross entropy loss.
+   */
+  @Endpoint(name = "sparseSoftmaxCrossEntropyWithLogits")
+  public static  Operand sparseSoftmaxCrossEntropyWithLogits(
+      Scope scope, Operand labels, Operand logits) {
+    scope = scope.withSubScope("SparseSoftmaxCrossEntropyWithLogits");
+    /** cannot use generics on preciseLogits as it may be recast later */
+    Operand preciseLogits = logits;
+    boolean convertToFloat32 =
+        logits.asOutput().dataType() == TFloat16.DTYPE
+            || logits.asOutput().dataType() == TBfloat16.DTYPE;
+    if (convertToFloat32) {
+      preciseLogits = Cast.create(scope, logits, TFloat32.DTYPE);
+    }
+    Shape labelsStaticShape = labels.asOutput().shape();
+    org.tensorflow.op.core.Shape labelsShape =
+        org.tensorflow.op.core.Shape.create(scope, labels);
+    Shape logitsShape = logits.asOutput().shape();
+    Shape logitsShortened = logitsShape.take(logitsShape.numDimensions() - 1);
+
+    boolean staticShapesFullyDefined =
+        !labelsStaticShape.hasUnknownDimension() && !logitsShortened.hasUnknownDimension();
+    if (logitsShape.numDimensions() == 0) {
+      throw new IllegalArgumentException(
+          String.format("Logits cannot be scalars - received shape %s.", logitsShape));
+    }
+    if (!logitsShape.hasUnknownDimension()
+        && !labelsStaticShape.hasUnknownDimension()
+        && labelsStaticShape.numDimensions() != logitsShape.numDimensions() - 1) {
+      throw new IllegalArgumentException(
+          String.format(
+              "Rank mismatch: Rank of labels (received %s) should equal rank of logits minus 1 (received %s).",
+              labelsStaticShape.toString(), logitsShape.toString()));
+    }
+
+    if (staticShapesFullyDefined && !labelsStaticShape.equals(logitsShortened)) {
+      throw new IllegalArgumentException(
+          String.format(
+              "Shape mismatch: The shape of labels (received %s) "
+                  + "should equal the shape of logits except for the last "
+                  + "dimension (received %s).",
+              labelsStaticShape.toString(), logitsShape.toString()));
+    }
+    // Check if no reshapes are required.
+    if (logitsShape.numDimensions() == 2) {
+      org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits smax =
+          org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits.create(
+              scope, preciseLogits, labels);
+      Operand loss = smax.loss();
+      if (logits.asOutput().dataType() == TFloat16.DTYPE) {
+        loss = Cast.create(scope, loss, TFloat16.DTYPE);
+      }
+      return loss;
+    }
+
+    List shapeChecks = new ArrayList<>();
+
+    if (!staticShapesFullyDefined) {
+      shapeChecks.add(
+          AssertThat.create(
+              scope,
+              Equal.create(
+                  scope,
+                  org.tensorflow.op.core.Shape.create(scope, labels),
+                  Shapes.take(
+                      scope,
+                      org.tensorflow.op.core.Shape.create(scope, logits),
+                      Constant.scalarOf(scope, -1))),
+              Collections.singletonList(
+                  Constant.scalarOf(
+                      scope,
+                      "Shape mismatch: The shape of labels  "
+                          + "should equal the shape of logits except for the last "
+                          + "dimension "))));
+    }
+
+    // Reshape logits to 2 dim, labels to 1 dim.
+    long numClassses = logitsShape.size(logitsShape.numDimensions() - 1);
+
+    preciseLogits =
+        Reshape.create(
+            scope, preciseLogits, Constant.vectorOf(scope, new long[] {-1, numClassses}));
+    labels = Reshape.create(scope, labels, Constant.scalarOf(scope, -1));
+    scope.withControlDependencies(shapeChecks);
+    org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits smax =
+        org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits.create(
+            scope, preciseLogits, labels);
+    Operand cost = smax.loss();
+    cost = Reshape.create(scope, cost, labelsShape);
+    if (logits.asOutput().dataType() == TFloat16.DTYPE) {
+      cost = Cast.create(scope, cost, TFloat16.DTYPE);
+    }
+    return cost;
+  }
+}

From 889d67e11ec7154605a0cb235097e30c53a5704a Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 10:21:33 -0400
Subject: [PATCH 20/33] Refactor NN into individual operations under
 org.tensorflow.op.nn. Fix JavaDoc. Change from snake case to camel case.

---
 .../main/java/org/tensorflow/op/core/NN.java  | 379 ------------------
 1 file changed, 379 deletions(-)
 delete mode 100644 tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java
deleted file mode 100644
index b4fa7bd01de..00000000000
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/NN.java
+++ /dev/null
@@ -1,379 +0,0 @@
-package org.tensorflow.op.core;
-
-import org.tensorflow.DataType;
-import org.tensorflow.Operand;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Scope;
-import org.tensorflow.op.annotation.Endpoint;
-import org.tensorflow.op.annotation.Operator;
-import org.tensorflow.op.math.*;
-import org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits;
-import org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits;
-import org.tensorflow.types.*;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.op.dtypes.Cast;
-import org.tensorflow.types.family.TType;
-import org.tensorflow.op.linalg.Transpose;
-
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.Collections;
-import java.util.List;
-
-@Operator(group = "nn")
-public abstract class NN {
-
-  /**
-   * Computes softmax cross entropy between `logits` and `labels`.
-   *
-   * 
Measures the probability error in discrete classification tasks in which the classes are
-   * mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is
-   * labeled with one and only one label: an image can be a dog or a truck, but not both.
-   *
-   * 
**NOTE:** While the classes are mutually exclusive, their probabilities need not be. All
-   * that is required is that each row of `labels` is a valid probability distribution. If they are
-   * not, the computation of the gradient will be incorrect.
-   *
-   * 
If using exclusive `labels` (wherein one and only one class is true at a time), see
-   * `sparse_softmax_cross_entropy_with_logits`.
-   *
-   * 
Usage:
-   *
-   * 
-   *   >>> logits = [[4.0, 2.0, 1.0], [0.0, 5.0, 1.0]]
-   *   >>> labels = [[1.0, 0.0, 0.0], [0.0, 0.8, 0.2]]
-   *   >>> tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits)
-   *   
-   * 

-   *
-   * 
Backpropagation will happen into both `logits` and `labels`. To disallow backpropagation
-   * into `labels`, pass label tensors through `tf.stop_gradient` before feeding it to this
-   * function.
-   *
-   * @param scope current scope
-   * @param labels Each vector along the class dimension should hold a valid probability
-   *     distribution e.g. for the case in which labels are of shape `[batch_size, num_classes]`,
-   *     each row of `labels[i]` must be a valid probability distribution.
-   * @param logits Per-label activations, typically a linear output. These activation energies are
-   *     interpreted as unnormalized log probabilities.
-   * @param axis The class dimension. -1 is the last dimension.
-   * @param  the data type of the logits
-   * @param  the number type of the operands
-   * @return the softmax cross entropy loss. Its type is the same as `logits` and its shape is the
-   *     same as `labels` except that it does not have the last dimension of `labels`.
-   */
-  @Endpoint(name = "softmaxCrossEntropyWithLogits")
-  public static  Operand softmaxCrossEntropyWithLogits(
-      Scope scope, Operand labels, Operand logits, int axis) {
-    axis = axis % logits.asOutput().shape().numDimensions();
-    if (axis < 0) {
-      axis += logits.asOutput().shape().numDimensions();
-    }
-
-    Operand precise_logits =
-        logits; // cannot use generics cause logits of bool gets cast to TFloat32
-
-    boolean convertToFloat32 =
-        logits.asOutput().dataType() == TFloat16.DTYPE
-            || logits.asOutput().dataType() == TBfloat16.DTYPE;
-    if (convertToFloat32) {
-      precise_logits = Cast.create(scope, logits, TFloat32.DTYPE);
-    }
-    /* cannot use generics on DataType because precis_logits may have been cast. */
-    DataType dtype = precise_logits.asOutput().dataType();
-    labels = Cast.create(scope, labels, dtype);
-    Operand inputRank =
-        Cast.create(scope, Rank.create(scope, precise_logits), TInt64.DTYPE);
-    Shape shape = logits.asOutput().shape();
-
-    // Move the dim to the end if dim is not the last dimension.
-    if (axis != -1 && axis != precise_logits.asOutput().shape().numDimensions() - 1) {
-      precise_logits = moveDimToEnd(scope, precise_logits, axis, inputRank);
-      labels = moveDimToEnd(scope, labels, axis, inputRank);
-    }
-
-    Shape inputShape = precise_logits.asOutput().shape();
-    precise_logits = flattenOuterDims(scope, precise_logits);
-    labels = flattenOuterDims(scope, labels);
-    SoftmaxCrossEntropyWithLogits smax =
-        SoftmaxCrossEntropyWithLogits.create(scope, precise_logits, labels);
-    /* cannot use generic on cost, because cost may be recast later. */
-    Operand cost = smax.loss();
-    Operand outputShape =
-        Slice.create(
-            scope,
-            Constant.vectorOf(scope, inputShape.asArray()),
-            Constant.vectorOf(scope, new long[] {0}),
-            Constant.vectorOf(scope, new long[] {inputShape.numDimensions() - 1}));
-    cost = Reshape.create(scope, cost, outputShape);
-    if (scope.env().isGraph() && !shape.hasUnknownDimension()) {
-      long[] array = shape.asArray();
-      long[] newArray = new long[array.length - 1];
-      if (axis < 0) {
-        axis = shape.numDimensions() + axis;
-      }
-      for (int i = 0; i < axis; i++) {
-        newArray[i] = shape.size(i);
-      }
-      for (int i = axis + 1; i < shape.numDimensions(); i++) {
-        newArray[i - 1] = shape.size(i);
-      }
-      Shape newShape = Shape.of(newArray);
-      cost = Reshape.create(scope, cost, Constant.vectorOf(scope, newShape.asArray()));
-    }
-
-    if (convertToFloat32) {
-      cost = Cast.create(scope, cost, logits.asOutput().dataType());
-    }
-    return cost;
-  }
-
-  /**
-   * Computes sparse softmax cross entropy between `logits` and `labels`.
-   *
-   * @param scope current scope
-   * @param labels `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of `labels` and
-   *     result) and dtype `int32` or `int64`. Each entry in `labels` must be an index in `[0,
-   *     num_classes)`. Other values will raise an exception when this op is run on CPU, and return
-   *     `NaN` for corresponding loss and gradient rows on GPU.
-   * @param logits Per-label activations (typically a linear output) of shape `[d_0, d_1, ...,
-   *     d_{r-1}, num_classes]` and dtype `float16`, `float32`, or `float64`. These activation
-   *     energies are interpreted as unnormalized log probabilities.
-   * @return A `Tensor` of the same shape as `labels` and of the same type as `logits` with the
-   *     softmax cross entropy loss.
-   */
-  @Endpoint(name = "sparseSoftmaxCrossEntropyWithLogits")
-  public static  Operand sparseSoftmaxCrossEntropyWithLogits(
-      Scope scope, Operand labels, Operand logits) {
-    // assert shapeIsCompatible(labels.asOutput().shape(), logits.asOutput().shape()):
-    //        String.format("Shapes %s and %s are incompatible",
-    //                labels.asOutput().shape(), logits.asOutput().shape());
-    scope = scope.withSubScope("SparseSoftmaxCrossEntropyWithLogits");
-    /** cannot use generics on precise_logits as it may be recast later */
-    Operand precise_logits = logits;
-    boolean convertToFloat32 =
-        logits.asOutput().dataType() == TFloat16.DTYPE
-            || logits.asOutput().dataType() == TBfloat16.DTYPE;
-    if (convertToFloat32) {
-      precise_logits = Cast.create(scope, logits, TFloat32.DTYPE);
-    }
-    Shape labelsStaticShape = labels.asOutput().shape();
-    org.tensorflow.op.core.Shape labelsShape =
-        org.tensorflow.op.core.Shape.create(scope, labels);
-    Shape logitsShape = logits.asOutput().shape();
-    Shape logitsShortened = logitsShape.take(logitsShape.numDimensions() - 1);
-
-    boolean staticShapesFullyDefined =
-        !labelsStaticShape.hasUnknownDimension() && !logitsShortened.hasUnknownDimension();
-    if (logitsShape.numDimensions() == 0) {
-      throw new IllegalArgumentException(
-          String.format("Logits cannot be scalars - received shape %s.", logitsShape));
-    }
-    if (!logitsShape.hasUnknownDimension()
-        && !labelsStaticShape.hasUnknownDimension()
-        && labelsStaticShape.numDimensions() != logitsShape.numDimensions() - 1) {
-      throw new IllegalArgumentException(
-          String.format(
-              "Rank mismatch: Rank of labels (received %s) should equal rank of logits minus 1 (received %s).",
-              labelsStaticShape.toString(), logitsShape.toString()));
-    }
-
-    if (staticShapesFullyDefined && !labelsStaticShape.equals(logitsShortened)) {
-      throw new IllegalArgumentException(
-          String.format(
-              "Shape mismatch: The shape of labels (received %s) "
-                  + "should equal the shape of logits except for the last "
-                  + "dimension (received %s).",
-              labelsStaticShape.toString(), logitsShape.toString()));
-    }
-    // Check if no reshapes are required.
-    if (logitsShape.numDimensions() == 2) {
-      SparseSoftmaxCrossEntropyWithLogits smax =
-          SparseSoftmaxCrossEntropyWithLogits.create(scope, precise_logits, labels);
-      Operand loss = smax.loss();
-      if (logits.asOutput().dataType() == TFloat16.DTYPE) {
-        loss = Cast.create(scope, loss, TFloat16.DTYPE);
-      }
-      return loss;
-    }
-
-    List shapeChecks = new ArrayList<>();
-
-    if (!staticShapesFullyDefined) {
-      shapeChecks.add(
-          AssertThat.create(
-              scope,
-              Equal.create(
-                  scope,
-                  org.tensorflow.op.core.Shape.create(scope, labels),
-                  Shapes.take(
-                      scope,
-                      org.tensorflow.op.core.Shape.create(scope, logits),
-                      Constant.scalarOf(scope, -1))),
-              Collections.singletonList(
-                  Constant.scalarOf(
-                      scope,
-                      "Shape mismatch: The shape of labels  "
-                          + "should equal the shape of logits except for the last "
-                          + "dimension "))));
-    }
-
-    // Reshape logits to 2 dim, labels to 1 dim.
-    long numClassses = logitsShape.size(logitsShape.numDimensions() - 1);
-
-    precise_logits =
-        Reshape.create(
-            scope, precise_logits, Constant.vectorOf(scope, new long[] {-1, numClassses}));
-    labels = Reshape.create(scope, labels, Constant.scalarOf(scope, -1));
-    scope.withControlDependencies(shapeChecks);
-    SparseSoftmaxCrossEntropyWithLogits smax =
-        SparseSoftmaxCrossEntropyWithLogits.create(scope, precise_logits, labels);
-    Operand cost = smax.loss();
-    cost = Reshape.create(scope, cost, labelsShape);
-    if (logits.asOutput().dataType() == TFloat16.DTYPE) {
-      cost = Cast.create(scope, cost, TFloat16.DTYPE);
-    }
-    return cost;
-  }
-
-  /**
-   * Computes sigmoid cross entropy given `logits`.
-   *
-   * 
Measures the probability error in discrete classification tasks in which each class is
-   * independent and not mutually exclusive. For instance, one could perform multilabel
-   * classification where a picture can contain both an elephant and a dog at the same time.
-   *
-   * 
For brevity, let `x = logits`, `z = labels`. The logistic loss is
-   *
-   * 
-   *     z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
-   *     = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
-   *     = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
-   *     = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
-   *     = (1 - z) * x + log(1 + exp(-x))
-   *     = x - x * z + log(1 + exp(-x))
-   * 

-   *
-   * 
For x < 0, to avoid overflow in exp(-x), we reformulate the above
-   *
-   * 
-   *      x - x * z + log(1 + exp(-x))
-   *      = log(exp(x)) - x * z + log(1 + exp(-x))
-   *      = - x * z + log(1 + exp(x))
-   * 

-   *
-   * 
Hence, to ensure stability and avoid overflow, the implementation uses this equivalent
-   * formulation
-   *
-   * 
-   *     max(x, 0) - x * z + log(1 + exp(-abs(x)))
-   * 

-   *
-   * 
`logits` and `labels` must have the same type and shape.
-   *
-   * @param scope The TensorFlow scope
-   * @param labels the labels
-   * @param logits the logits of type float32 or float64
-   * @param  the type of labels and logits
-   * @return the component-wise logistic losses.
-   */
-  @Endpoint(name = "sigmoidCrossEntropyWithLogits")
-  public static  Operand sigmoidCrossEntropyWithLogits(
-      Scope scope, Operand labels, Operand logits) {
-    if (labels.asOutput().shape().numDimensions() != logits.asOutput().shape().numDimensions())
-      throw new IllegalArgumentException(
-          String.format(
-              "logits and labels must have the same shape (%s vs %s)",
-              labels.asOutput().shape().toString(), logits.asOutput().shape()));
-    Operand zeros =
-        Cast.create(scope, ZerosLike.create(scope, logits), logits.asOutput().dataType());
-    Operand cond = GreaterEqual.create(scope, logits, zeros);
-
-    Operand relu_logits = Select.create(scope, cond, logits, zeros);
-    Operand neg_abs_logits = Select.create(scope, cond, Neg.create(scope, logits), logits);
-    return Add.create(
-        scope,
-        Sub.create(scope, relu_logits, Mul.create(scope, logits, labels)),
-        Log1p.create(scope, Exp.create(scope, neg_abs_logits)));
-  }
-
-  /**
-   * Flattens logits' outer dimensions and keep its last dimension.
-   *
-   * @param scope the TensorFlow scope
-   * @param logits the logits
-   * @param  the type of logits
-   * @return the flattened logits
-   */
-  private static  Operand flattenOuterDims(Scope scope, Operand logits) {
-    Operand one = Constant.scalarOf(scope, 1L);
-
-    org.tensorflow.ndarray.Shape shape = logits.asOutput().shape();
-    int ndims = shape.numDimensions();
-    if (!shape.hasUnknownDimension()) {
-      long product = 1L;
-      boolean productValid = true;
-      for (int i = ndims - 2; i >= 0; i--) {
-        long d = shape.size(i);
-        if (d == org.tensorflow.ndarray.Shape.UNKNOWN_SIZE) {
-          productValid = false;
-          break;
-        }
-        product *= d;
-      }
-      if (productValid) {
-        org.tensorflow.ndarray.Shape outputShape = Shape.of(product, shape.size(ndims - 1));
-        return Reshape.create(scope, logits, Constant.vectorOf(scope, outputShape.asArray()));
-      }
-    }
-
-    Operand rank = Cast.create(scope, Rank.create(scope, logits), TInt64.DTYPE);
-    Operand rankMinusOne = Sub.create(scope, rank, one);
-
-    Operand last_dim_size =
-        Slice.create(
-            scope,
-            org.tensorflow.op.core.Shape.create(scope, logits, TInt64.DTYPE),
-            rankMinusOne,
-            one);
-    Operand concat =
-        Concat.create(
-            scope,
-            Arrays.asList(Constant.vectorOf(scope, new long[] {-1}), last_dim_size),
-            Constant.scalarOf(scope, 0));
-    return Reshape.create(scope, logits, concat);
-  }
-
-  /**
-   * Move the dim to the end if dim is not the last dimension.
-   *
-   * @param scope The TensorFlow Scope
-   * @param input the input to reshape
-   * @param dim_index the index to move
-   * @param rank the number of Dimensions in the tensor
-   * @param  the data type of the tensor.
-   * @param  the data type of the rank
-   * @return the reshaped input
-   */
-  private static  Operand moveDimToEnd(
-      Scope scope, Operand input, int dim_index, Operand rank) {
-    DataType rankDType = rank.asOutput().dataType();
-    Operand one = Cast.create(scope, Constant.scalarOf(scope, 1), rankDType);
-    List> concatList =
-        Arrays.asList(
-            Range.create(
-                scope,
-                Cast.create(scope, Constant.scalarOf(scope, dim_index), rankDType),
-                one,
-                one),
-            Range.create(
-                scope,
-                Cast.create(scope, Constant.scalarOf(scope, (dim_index + 1)), rankDType),
-                rank,
-                one));
-    return Transpose.create(
-        scope, input, Concat.create(scope, concatList, Constant.scalarOf(scope, 0)));
-  }
-}

From 515b799bf793fbb38a47b5aa92d948dad052187b Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 10:34:57 -0400
Subject: [PATCH 21/33] Reformatted code

---
 .../src/main/java/org/tensorflow/types/TBool.java     |  9 +++++----
 .../src/main/java/org/tensorflow/types/TString.java   | 11 ++++++-----
 2 files changed, 11 insertions(+), 9 deletions(-)

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
index bac5fb96f87..3cc72101893 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
@@ -17,21 +17,22 @@
 
 package org.tensorflow.types;
 
-import java.util.function.Consumer;
 import org.tensorflow.DataType;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
 import org.tensorflow.internal.buffer.TensorBuffers;
 import org.tensorflow.internal.c_api.TF_Tensor;
-import org.tensorflow.ndarray.buffer.layout.DataLayouts;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.ndarray.buffer.BooleanDataBuffer;
 import org.tensorflow.ndarray.BooleanNdArray;
 import org.tensorflow.ndarray.NdArray;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
+import org.tensorflow.ndarray.buffer.BooleanDataBuffer;
+import org.tensorflow.ndarray.buffer.layout.DataLayouts;
 import org.tensorflow.ndarray.impl.dense.BooleanDenseNdArray;
 import org.tensorflow.types.family.TType;
 
+import java.util.function.Consumer;
+
 /**
  * Boolean tensor type.
  *
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
index 0f097a16ddb..6e2e7a7ba56 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
@@ -17,23 +17,24 @@
 
 package org.tensorflow.types;
 
-import java.nio.charset.Charset;
-import java.nio.charset.StandardCharsets;
-import java.util.function.Function;
 import org.tensorflow.DataType;
 import org.tensorflow.Tensor;
 import org.tensorflow.internal.buffer.StringTensorBuffer;
 import org.tensorflow.internal.buffer.TensorBuffers;
 import org.tensorflow.internal.c_api.TF_Tensor;
+import org.tensorflow.ndarray.NdArray;
+import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.buffer.DataBuffer;
 import org.tensorflow.ndarray.buffer.layout.DataLayout;
 import org.tensorflow.ndarray.buffer.layout.DataLayouts;
-import org.tensorflow.ndarray.NdArray;
-import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.impl.dense.DenseNdArray;
 import org.tensorflow.types.family.TType;
 
+import java.nio.charset.Charset;
+import java.nio.charset.StandardCharsets;
+import java.util.function.Function;
+
 /**
  * String type.
  *

From 5a9fe3747b730cbfb28b544bcac3aeb2077499a2 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 10:35:19 -0400
Subject: [PATCH 22/33] Added sub scope

---
 .../java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java | 1 +
 .../java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java | 1 +
 2 files changed, 2 insertions(+)

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
index 1e8f3dd7907..1918e55a2f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
@@ -68,6 +68,7 @@ public static  Operand sigmoidCrossEntropyWithLogits(
               "logits and labels must have the same shape (%s vs %s)",
               labels.asOutput().shape().toString(), logits.asOutput().shape()));
     }
+    scope = scope.withSubScope("SigmoidCrossEntropyWithLogits");
 
     Operand zeros =
         Cast.create(scope, ZerosLike.create(scope, logits), logits.asOutput().dataType());
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
index 6d8f5ef6f78..124b520aac8 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
@@ -73,6 +73,7 @@ public class SoftmaxCrossEntropyWithLogits {
   @Endpoint(name = "softmaxCrossEntropyWithLogits")
   public static  Operand softmaxCrossEntropyWithLogits(
       Scope scope, Operand labels, Operand logits, int axis) {
+    scope = scope.withSubScope("SoftmaxCrossEntropyWithLogits");
     axis = axis % logits.asOutput().shape().numDimensions();
     if (axis < 0) {
       axis += logits.asOutput().shape().numDimensions();

From 8d21dd7266e48a4df36813ed3fb9dc1adee58915 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 12:30:10 -0400
Subject: [PATCH 23/33] Miscellaneous fixes based on review comments.

---
 .../op/nn/SigmoidCrossEntropyWithLogits.java  | 34 ++++++++++++++++---
 .../op/nn/SoftmaxCrossEntropyWithLogits.java  | 14 ++++----
 .../SparseSoftmaxCrossEntropyWithLogits.java  | 10 +++---
 3 files changed, 40 insertions(+), 18 deletions(-)

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
index 1918e55a2f7..4f3e9569103 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
@@ -1,6 +1,7 @@
 package org.tensorflow.op.nn;
 
 import org.tensorflow.Operand;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -62,7 +63,7 @@ public class SigmoidCrossEntropyWithLogits {
   @Endpoint(name = "sigmoidCrossEntropyWithLogits")
   public static  Operand sigmoidCrossEntropyWithLogits(
       Scope scope, Operand labels, Operand logits) {
-    if (!labels.asOutput().shape().equals(logits.asOutput().shape())) {
+    if (!isCompatible(labels.asOutput().shape(), logits.asOutput().shape())) {
       throw new IllegalArgumentException(
           String.format(
               "logits and labels must have the same shape (%s vs %s)",
@@ -74,11 +75,34 @@ public static  Operand sigmoidCrossEntropyWithLogits(
         Cast.create(scope, ZerosLike.create(scope, logits), logits.asOutput().dataType());
     Operand cond = GreaterEqual.create(scope, logits, zeros);
 
-    Operand relu_logits = Select.create(scope, cond, logits, zeros);
-    Operand neg_abs_logits = Select.create(scope, cond, Neg.create(scope, logits), logits);
+    Operand reluLogits = Select.create(scope, cond, logits, zeros);
+    Operand negAbsLogits = Select.create(scope, cond, Neg.create(scope, logits), logits);
     return Add.create(
         scope,
-        Sub.create(scope, relu_logits, Mul.create(scope, logits, labels)),
-        Log1p.create(scope, Exp.create(scope, neg_abs_logits)));
+        Sub.create(scope, reluLogits, Mul.create(scope, logits, labels)),
+        Log1p.create(scope, Exp.create(scope, negAbsLogits)));
+  }
+  /**
+   * Determine if 2 shapes are compatible
+   *
+   * 
2 shapes are compatible if they have the same number of dimensions, and if the corresponding
+   * dimensions are equal, or at least one of the corresponding dimensions is unknown.
+   *
+   * @param shape the first shape
+   * @param other the second shape
+   * @return true, if the shapes are compatible.
+   */
+  private static boolean isCompatible(Shape shape, Shape other) {
+    if (shape.numDimensions() != other.numDimensions()) return false;
+    for (int i = 0; i < shape.numDimensions(); i++) {
+      long aShapeDim = shape.size(i);
+      long bShapeDim = other.size(i);
+      if (aShapeDim == bShapeDim
+          || (aShapeDim == Shape.UNKNOWN_SIZE || bShapeDim == Shape.UNKNOWN_SIZE)) {
+        continue;
+      }
+      return false;
+    }
+    return true;
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
index 124b520aac8..f3caa0c4926 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
@@ -113,9 +113,9 @@ public static  Operand softmaxCrossEntrop
     Operand outputShape =
         Slice.create(
             scope,
-            Constant.vectorOf(scope, inputShape.asArray()),
-            Constant.vectorOf(scope, new long[] {0}),
-            Constant.vectorOf(scope, new long[] {inputShape.numDimensions() - 1}));
+            Constant.tensorOf(scope, inputShape),
+            Constant.arrayOf(scope, 0L),
+            Constant.arrayOf(scope, inputShape.numDimensions() - 1L));
     cost = Reshape.create(scope, cost, outputShape);
     if (scope.env().isGraph() && !shape.hasUnknownDimension()) {
       long[] array = shape.asArray();
@@ -129,8 +129,7 @@ public static  Operand softmaxCrossEntrop
       for (int i = axis + 1; i < shape.numDimensions(); i++) {
         newArray[i - 1] = shape.size(i);
       }
-      Shape newShape = Shape.of(newArray);
-      cost = Reshape.create(scope, cost, Constant.vectorOf(scope, newShape.asArray()));
+      cost = Reshape.create(scope, cost, Constant.vectorOf(scope, newArray));
     }
 
     if (convertToFloat32) {
@@ -150,7 +149,7 @@ public static  Operand softmaxCrossEntrop
   private static  Operand flattenOuterDims(Scope scope, Operand logits) {
     Operand one = Constant.scalarOf(scope, 1L);
 
-    org.tensorflow.ndarray.Shape shape = logits.asOutput().shape();
+    Shape shape = logits.asOutput().shape();
     int ndims = shape.numDimensions();
     if (!shape.hasUnknownDimension()) {
       long product = 1L;
@@ -164,8 +163,7 @@ private static  Operand flattenOuterDims(Scope scope, Oper
         product *= d;
       }
       if (productValid) {
-        return Reshape.create(
-            scope, logits, Constant.vectorOf(scope, new long[] {product, shape.size(-1)}));
+        return Reshape.create(scope, logits, Constant.arrayOf(scope, product, shape.size(-1)));
       }
     }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
index 8d125235719..ebd6f74e7d8 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
@@ -65,6 +65,8 @@ public class SparseSoftmaxCrossEntropyWithLogits {
    *     probabilities.
    * @return A Tensor of the same shape as labels and of the same type as
    *     logits with the softmax cross entropy loss.
+   * @throws IllegalArgumentException If logits are scalars (need to have rank >= 1) or if the rank
+   *     of the labels is not equal to the rank of the logits minus one.
    */
   @Endpoint(name = "sparseSoftmaxCrossEntropyWithLogits")
   public static  Operand sparseSoftmaxCrossEntropyWithLogits(
@@ -140,12 +142,10 @@ public static  Operand sparseSoftmaxCrossE
                           + "dimension "))));
     }
 
-    // Reshape logits to 2 dim, labels to 1 dim.
-    long numClassses = logitsShape.size(logitsShape.numDimensions() - 1);
+    // Reshape logits to 2 dims, labels to 1 dim.
+    long numClassses = logitsShape.size(-1);
 
-    preciseLogits =
-        Reshape.create(
-            scope, preciseLogits, Constant.vectorOf(scope, new long[] {-1, numClassses}));
+    preciseLogits = Reshape.create(scope, preciseLogits, Constant.arrayOf(scope, -1L, numClassses));
     labels = Reshape.create(scope, labels, Constant.scalarOf(scope, -1));
     scope.withControlDependencies(shapeChecks);
     org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits smax =

From 4c3cc78a999505240be35040b8865d86b955e1af Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 18:52:11 -0400
Subject: [PATCH 24/33] Fixed op_generator.cc to remove a spurious new line in
 the generated Java files for some Ops. This also  resulted in new generated 
 source that are also committed.

---
 .../src/bazel/op_generator/op_generator.cc             | 10 +++++++---
 .../src/gen/java/org/tensorflow/op/core/Abort.java     |  1 -
 .../gen/java/org/tensorflow/op/core/AssertThat.java    |  1 -
 .../org/tensorflow/op/core/AssignAddVariableOp.java    |  1 -
 .../org/tensorflow/op/core/AssignSubVariableOp.java    |  1 -
 .../java/org/tensorflow/op/core/AssignVariableOp.java  |  1 -
 .../gen/java/org/tensorflow/op/core/BarrierClose.java  |  1 -
 .../java/org/tensorflow/op/core/BarrierInsertMany.java |  1 -
 .../java/org/tensorflow/op/core/ConsumeMutexLock.java  |  1 -
 .../java/org/tensorflow/op/core/ControlTrigger.java    |  1 -
 .../org/tensorflow/op/core/DeleteSessionTensor.java    |  1 -
 .../java/org/tensorflow/op/core/DestroyResourceOp.java |  1 -
 .../gen/java/org/tensorflow/op/core/DeviceIndex.java   |  3 +++
 .../java/org/tensorflow/op/core/InitializeTable.java   |  1 -
 .../op/core/InitializeTableFromTextFile.java           |  1 -
 .../java/org/tensorflow/op/core/LookupTableImport.java |  1 -
 .../java/org/tensorflow/op/core/LookupTableInsert.java |  1 -
 .../java/org/tensorflow/op/core/LookupTableRemove.java |  1 -
 .../src/gen/java/org/tensorflow/op/core/MapClear.java  |  1 -
 .../src/gen/java/org/tensorflow/op/core/MapStage.java  |  1 -
 .../src/gen/java/org/tensorflow/op/core/NoOp.java      |  1 -
 .../java/org/tensorflow/op/core/OrderedMapClear.java   |  1 -
 .../java/org/tensorflow/op/core/OrderedMapStage.java   |  1 -
 .../src/gen/java/org/tensorflow/op/core/Print.java     |  1 -
 .../org/tensorflow/op/core/ResourceScatterAdd.java     |  1 -
 .../org/tensorflow/op/core/ResourceScatterDiv.java     |  1 -
 .../org/tensorflow/op/core/ResourceScatterMax.java     |  1 -
 .../org/tensorflow/op/core/ResourceScatterMin.java     |  1 -
 .../org/tensorflow/op/core/ResourceScatterMul.java     |  1 -
 .../org/tensorflow/op/core/ResourceScatterNdAdd.java   |  1 -
 .../org/tensorflow/op/core/ResourceScatterNdMax.java   |  2 ++
 .../org/tensorflow/op/core/ResourceScatterNdMin.java   |  2 ++
 .../org/tensorflow/op/core/ResourceScatterNdSub.java   |  1 -
 .../tensorflow/op/core/ResourceScatterNdUpdate.java    |  1 -
 .../org/tensorflow/op/core/ResourceScatterSub.java     |  1 -
 .../org/tensorflow/op/core/ResourceScatterUpdate.java  |  1 -
 .../tensorflow/op/core/ResourceStridedSliceAssign.java |  1 -
 .../gen/java/org/tensorflow/op/core/ScatterNdMax.java  |  3 +++
 .../gen/java/org/tensorflow/op/core/ScatterNdMin.java  |  3 +++
 .../src/gen/java/org/tensorflow/op/core/Send.java      |  1 -
 .../src/gen/java/org/tensorflow/op/core/Stage.java     |  1 -
 .../gen/java/org/tensorflow/op/core/StageClear.java    |  1 -
 .../java/org/tensorflow/op/core/TensorArrayClose.java  |  1 -
 .../op/core/TensorForestCreateTreeVariable.java        |  1 -
 .../op/core/TensorForestTreeDeserialize.java           |  1 -
 .../org/tensorflow/op/core/TensorScatterNdMax.java     |  3 +++
 .../org/tensorflow/op/core/TensorScatterNdMin.java     |  3 +++
 .../tensorflow/op/core/XlaSpmdFullToShardShape.java    |  3 +++
 .../tensorflow/op/core/XlaSpmdShardToFullShape.java    |  3 +++
 .../java/org/tensorflow/op/data/DatasetToTfRecord.java |  1 -
 .../java/org/tensorflow/op/data/DeleteIterator.java    |  1 -
 .../java/org/tensorflow/op/data/DeleteMemoryCache.java |  1 -
 .../tensorflow/op/data/DeleteMultiDeviceIterator.java  |  1 -
 .../org/tensorflow/op/data/DeserializeIterator.java    |  1 -
 .../tensorflow/op/data/InitializeTableFromDataset.java |  2 ++
 .../gen/java/org/tensorflow/op/data/MakeIterator.java  |  1 -
 .../java/org/tensorflow/op/data/RegisterDataset.java   |  3 +++
 .../tensorflow/op/data/ShuffleAndRepeatDataset.java    |  2 +-
 .../java/org/tensorflow/op/data/ShuffleDataset.java    |  2 +-
 .../op/data/experimental/CompressElement.java          |  3 +++
 .../op/data/experimental/DataServiceDataset.java       |  3 +++
 .../op/data/experimental/DatasetToTFRecord.java        |  1 -
 .../op/data/experimental/DummyIterationCounter.java    |  3 +++
 .../experimental/StatsAggregatorSetSummaryWriter.java  |  1 -
 .../op/data/experimental/UncompressElement.java        |  3 +++
 .../op/estimator/BoostedTreesCreateEnsemble.java       |  1 -
 .../BoostedTreesCreateQuantileStreamResource.java      |  1 -
 .../op/estimator/BoostedTreesDeserializeEnsemble.java  |  1 -
 ...BoostedTreesQuantileStreamResourceAddSummaries.java |  1 -
 .../BoostedTreesQuantileStreamResourceDeserialize.java |  1 -
 .../BoostedTreesQuantileStreamResourceFlush.java       |  1 -
 .../op/estimator/BoostedTreesUpdateEnsemble.java       |  1 -
 .../op/estimator/BoostedTreesUpdateEnsembleV2.java     |  1 -
 .../java/org/tensorflow/op/image/ExtractGlimpse.java   |  2 +-
 .../src/gen/java/org/tensorflow/op/io/QueueClose.java  |  1 -
 .../gen/java/org/tensorflow/op/io/QueueEnqueue.java    |  1 -
 .../java/org/tensorflow/op/io/QueueEnqueueMany.java    |  1 -
 .../src/gen/java/org/tensorflow/op/io/ReaderReset.java |  1 -
 .../java/org/tensorflow/op/io/ReaderRestoreState.java  |  1 -
 .../src/gen/java/org/tensorflow/op/io/WriteFile.java   |  1 -
 .../tensorflow/op/linalg/BandedTriangularSolve.java    |  3 +++
 .../src/gen/java/org/tensorflow/op/math/BesselI0.java  |  3 +++
 .../src/gen/java/org/tensorflow/op/math/BesselI1.java  |  3 +++
 .../gen/java/org/tensorflow/op/math/DenseBincount.java |  3 +++
 .../java/org/tensorflow/op/math/special/BesselJ0.java  |  3 +++
 .../java/org/tensorflow/op/math/special/BesselJ1.java  |  3 +++
 .../java/org/tensorflow/op/math/special/BesselK0.java  |  3 +++
 .../java/org/tensorflow/op/math/special/BesselK0e.java |  3 +++
 .../java/org/tensorflow/op/math/special/BesselK1.java  |  3 +++
 .../java/org/tensorflow/op/math/special/BesselK1e.java |  3 +++
 .../java/org/tensorflow/op/math/special/BesselY0.java  |  3 +++
 .../java/org/tensorflow/op/math/special/BesselY1.java  |  3 +++
 .../java/org/tensorflow/op/ragged/RaggedBincount.java  |  3 +++
 .../tensorflow/op/ragged/RaggedCountSparseOutput.java  |  3 +++
 .../gen/java/org/tensorflow/op/ragged/RaggedCross.java |  3 +++
 .../tensorflow/op/random/AnonymousSeedGenerator.java   |  3 +++
 .../op/random/DeleteRandomSeedGenerator.java           |  1 -
 .../org/tensorflow/op/random/DeleteSeedGenerator.java  |  2 ++
 .../src/gen/java/org/tensorflow/op/random/RngSkip.java |  1 -
 .../random/StatelessParameterizedTruncatedNormal.java  |  3 +++
 .../op/random/experimental/DummySeedGenerator.java     |  3 +++
 .../tensorflow/op/sparse/DenseCountSparseOutput.java   |  3 +++
 .../op/sparse/SparseAccumulatorApplyGradient.java      |  1 -
 .../java/org/tensorflow/op/sparse/SparseBincount.java  |  3 +++
 .../tensorflow/op/sparse/SparseCountSparseOutput.java  |  3 +++
 .../gen/java/org/tensorflow/op/sparse/SparseCross.java |  2 +-
 .../org/tensorflow/op/sparse/SparseCrossHashed.java    |  3 +++
 .../org/tensorflow/op/summary/CloseSummaryWriter.java  |  1 -
 .../tensorflow/op/summary/CreateSummaryDbWriter.java   |  1 -
 .../tensorflow/op/summary/CreateSummaryFileWriter.java |  1 -
 .../org/tensorflow/op/summary/FlushSummaryWriter.java  |  1 -
 .../java/org/tensorflow/op/summary/ImportEvent.java    |  1 -
 .../org/tensorflow/op/summary/WriteAudioSummary.java   |  1 -
 .../org/tensorflow/op/summary/WriteGraphSummary.java   |  1 -
 .../tensorflow/op/summary/WriteHistogramSummary.java   |  1 -
 .../org/tensorflow/op/summary/WriteImageSummary.java   |  1 -
 .../tensorflow/op/summary/WriteRawProtoSummary.java    |  1 -
 .../org/tensorflow/op/summary/WriteScalarSummary.java  |  1 -
 .../java/org/tensorflow/op/summary/WriteSummary.java   |  1 -
 .../org/tensorflow/op/tpu/ConfigureTPUEmbedding.java   |  1 -
 .../op/tpu/EnqueueTPUEmbeddingIntegerBatch.java        |  1 -
 .../op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java   |  2 ++
 .../op/tpu/EnqueueTPUEmbeddingSparseBatch.java         |  1 -
 .../op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java   |  1 -
 .../gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java  |  1 -
 .../op/tpu/InfeedEnqueuePrelinearizedBuffer.java       |  1 -
 .../java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java |  1 -
 .../op/tpu/LoadTPUEmbeddingADAMParameters.java         |  1 -
 .../LoadTPUEmbeddingADAMParametersGradAccumDebug.java  |  1 -
 .../op/tpu/LoadTPUEmbeddingAdadeltaParameters.java     |  1 -
 ...adTPUEmbeddingAdadeltaParametersGradAccumDebug.java |  1 -
 .../op/tpu/LoadTPUEmbeddingAdagradParameters.java      |  1 -
 ...oadTPUEmbeddingAdagradParametersGradAccumDebug.java |  1 -
 .../tpu/LoadTPUEmbeddingCenteredRMSPropParameters.java |  1 -
 .../op/tpu/LoadTPUEmbeddingFTRLParameters.java         |  1 -
 .../LoadTPUEmbeddingFTRLParametersGradAccumDebug.java  |  1 -
 .../tpu/LoadTPUEmbeddingMDLAdagradLightParameters.java |  1 -
 .../op/tpu/LoadTPUEmbeddingMomentumParameters.java     |  1 -
 ...adTPUEmbeddingMomentumParametersGradAccumDebug.java |  1 -
 .../tpu/LoadTPUEmbeddingProximalAdagradParameters.java |  1 -
 ...beddingProximalAdagradParametersGradAccumDebug.java |  1 -
 .../op/tpu/LoadTPUEmbeddingProximalYogiParameters.java |  2 ++
 ...UEmbeddingProximalYogiParametersGradAccumDebug.java |  2 ++
 .../op/tpu/LoadTPUEmbeddingRMSPropParameters.java      |  1 -
 ...oadTPUEmbeddingRMSPropParametersGradAccumDebug.java |  1 -
 ...PUEmbeddingStochasticGradientDescentParameters.java |  1 -
 ...chasticGradientDescentParametersGradAccumDebug.java |  2 ++
 .../gen/java/org/tensorflow/op/tpu/OutfeedEnqueue.java |  1 -
 .../org/tensorflow/op/tpu/OutfeedEnqueueTuple.java     |  1 -
 .../RetrieveTPUEmbeddingProximalYogiParameters.java    |  3 +++
 ...UEmbeddingProximalYogiParametersGradAccumDebug.java |  3 +++
 ...chasticGradientDescentParametersGradAccumDebug.java |  3 +++
 .../tensorflow/op/tpu/SendTPUEmbeddingGradients.java   |  1 -
 .../org/tensorflow/op/tpu/ShutdownDistributedTPU.java  |  1 -
 .../org/tensorflow/op/tpu/TPUReplicateMetadata.java    |  1 -
 .../tensorflow/op/train/AccumulatorApplyGradient.java  |  1 -
 .../tensorflow/op/train/AccumulatorSetGlobalStep.java  |  1 -
 .../org/tensorflow/op/train/MergeV2Checkpoints.java    |  1 -
 .../src/gen/java/org/tensorflow/op/train/NegTrain.java |  1 -
 .../op/train/ResourceAccumulatorApplyGradient.java     |  1 -
 .../op/train/ResourceAccumulatorSetGlobalStep.java     |  1 -
 .../org/tensorflow/op/train/ResourceApplyAdaMax.java   |  1 -
 .../org/tensorflow/op/train/ResourceApplyAdadelta.java |  1 -
 .../org/tensorflow/op/train/ResourceApplyAdagrad.java  |  1 -
 .../tensorflow/op/train/ResourceApplyAdagradDa.java    |  1 -
 .../org/tensorflow/op/train/ResourceApplyAdam.java     |  1 -
 .../op/train/ResourceApplyAdamWithAmsgrad.java         |  1 -
 .../org/tensorflow/op/train/ResourceApplyAddSign.java  |  1 -
 .../op/train/ResourceApplyCenteredRmsProp.java         |  1 -
 .../org/tensorflow/op/train/ResourceApplyFtrl.java     |  8 +++-----
 .../op/train/ResourceApplyGradientDescent.java         |  1 -
 .../op/train/ResourceApplyKerasMomentum.java           |  1 -
 .../org/tensorflow/op/train/ResourceApplyMomentum.java |  1 -
 .../tensorflow/op/train/ResourceApplyPowerSign.java    |  1 -
 .../op/train/ResourceApplyProximalAdagrad.java         |  1 -
 .../op/train/ResourceApplyProximalGradientDescent.java |  1 -
 .../org/tensorflow/op/train/ResourceApplyRmsProp.java  |  1 -
 .../op/train/ResourceSparseApplyAdadelta.java          |  1 -
 .../op/train/ResourceSparseApplyAdagrad.java           |  1 -
 .../op/train/ResourceSparseApplyAdagradDa.java         |  1 -
 .../op/train/ResourceSparseApplyAdagradV2.java         |  1 -
 .../op/train/ResourceSparseApplyCenteredRmsProp.java   |  1 -
 .../tensorflow/op/train/ResourceSparseApplyFtrl.java   |  7 ++-----
 .../op/train/ResourceSparseApplyKerasMomentum.java     |  1 -
 .../op/train/ResourceSparseApplyMomentum.java          |  1 -
 .../op/train/ResourceSparseApplyProximalAdagrad.java   |  1 -
 .../ResourceSparseApplyProximalGradientDescent.java    |  1 -
 .../op/train/ResourceSparseApplyRmsProp.java           |  1 -
 .../src/gen/java/org/tensorflow/op/train/Save.java     |  1 -
 .../gen/java/org/tensorflow/op/train/SaveSlices.java   |  1 -
 .../gen/java/org/tensorflow/op/train/SdcaShrinkL1.java |  1 -
 .../src/gen/java/org/tensorflow/op/xla/Send.java       |  1 -
 192 files changed, 143 insertions(+), 157 deletions(-)

diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
index 03db4be125b..843f3bdb247 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
@@ -514,11 +514,15 @@ void GenerateOp(const OpSpec& op, const EndpointSpec& endpoint,
   Javadoc name_javadoc = Javadoc::Create("The name of this op, as known by TensorFlow core engine");
   string quoted_string = "\"" + op.graph_op_name() + "\"";
   writer.WriteFieldWithInitializer(nameVariable, PUBLIC|STATIC|FINAL, &name_javadoc, quoted_string );
-  writer.EndLine();
 
-  for (const ArgumentSpec& output : op.outputs()) {
-    writer.WriteField(output.var(), PRIVATE);
+
+  if(!op.outputs().empty()) {
+    writer.EndLine();
+    for (const ArgumentSpec& output : op.outputs()) {
+        writer.WriteField(output.var(), PRIVATE);
+    }
   }
+
   RenderConstructor(op, op_class, &writer);
   writer.EndType();
 }
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 53e9401dfa2..a84f2405b19 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
@@ -104,7 +104,6 @@ public static Options exitWithoutError(Boolean exitWithoutError) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "Abort";
   
-  
   private Abort(Operation operation) {
     super(operation);
   }
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 950830b7462..dce70c04e5a 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
@@ -90,7 +90,6 @@ public static Options summarize(Long summarize) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "Assert";
   
-  
   private AssertThat(Operation operation) {
     super(operation);
   }
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 5adaccf15e0..53edc808882 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
@@ -55,7 +55,6 @@ public static  AssignAddVariableOp create(Scope scope, Operand<
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "AssignAddVariableOp";
   
-  
   private AssignAddVariableOp(Operation operation) {
     super(operation);
   }
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 4bb683c97d2..372a71b2168 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
@@ -55,7 +55,6 @@ public static  AssignSubVariableOp create(Scope scope, Operand<
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "AssignSubVariableOp";
   
-  
   private AssignSubVariableOp(Operation operation) {
     super(operation);
   }
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 90cabd12a24..ac08d62f9a8 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
@@ -55,7 +55,6 @@ public static  AssignVariableOp create(Scope scope, Operand
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "AssignVariableOp";
   
-  
   private AssignVariableOp(Operation operation) {
     super(operation);
   }
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 a777d684ec1..514f4f50edf 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
@@ -95,7 +95,6 @@ public static Options cancelPendingEnqueues(Boolean cancelPendingEnqueues) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BarrierClose";
   
-  
   private BarrierClose(Operation operation) {
     super(operation);
   }
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 31488738838..b652c11a35c 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
@@ -63,7 +63,6 @@ public static  BarrierInsertMany create(Scope scope, Operand mutexLock) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ConsumeMutexLock";
   
-  
   private ConsumeMutexLock(Operation operation) {
     super(operation);
   }
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 721112b8204..e40715c9f2c 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
@@ -48,7 +48,6 @@ public static ControlTrigger create(Scope scope) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ControlTrigger";
   
-  
   private ControlTrigger(Operation operation) {
     super(operation);
   }
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 50c7615a0ff..5f92cc26ca2 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
@@ -50,7 +50,6 @@ public static DeleteSessionTensor create(Scope scope, Operand handle) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "DeleteSessionTensor";
   
-  
   private DeleteSessionTensor(Operation operation) {
     super(operation);
   }
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 e1958682ee1..8a427166874 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
@@ -88,7 +88,6 @@ public static Options ignoreLookupError(Boolean ignoreLookupError) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "DestroyResourceOp";
   
-  
   private DestroyResourceOp(Operation operation) {
     super(operation);
   }
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 26f984e840d..f033d3fcc9d 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
@@ -68,6 +68,9 @@ public Output asOutput() {
     return index;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeviceIndex";
+  
   private Output index;
   
   private DeviceIndex(Operation operation) {
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 5de2ca6ff07..48662ed420d 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
@@ -54,7 +54,6 @@ public static  InitializeTable create(Scope sc
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "InitializeTableV2";
   
-  
   private InitializeTable(Operation operation) {
     super(operation);
   }
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 0a88cea3ef2..2050c4d8628 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
@@ -121,7 +121,6 @@ public static Options delimiter(String delimiter) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "InitializeTableFromTextFileV2";
   
-  
   private InitializeTableFromTextFile(Operation operation) {
     super(operation);
   }
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 a94393a50f1..9884a40e3cb 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
@@ -57,7 +57,6 @@ public static  LookupTableImport create(Scope
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LookupTableImportV2";
   
-  
   private LookupTableImport(Operation operation) {
     super(operation);
   }
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 c31784ea942..0f09ae25d1b 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
@@ -57,7 +57,6 @@ public static  LookupTableInsert create(Scope
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LookupTableInsertV2";
   
-  
   private LookupTableInsert(Operation operation) {
     super(operation);
   }
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 584e7e1325c..41463ad7539 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
@@ -54,7 +54,6 @@ public static  LookupTableRemove create(Scope scope, Operand
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LookupTableRemoveV2";
   
-  
   private LookupTableRemove(Operation operation) {
     super(operation);
   }
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 ea7581ef2c7..bad1e90554f 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
@@ -145,7 +145,6 @@ public static Options sharedName(String sharedName) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "MapClear";
   
-  
   private MapClear(Operation operation) {
     super(operation);
   }
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 5d72ce8f22f..9291b32d53b 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
@@ -160,7 +160,6 @@ public static Options sharedName(String sharedName) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "MapStage";
   
-  
   private MapStage(Operation operation) {
     super(operation);
   }
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 862aabcd795..922b5d55ce3 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
@@ -46,7 +46,6 @@ public static NoOp create(Scope scope) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "NoOp";
   
-  
   private NoOp(Operation operation) {
     super(operation);
   }
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 29f4133ce09..05a1b7ab984 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
@@ -145,7 +145,6 @@ public static Options sharedName(String sharedName) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "OrderedMapClear";
   
-  
   private OrderedMapClear(Operation operation) {
     super(operation);
   }
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 b51f94c148a..7e02973e3c6 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
@@ -162,7 +162,6 @@ public static Options sharedName(String sharedName) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "OrderedMapStage";
   
-  
   private OrderedMapStage(Operation operation) {
     super(operation);
   }
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 3e96c00d369..52b933329a0 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
@@ -105,7 +105,6 @@ public static Options end(String end) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "PrintV2";
   
-  
   private Print(Operation operation) {
     super(operation);
   }
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 5383062823b..0966dd5fcc4 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
@@ -75,7 +75,6 @@ public static  ResourceScatterAdd create(Sco
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterAdd";
   
-  
   private ResourceScatterAdd(Operation operation) {
     super(operation);
   }
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 ed950863242..9560bddf284 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
@@ -75,7 +75,6 @@ public static  ResourceScatterDiv create(Sco
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterDiv";
   
-  
   private ResourceScatterDiv(Operation operation) {
     super(operation);
   }
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 7553fab4812..ce952ee19ba 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
@@ -75,7 +75,6 @@ public static  ResourceScatterMax create(Sco
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterMax";
   
-  
   private ResourceScatterMax(Operation operation) {
     super(operation);
   }
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 68518b4c640..51ec6b7637e 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
@@ -75,7 +75,6 @@ public static  ResourceScatterMin create(Sco
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterMin";
   
-  
   private ResourceScatterMin(Operation operation) {
     super(operation);
   }
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 f52b338de57..2d5f71e006d 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
@@ -75,7 +75,6 @@ public static  ResourceScatterMul create(Sco
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterMul";
   
-  
   private ResourceScatterMul(Operation operation) {
     super(operation);
   }
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 5abfcbea5ee..11e45c33098 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
@@ -125,7 +125,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterNdAdd";
   
-  
   private ResourceScatterNdAdd(Operation operation) {
     super(operation);
   }
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 e24e3d68fef..82c1f766308 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
@@ -91,6 +91,8 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterNdMax";
   
   private ResourceScatterNdMax(Operation operation) {
     super(operation);
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 3ffc78afa87..88e107c65c7 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
@@ -91,6 +91,8 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceScatterNdMin";
   
   private ResourceScatterNdMin(Operation operation) {
     super(operation);
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 c4b6060d611..267099b7cfc 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
@@ -125,7 +125,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterNdSub";
   
-  
   private ResourceScatterNdSub(Operation operation) {
     super(operation);
   }
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 b47fb4a1367..4a1e875bc97 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
@@ -127,7 +127,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterNdUpdate";
   
-  
   private ResourceScatterNdUpdate(Operation operation) {
     super(operation);
   }
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 2559ff21a93..7b772fab997 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
@@ -75,7 +75,6 @@ public static  ResourceScatterSub create(Sco
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterSub";
   
-  
   private ResourceScatterSub(Operation operation) {
     super(operation);
   }
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 eff04c6c08a..067ddf5f205 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
@@ -66,7 +66,6 @@ public static  ResourceScatterUpdate create(
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceScatterUpdate";
   
-  
   private ResourceScatterUpdate(Operation operation) {
     super(operation);
   }
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 2002140573b..4deb4c55f64 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
@@ -176,7 +176,6 @@ public static Options shrinkAxisMask(Long shrinkAxisMask) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceStridedSliceAssign";
   
-  
   private ResourceStridedSliceAssign(Operation operation) {
     super(operation);
   }
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 851cbb16cf4..da94c783cae 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
@@ -107,6 +107,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterNdMax";
+  
   private Output outputRef;
   
   private ScatterNdMax(Operation operation) {
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 a3e3d4c9790..5aea70bc929 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
@@ -107,6 +107,9 @@ public Output asOutput() {
     return outputRef;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ScatterNdMin";
+  
   private Output outputRef;
   
   private ScatterNdMin(Operation operation) {
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 bf3db1cd88a..d679b85319a 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
@@ -97,7 +97,6 @@ public static Options clientTerminated(Boolean clientTerminated) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "Send";
   
-  
   private Send(Operation operation) {
     super(operation);
   }
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 408b6eca252..526462b02f4 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
@@ -151,7 +151,6 @@ public static Options sharedName(String sharedName) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "Stage";
   
-  
   private Stage(Operation operation) {
     super(operation);
   }
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 755e7ab72d9..60e51559f74 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
@@ -145,7 +145,6 @@ public static Options sharedName(String sharedName) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "StageClear";
   
-  
   private StageClear(Operation operation) {
     super(operation);
   }
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 a16e856ae72..62180e8e5ff 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
@@ -52,7 +52,6 @@ public static TensorArrayClose create(Scope scope, Operand handle) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "TensorArrayCloseV3";
   
-  
   private TensorArrayClose(Operation operation) {
     super(operation);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java
index e647f58b2f3..5ca6ffa1cd0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestCreateTreeVariable.java
@@ -51,7 +51,6 @@ public static TensorForestCreateTreeVariable create(Scope scope, Operand tree
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "TensorForestCreateTreeVariable";
   
-  
   private TensorForestCreateTreeVariable(Operation operation) {
     super(operation);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java
index 5fb704b2361..a5e1638035e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorForestTreeDeserialize.java
@@ -51,7 +51,6 @@ public static TensorForestTreeDeserialize create(Scope scope, Operand treeHan
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "TensorForestTreeDeserialize";
   
-  
   private TensorForestTreeDeserialize(Operation operation) {
     super(operation);
   }
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 d040cf0639a..a14b20195af 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorScatterMax";
+  
   private Output output;
   
   private TensorScatterNdMax(Operation operation) {
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 797878d9c76..b202b72eebd 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "TensorScatterMin";
+  
   private Output output;
   
   private TensorScatterNdMin(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdFullToShardShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdFullToShardShape.java
index 51f2c2b5dde..6615d2ef9f6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdFullToShardShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdFullToShardShape.java
@@ -68,6 +68,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaSpmdFullToShardShape";
+  
   private Output output;
   
   private XlaSpmdFullToShardShape(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdShardToFullShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdShardToFullShape.java
index 5a120fb6fb8..75e31c7c317 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdShardToFullShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/XlaSpmdShardToFullShape.java
@@ -70,6 +70,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "XlaSpmdShardToFullShape";
+  
   private Output output;
   
   private XlaSpmdShardToFullShape(Operation operation) {
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 41617c9b690..114e11074dc 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
@@ -54,7 +54,6 @@ public static DatasetToTfRecord create(Scope scope, Operand inputDataset, Ope
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "DatasetToTFRecord";
   
-  
   private DatasetToTfRecord(Operation operation) {
     super(operation);
   }
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 ec3629a8eb7..69f3af096bb 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
@@ -51,7 +51,6 @@ public static DeleteIterator create(Scope scope, Operand handle, Operand d
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "DeleteIterator";
   
-  
   private DeleteIterator(Operation operation) {
     super(operation);
   }
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 3c0f37dc409..21c33030b66 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
@@ -49,7 +49,6 @@ public static DeleteMemoryCache create(Scope scope, Operand handle, Operand multiDevi
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "DeleteMultiDeviceIterator";
   
-  
   private DeleteMultiDeviceIterator(Operation operation) {
     super(operation);
   }
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 528fd09bc53..4f772fd5028 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
@@ -52,7 +52,6 @@ public static DeserializeIterator create(Scope scope, Operand resourceHandle,
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "DeserializeIterator";
   
-  
   private DeserializeIterator(Operation operation) {
     super(operation);
   }
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 527c951377b..05a263a4ec1 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
@@ -46,6 +46,8 @@ public static InitializeTableFromDataset create(Scope scope, Operand tableHan
     return new InitializeTableFromDataset(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "InitializeTableFromDataset";
   
   private InitializeTableFromDataset(Operation operation) {
     super(operation);
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 685574a92d5..4aace25184e 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
@@ -54,7 +54,6 @@ public static MakeIterator create(Scope scope, Operand dataset, Operand it
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "MakeIterator";
   
-  
   private MakeIterator(Operation operation) {
     super(operation);
   }
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 7e0695768c2..5705413165c 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
@@ -65,6 +65,9 @@ public Output asOutput() {
     return datasetId;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RegisterDataset";
+  
   private Output datasetId;
   
   private RegisterDataset(Operation operation) {
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 1f6d2697497..c5703e8e85c 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
@@ -119,7 +119,7 @@ public Output asOutput() {
   }
   
   /** The name of this op, as known by TensorFlow core engine */
-  public static final String OP_NAME = "ShuffleAndRepeatDataset";
+  public static final String OP_NAME = "ShuffleAndRepeatDatasetV2";
   
   private Output handle;
   
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 ce3de6f787f..3dd522e319c 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
@@ -117,7 +117,7 @@ public Output asOutput() {
   }
   
   /** The name of this op, as known by TensorFlow core engine */
-  public static final String OP_NAME = "ShuffleDatasetV2";
+  public static final String OP_NAME = "ShuffleDatasetV3";
   
   private Output handle;
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CompressElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CompressElement.java
index e56a8cde614..9e4bfb34a8b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CompressElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/CompressElement.java
@@ -60,6 +60,9 @@ public Output asOutput() {
     return (Output) compressed;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "CompressElement";
+  
   private Output compressed;
   
   private CompressElement(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java
index 4623ec2ea5d..b3e853f9de4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java
@@ -122,6 +122,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DataServiceDataset";
+  
   private Output handle;
   
   private DataServiceDataset(Operation operation) {
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 ee0f494fa73..6e0a0b8f2dc 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
@@ -54,7 +54,6 @@ public static DatasetToTFRecord create(Scope scope, Operand inputDataset, Ope
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ExperimentalDatasetToTFRecord";
   
-  
   private DatasetToTFRecord(Operation operation) {
     super(operation);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DummyIterationCounter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DummyIterationCounter.java
index b2febce6f81..72f83847285 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DummyIterationCounter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DummyIterationCounter.java
@@ -56,6 +56,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DummyIterationCounter";
+  
   private Output handle;
   
   private DummyIterationCounter(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java
index ad63ff056d8..1af246d8313 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/StatsAggregatorSetSummaryWriter.java
@@ -50,7 +50,6 @@ public static StatsAggregatorSetSummaryWriter create(Scope scope, Operand sta
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "StatsAggregatorSetSummaryWriter";
   
-  
   private StatsAggregatorSetSummaryWriter(Operation operation) {
     super(operation);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java
index 5d94d8699ab..c5732154e94 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java
@@ -76,6 +76,9 @@ public Iterator> iterator() {
     return (Iterator) components.iterator();
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "UncompressElement";
+  
   private List> components;
   
   private UncompressElement(Operation operation) {
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 04613900567..8841988b36d 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
@@ -54,7 +54,6 @@ public static BoostedTreesCreateEnsemble create(Scope scope, Operand treeEnse
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesCreateEnsemble";
   
-  
   private BoostedTreesCreateEnsemble(Operation operation) {
     super(operation);
   }
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 59362970a58..802a61ecb2a 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
@@ -88,7 +88,6 @@ public static Options maxElements(Long maxElements) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesCreateQuantileStreamResource";
   
-  
   private BoostedTreesCreateQuantileStreamResource(Operation operation) {
     super(operation);
   }
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 6fd83d5785d..15371fb4df9 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
@@ -56,7 +56,6 @@ public static BoostedTreesDeserializeEnsemble create(Scope scope, Operand tre
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesDeserializeEnsemble";
   
-  
   private BoostedTreesDeserializeEnsemble(Operation operation) {
     super(operation);
   }
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 76480c4be6d..418ff3b2ff6 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
@@ -56,7 +56,6 @@ public static BoostedTreesQuantileStreamResourceAddSummaries create(Scope scope,
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesQuantileStreamResourceAddSummaries";
   
-  
   private BoostedTreesQuantileStreamResourceAddSummaries(Operation operation) {
     super(operation);
   }
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 82066e267d2..6efb58ed60c 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
@@ -54,7 +54,6 @@ public static BoostedTreesQuantileStreamResourceDeserialize create(Scope scope,
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesQuantileStreamResourceDeserialize";
   
-  
   private BoostedTreesQuantileStreamResourceDeserialize(Operation operation) {
     super(operation);
   }
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 359b7b63ff6..cc10434a582 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
@@ -97,7 +97,6 @@ public static Options generateQuantiles(Boolean generateQuantiles) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesQuantileStreamResourceFlush";
   
-  
   private BoostedTreesQuantileStreamResourceFlush(Operation operation) {
     super(operation);
   }
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 c1b7bb44559..e6ddcf3d2da 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
@@ -79,7 +79,6 @@ public static BoostedTreesUpdateEnsemble create(Scope scope, Operand treeEnse
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesUpdateEnsemble";
   
-  
   private BoostedTreesUpdateEnsemble(Operation operation) {
     super(operation);
   }
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 afd9d646c2f..ceaff116fd1 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
@@ -118,7 +118,6 @@ public static Options logitsDimension(Long logitsDimension) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "BoostedTreesUpdateEnsembleV2";
   
-  
   private BoostedTreesUpdateEnsembleV2(Operation operation) {
     super(operation);
   }
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 172b24f74ac..05bc1d924b3 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
@@ -199,7 +199,7 @@ public Output asOutput() {
   }
   
   /** The name of this op, as known by TensorFlow core engine */
-  public static final String OP_NAME = "ExtractGlimpse";
+  public static final String OP_NAME = "ExtractGlimpseV2";
   
   private Output glimpse;
   
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 fb55f708140..ea7791f143e 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
@@ -91,7 +91,6 @@ public static Options cancelPendingEnqueues(Boolean cancelPendingEnqueues) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "QueueCloseV2";
   
-  
   private QueueClose(Operation operation) {
     super(operation);
   }
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 546981e8abf..a159b0cd17c 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
@@ -96,7 +96,6 @@ public static Options timeoutMs(Long timeoutMs) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "QueueEnqueueV2";
   
-  
   private QueueEnqueue(Operation operation) {
     super(operation);
   }
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 48df5d3b9d3..b1f9cbd6807 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
@@ -101,7 +101,6 @@ public static Options timeoutMs(Long timeoutMs) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "QueueEnqueueManyV2";
   
-  
   private QueueEnqueueMany(Operation operation) {
     super(operation);
   }
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 6e3de01134b..243d4a72080 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
@@ -49,7 +49,6 @@ public static ReaderReset create(Scope scope, Operand readerHandle) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ReaderResetV2";
   
-  
   private ReaderReset(Operation operation) {
     super(operation);
   }
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 b0abea1257c..431ba079ffc 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
@@ -56,7 +56,6 @@ public static ReaderRestoreState create(Scope scope, Operand readerHandle, Op
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ReaderRestoreStateV2";
   
-  
   private ReaderRestoreState(Operation operation) {
     super(operation);
   }
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 d9fba243fc3..d1c9dd9b9c8 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
@@ -54,7 +54,6 @@ public static WriteFile create(Scope scope, Operand filename, Operand asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BandedTriangularSolve";
+  
   private Output output;
   
   private BandedTriangularSolve(Operation operation) {
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 53e1ac83c32..45dcd2b8e4c 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselI0";
+  
   private Output y;
   
   private BesselI0(Operation operation) {
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 638f6b06972..148758aa5a4 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselI1";
+  
   private Output y;
   
   private BesselI1(Operation operation) {
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 165be081102..e38d559f4ae 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
@@ -112,6 +112,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DenseBincount";
+  
   private Output output;
   
   private DenseBincount(Operation operation) {
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 bc73a0c9c02..8d2184a49cb 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselJ0";
+  
   private Output y;
   
   private BesselJ0(Operation operation) {
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 4fd21c42288..d8f9621a36c 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselJ1";
+  
   private Output y;
   
   private BesselJ1(Operation operation) {
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 8f3c540b185..eaae243f83f 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselK0";
+  
   private Output y;
   
   private BesselK0(Operation operation) {
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 1a8f9761c08..c57ae64e233 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselK0e";
+  
   private Output y;
   
   private BesselK0e(Operation operation) {
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 bcaaf6f6f9c..1858d25fe3d 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselK1";
+  
   private Output y;
   
   private BesselK1(Operation operation) {
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 c6590805d54..e4a5cc23efd 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselK1e";
+  
   private Output y;
   
   private BesselK1e(Operation operation) {
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 86843a30939..9228d1b6145 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselY0";
+  
   private Output y;
   
   private BesselY0(Operation operation) {
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 2cdc4ad7df0..0461416b808 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
@@ -59,6 +59,9 @@ public Output asOutput() {
     return y;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "BesselY1";
+  
   private Output y;
   
   private BesselY1(Operation operation) {
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 fc1636d8d64..1e0224aa9ef 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
@@ -115,6 +115,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedBincount";
+  
   private Output output;
   
   private RaggedBincount(Operation operation) {
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 07b364f6ebb..4829e49488b 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
@@ -140,6 +140,9 @@ public Output outputDenseShape() {
     return outputDenseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedCountSparseOutput";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputDenseShape;
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 fa6e811969b..9ea32878257 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
@@ -94,6 +94,9 @@ public Output outputRowSplits() {
     return outputRowSplits;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RaggedCross";
+  
   private Output outputValues;
   private Output outputRowSplits;
   
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 f55c3222977..c724bb6d110 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
@@ -63,6 +63,9 @@ public Output deleter() {
     return deleter;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "AnonymousSeedGenerator";
+  
   private Output handle;
   private Output deleter;
   
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 9bc34d98ebb..23b154f9d75 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
@@ -49,7 +49,6 @@ public static DeleteRandomSeedGenerator create(Scope scope, Operand handle, O
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "DeleteRandomSeedGenerator";
   
-  
   private DeleteRandomSeedGenerator(Operation operation) {
     super(operation);
   }
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 2872ea12aff..16982946d1f 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
@@ -46,6 +46,8 @@ public static DeleteSeedGenerator create(Scope scope, Operand handle, Operand
     return new DeleteSeedGenerator(opBuilder.build());
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DeleteSeedGenerator";
   
   private DeleteSeedGenerator(Operation operation) {
     super(operation);
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 e3411c3b989..f41cff35b04 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
@@ -58,7 +58,6 @@ public static RngSkip create(Scope scope, Operand resource, Operand a
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "RngSkip";
   
-  
   private RngSkip(Operation operation) {
     super(operation);
   }
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 053db14c986..179160463c7 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
@@ -72,6 +72,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "StatelessParameterizedTruncatedNormal";
+  
   private Output output;
   
   private StatelessParameterizedTruncatedNormal(Operation operation) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/DummySeedGenerator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/DummySeedGenerator.java
index 92e58ba293f..dd537fa2d68 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/DummySeedGenerator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/DummySeedGenerator.java
@@ -56,6 +56,9 @@ public Output asOutput() {
     return (Output) handle;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DummySeedGenerator";
+  
   private Output handle;
   
   private DummySeedGenerator(Operation operation) {
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 62c489cab7b..ed390a7ba47 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
@@ -132,6 +132,9 @@ public Output outputDenseShape() {
     return outputDenseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "DenseCountSparseOutput";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputDenseShape;
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 3f36812ea57..328fe0c49ea 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
@@ -69,7 +69,6 @@ public static  SparseAccumulatorApplyGradient create(Scope scop
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "SparseAccumulatorApplyGradient";
   
-  
   private SparseAccumulatorApplyGradient(Operation operation) {
     super(operation);
   }
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 7902e8544dd..344e27f1346 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
@@ -117,6 +117,9 @@ public Output asOutput() {
     return output;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseBincount";
+  
   private Output output;
   
   private SparseBincount(Operation operation) {
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 36230bc774e..5e5566db5ec 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
@@ -136,6 +136,9 @@ public Output outputDenseShape() {
     return outputDenseShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseCountSparseOutput";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputDenseShape;
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 06113f0315b..1cd471349c2 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
@@ -118,7 +118,7 @@ public Output outputShape() {
   }
   
   /** The name of this op, as known by TensorFlow core engine */
-  public static final String OP_NAME = "SparseCross";
+  public static final String OP_NAME = "SparseCrossV2";
   
   private Output outputIndices;
   private Output outputValues;
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 9e7cc9b1e6c..2fc6976079e 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
@@ -122,6 +122,9 @@ public Output outputShape() {
     return outputShape;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "SparseCrossHashed";
+  
   private Output outputIndices;
   private Output outputValues;
   private Output outputShape;
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 ff9735f0b07..f5d95d50976 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
@@ -47,7 +47,6 @@ public static CloseSummaryWriter create(Scope scope, Operand writer) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "CloseSummaryWriter";
   
-  
   private CloseSummaryWriter(Operation operation) {
     super(operation);
   }
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 61e7405f74d..8e40aa798d6 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
@@ -56,7 +56,6 @@ public static CreateSummaryDbWriter create(Scope scope, Operand writer, Opera
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "CreateSummaryDbWriter";
   
-  
   private CreateSummaryDbWriter(Operation operation) {
     super(operation);
   }
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 d113ebcf3f6..e429fab20e2 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
@@ -57,7 +57,6 @@ public static CreateSummaryFileWriter create(Scope scope, Operand writer, Ope
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "CreateSummaryFileWriter";
   
-  
   private CreateSummaryFileWriter(Operation operation) {
     super(operation);
   }
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 6b1e610c632..e1586542972 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
@@ -47,7 +47,6 @@ public static FlushSummaryWriter create(Scope scope, Operand writer) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "FlushSummaryWriter";
   
-  
   private FlushSummaryWriter(Operation operation) {
     super(operation);
   }
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 9b6dc173abe..7bd97de571e 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
@@ -50,7 +50,6 @@ public static ImportEvent create(Scope scope, Operand writer, Operand writer, Operand WriteHistogramSummary create(Scope scope, Oper
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "WriteHistogramSummary";
   
-  
   private WriteHistogramSummary(Operation operation) {
     super(operation);
   }
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 286d584d695..757ddf59a1c 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
@@ -94,7 +94,6 @@ public static Options maxImages(Long maxImages) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "WriteImageSummary";
   
-  
   private WriteImageSummary(Operation operation) {
     super(operation);
   }
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 524b56bed7a..75499c1ff69 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
@@ -53,7 +53,6 @@ public static WriteRawProtoSummary create(Scope scope, Operand writer, Operan
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "WriteRawProtoSummary";
   
-  
   private WriteRawProtoSummary(Operation operation) {
     super(operation);
   }
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 2317db7bdeb..f173651001a 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
@@ -57,7 +57,6 @@ public static  WriteScalarSummary create(Scope scope, Operand
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "WriteScalarSummary";
   
-  
   private WriteScalarSummary(Operation operation) {
     super(operation);
   }
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 6d257f948e8..5404e593f27 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
@@ -58,7 +58,6 @@ public static  WriteSummary create(Scope scope, Operand writ
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "WriteSummary";
   
-  
   private WriteSummary(Operation operation) {
     super(operation);
   }
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 1905a3082b3..76bccd51f83 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
@@ -48,7 +48,6 @@ public static ConfigureTPUEmbedding create(Scope scope, String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ConfigureTPUEmbedding";
   
-  
   private ConfigureTPUEmbedding(Operation operation) {
     super(operation);
   }
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 4198c38e11c..0a1a80c7a0a 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
@@ -93,7 +93,6 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "EnqueueTPUEmbeddingIntegerBatch";
   
-  
   private EnqueueTPUEmbeddingIntegerBatch(Operation operation) {
     super(operation);
   }
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 c605dafbc87..bf4da86d05d 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
@@ -177,6 +177,8 @@ public static Options maxSequenceLengths(List maxSequenceLengths) {
     return new Options().maxSequenceLengths(maxSequenceLengths);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "EnqueueTPUEmbeddingRaggedTensorBatch";
   
   private EnqueueTPUEmbeddingRaggedTensorBatch(Operation operation) {
     super(operation);
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 23288018938..2cb7dfb674b 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
@@ -146,7 +146,6 @@ public static Options combiners(List combiners) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "EnqueueTPUEmbeddingSparseBatch";
   
-  
   private EnqueueTPUEmbeddingSparseBatch(Operation operation) {
     super(operation);
   }
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 59018e1b3e5..3d93c6a0f71 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
@@ -178,7 +178,6 @@ public static Options maxSequenceLengths(List maxSequenceLengths) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "EnqueueTPUEmbeddingSparseTensorBatch";
   
-  
   private EnqueueTPUEmbeddingSparseTensorBatch(Operation operation) {
     super(operation);
   }
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 9c79df444e3..391d51a9ab0 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
@@ -135,7 +135,6 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "InfeedEnqueue";
   
-  
   private InfeedEnqueue(Operation operation) {
     super(operation);
   }
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 b1d32f70ec9..9344352791c 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
@@ -84,7 +84,6 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "InfeedEnqueuePrelinearizedBuffer";
   
-  
   private InfeedEnqueuePrelinearizedBuffer(Operation operation) {
     super(operation);
   }
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 d2a95d84244..b439df84f71 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
@@ -124,7 +124,6 @@ public static Options deviceOrdinal(Long deviceOrdinal) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "InfeedEnqueueTuple";
   
-  
   private InfeedEnqueueTuple(Operation operation) {
     super(operation);
   }
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 9e60fae350e..744688cee23 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
@@ -135,7 +135,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingADAMParameters";
   
-  
   private LoadTPUEmbeddingADAMParameters(Operation operation) {
     super(operation);
   }
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 58cfa5cf465..63df2e6aa79 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
@@ -137,7 +137,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingADAMParametersGradAccumDebug";
   
-  
   private LoadTPUEmbeddingADAMParametersGradAccumDebug(Operation operation) {
     super(operation);
   }
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 e4f4228f0f1..43535a2aff8 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
@@ -135,7 +135,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingAdadeltaParameters";
   
-  
   private LoadTPUEmbeddingAdadeltaParameters(Operation operation) {
     super(operation);
   }
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 76af15dc0b6..ce1b759ee60 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
@@ -137,7 +137,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingAdadeltaParametersGradAccumDebug";
   
-  
   private LoadTPUEmbeddingAdadeltaParametersGradAccumDebug(Operation operation) {
     super(operation);
   }
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 dc4f5c62341..f9e16c5b5d6 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
@@ -133,7 +133,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingAdagradParameters";
   
-  
   private LoadTPUEmbeddingAdagradParameters(Operation operation) {
     super(operation);
   }
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 6551f875f2d..7f8df653745 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
@@ -135,7 +135,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingAdagradParametersGradAccumDebug";
   
-  
   private LoadTPUEmbeddingAdagradParametersGradAccumDebug(Operation operation) {
     super(operation);
   }
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 d4a0103654c..f0b704cfaa1 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
@@ -137,7 +137,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingCenteredRMSPropParameters";
   
-  
   private LoadTPUEmbeddingCenteredRMSPropParameters(Operation operation) {
     super(operation);
   }
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 a65301f6348..c96edf58894 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
@@ -135,7 +135,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingFTRLParameters";
   
-  
   private LoadTPUEmbeddingFTRLParameters(Operation operation) {
     super(operation);
   }
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 5a1c165428d..f0a85bd945a 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
@@ -137,7 +137,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingFTRLParametersGradAccumDebug";
   
-  
   private LoadTPUEmbeddingFTRLParametersGradAccumDebug(Operation operation) {
     super(operation);
   }
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 407cf842f19..f418a70cc8c 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
@@ -137,7 +137,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingMDLAdagradLightParameters";
   
-  
   private LoadTPUEmbeddingMDLAdagradLightParameters(Operation operation) {
     super(operation);
   }
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 35b8479749b..718bdc24f5c 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
@@ -133,7 +133,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingMomentumParameters";
   
-  
   private LoadTPUEmbeddingMomentumParameters(Operation operation) {
     super(operation);
   }
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 babc2de15fd..424c3c846c0 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
@@ -135,7 +135,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingMomentumParametersGradAccumDebug";
   
-  
   private LoadTPUEmbeddingMomentumParametersGradAccumDebug(Operation operation) {
     super(operation);
   }
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 0ebad625abe..7b7265e9b82 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
@@ -133,7 +133,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingProximalAdagradParameters";
   
-  
   private LoadTPUEmbeddingProximalAdagradParameters(Operation operation) {
     super(operation);
   }
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 80b05d47203..c18d2cf22f5 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
@@ -135,7 +135,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug";
   
-  
   private LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug(Operation operation) {
     super(operation);
   }
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 651c8e189c4..2a96916c4f5 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
@@ -125,6 +125,8 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingProximalYogiParameters";
   
   private LoadTPUEmbeddingProximalYogiParameters(Operation operation) {
     super(operation);
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 274accba1c9..e863dc554d6 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
@@ -127,6 +127,8 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingProximalYogiParametersGradAccumDebug";
   
   private LoadTPUEmbeddingProximalYogiParametersGradAccumDebug(Operation operation) {
     super(operation);
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 d0e39d22edb..1f747282d55 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
@@ -135,7 +135,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingRMSPropParameters";
   
-  
   private LoadTPUEmbeddingRMSPropParameters(Operation operation) {
     super(operation);
   }
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 98f1043a768..a7c8ed4812c 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
@@ -137,7 +137,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingRMSPropParametersGradAccumDebug";
   
-  
   private LoadTPUEmbeddingRMSPropParametersGradAccumDebug(Operation operation) {
     super(operation);
   }
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 ca881823239..769d3436eda 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
@@ -131,7 +131,6 @@ public static Options config(String config) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "LoadTPUEmbeddingStochasticGradientDescentParameters";
   
-  
   private LoadTPUEmbeddingStochasticGradientDescentParameters(Operation operation) {
     super(operation);
   }
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 76a13a489ad..e408844e484 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
@@ -130,6 +130,8 @@ public static Options config(String config) {
     return new Options().config(config);
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug";
   
   private LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug(Operation operation) {
     super(operation);
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 46ee54430d9..5b5f059a81e 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
@@ -49,7 +49,6 @@ public static  OutfeedEnqueue create(Scope scope, Operand in
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "OutfeedEnqueue";
   
-  
   private OutfeedEnqueue(Operation operation) {
     super(operation);
   }
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 25d110f1114..8bfd04b9a2c 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
@@ -50,7 +50,6 @@ public static OutfeedEnqueueTuple create(Scope scope, Iterable> input
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "OutfeedEnqueueTuple";
   
-  
   private OutfeedEnqueueTuple(Operation operation) {
     super(operation);
   }
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 eaee4fdabc4..a46cae90359 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
@@ -137,6 +137,9 @@ public Output m() {
     return m;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingProximalYogiParameters";
+  
   private Output parameters;
   private Output v;
   private Output m;
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 ec57d8cb424..55535a573f6 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
@@ -143,6 +143,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug";
+  
   private Output parameters;
   private Output v;
   private Output m;
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 f649b4d01fa..9f35ffcd8e0 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
@@ -139,6 +139,9 @@ public Output gradientAccumulators() {
     return gradientAccumulators;
   }
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug";
+  
   private Output parameters;
   private Output gradientAccumulators;
   
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 25d25c1d5bf..482080bde5d 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
@@ -64,7 +64,6 @@ public static SendTPUEmbeddingGradients create(Scope scope, Iterable AccumulatorApplyGradient create(Scope scope, Ope
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "AccumulatorApplyGradient";
   
-  
   private AccumulatorApplyGradient(Operation operation) {
     super(operation);
   }
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 b57bb702669..9039d3a654d 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
@@ -56,7 +56,6 @@ public static AccumulatorSetGlobalStep create(Scope scope, Operand hand
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "AccumulatorSetGlobalStep";
   
-  
   private AccumulatorSetGlobalStep(Operation operation) {
     super(operation);
   }
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 4fe4a27171a..986553a2d8e 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
@@ -96,7 +96,6 @@ public static Options deleteOldDirs(Boolean deleteOldDirs) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "MergeV2Checkpoints";
   
-  
   private MergeV2Checkpoints(Operation operation) {
     super(operation);
   }
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 f43928961a9..b3e5316ad7e 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
@@ -68,7 +68,6 @@ public static NegTrain create(Scope scope, Operand wIn, Operand ResourceAccumulatorApplyGradient create(Scope sc
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceAccumulatorApplyGradient";
   
-  
   private ResourceAccumulatorApplyGradient(Operation operation) {
     super(operation);
   }
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 e04784aef48..37570909340 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
@@ -54,7 +54,6 @@ public static ResourceAccumulatorSetGlobalStep create(Scope scope, Operand ha
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceAccumulatorSetGlobalStep";
   
-  
   private ResourceAccumulatorSetGlobalStep(Operation operation) {
     super(operation);
   }
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 5efab216739..169da75fecd 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
@@ -107,7 +107,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyAdaMax";
   
-  
   private ResourceApplyAdaMax(Operation operation) {
     super(operation);
   }
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 0121155a2ef..4323a39de45 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
@@ -103,7 +103,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyAdadelta";
   
-  
   private ResourceApplyAdadelta(Operation operation) {
     super(operation);
   }
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 8868193464f..b60ad1fc0e0 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
@@ -117,7 +117,6 @@ public static Options updateSlots(Boolean updateSlots) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyAdagradV2";
   
-  
   private ResourceApplyAdagrad(Operation operation) {
     super(operation);
   }
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 7f5b26056ac..7c6f06634ef 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
@@ -101,7 +101,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyAdagradDA";
   
-  
   private ResourceApplyAdagradDa(Operation operation) {
     super(operation);
   }
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 20a07b4865d..4a1aea5d355 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
@@ -130,7 +130,6 @@ public static Options useNesterov(Boolean useNesterov) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyAdam";
   
-  
   private ResourceApplyAdam(Operation operation) {
     super(operation);
   }
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 ec13f10038d..a436bc7fdd2 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
@@ -114,7 +114,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyAdamWithAmsgrad";
   
-  
   private ResourceApplyAdamWithAmsgrad(Operation operation) {
     super(operation);
   }
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 e64354ec3bb..85c9c587979 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
@@ -104,7 +104,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyAddSign";
   
-  
   private ResourceApplyAddSign(Operation operation) {
     super(operation);
   }
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 c4c8d7c9ec7..6fc3a8a02ff 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
@@ -123,7 +123,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyCenteredRMSProp";
   
-  
   private ResourceApplyCenteredRmsProp(Operation operation) {
     super(operation);
   }
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 c9de01ad14d..e69b6b99959 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
@@ -120,18 +120,16 @@ public static  ResourceApplyFtrl create(Scope scope, Operand
   public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
-
-  /** The name of this op, as known by TensorFlow core engine */
-  public static final String OP_NAME = "ResourceApplyFtrlV2";
-
+  
   /**
    * @param multiplyLinearByLr 
    */
   public static Options multiplyLinearByLr(Boolean multiplyLinearByLr) {
     return new Options().multiplyLinearByLr(multiplyLinearByLr);
   }
-
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceApplyFtrlV2";
   
   private ResourceApplyFtrl(Operation operation) {
     super(operation);
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 0e495bdd651..f33c6b9ca87 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
@@ -90,7 +90,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyGradientDescent";
   
-  
   private ResourceApplyGradientDescent(Operation operation) {
     super(operation);
   }
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 3a986d617eb..3922439dcad 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
@@ -124,7 +124,6 @@ public static Options useNesterov(Boolean useNesterov) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyKerasMomentum";
   
-  
   private ResourceApplyKerasMomentum(Operation operation) {
     super(operation);
   }
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 c441193d864..c554c8a939d 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
@@ -124,7 +124,6 @@ public static Options useNesterov(Boolean useNesterov) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyMomentum";
   
-  
   private ResourceApplyMomentum(Operation operation) {
     super(operation);
   }
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 c1ba8b0ebd7..662c2253264 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
@@ -104,7 +104,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyPowerSign";
   
-  
   private ResourceApplyPowerSign(Operation operation) {
     super(operation);
   }
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 b51ce4698e1..8036d891e33 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
@@ -100,7 +100,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyProximalAdagrad";
   
-  
   private ResourceApplyProximalAdagrad(Operation operation) {
     super(operation);
   }
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 7f9c4f4e52c..3b217c88c67 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
@@ -97,7 +97,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyProximalGradientDescent";
   
-  
   private ResourceApplyProximalGradientDescent(Operation operation) {
     super(operation);
   }
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 4c400f1aaa1..ae42295c1f7 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
@@ -113,7 +113,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceApplyRMSProp";
   
-  
   private ResourceApplyRmsProp(Operation operation) {
     super(operation);
   }
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 9a50137d196..baea98fc1f7 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
@@ -101,7 +101,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyAdadelta";
   
-  
   private ResourceSparseApplyAdadelta(Operation operation) {
     super(operation);
   }
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 69a3e775622..f7816e78d0c 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
@@ -120,7 +120,6 @@ public static Options updateSlots(Boolean updateSlots) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyAdagrad";
   
-  
   private ResourceSparseApplyAdagrad(Operation operation) {
     super(operation);
   }
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 4f3189f074c..417eca86a80 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
@@ -104,7 +104,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyAdagradDA";
   
-  
   private ResourceSparseApplyAdagradDa(Operation operation) {
     super(operation);
   }
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 30e6c19da15..f60d192c368 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
@@ -121,7 +121,6 @@ public static Options updateSlots(Boolean updateSlots) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyAdagradV2";
   
-  
   private ResourceSparseApplyAdagradV2(Operation operation) {
     super(operation);
   }
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 ab9b9d3c38d..d6806c36abf 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
@@ -124,7 +124,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyCenteredRMSProp";
   
-  
   private ResourceSparseApplyCenteredRmsProp(Operation operation) {
     super(operation);
   }
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 84caa503dec..a13382272c8 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
@@ -125,18 +125,15 @@ public static Options useLocking(Boolean useLocking) {
     return new Options().useLocking(useLocking);
   }
   
-
-  /** The name of this op, as known by TensorFlow core engine */
-  public static final String OP_NAME = "ResourceSparseApplyFtrlV2";
-
   /**
    * @param multiplyLinearByLr 
    */
   public static Options multiplyLinearByLr(Boolean multiplyLinearByLr) {
     return new Options().multiplyLinearByLr(multiplyLinearByLr);
   }
-
   
+  /** The name of this op, as known by TensorFlow core engine */
+  public static final String OP_NAME = "ResourceSparseApplyFtrlV2";
   
   private ResourceSparseApplyFtrl(Operation operation) {
     super(operation);
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 0284564f78c..b385403f989 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
@@ -129,7 +129,6 @@ public static Options useNesterov(Boolean useNesterov) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyKerasMomentum";
   
-  
   private ResourceSparseApplyKerasMomentum(Operation operation) {
     super(operation);
   }
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 5199932b5bc..bc303bfbbf0 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
@@ -129,7 +129,6 @@ public static Options useNesterov(Boolean useNesterov) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyMomentum";
   
-  
   private ResourceSparseApplyMomentum(Operation operation) {
     super(operation);
   }
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 e235a19f5d1..678601d6aea 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
@@ -105,7 +105,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyProximalAdagrad";
   
-  
   private ResourceSparseApplyProximalAdagrad(Operation operation) {
     super(operation);
   }
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 08a9edc01c4..11ad213524c 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
@@ -101,7 +101,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyProximalGradientDescent";
   
-  
   private ResourceSparseApplyProximalGradientDescent(Operation operation) {
     super(operation);
   }
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 982e1f30eb7..8c519504f89 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
@@ -116,7 +116,6 @@ public static Options useLocking(Boolean useLocking) {
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "ResourceSparseApplyRMSProp";
   
-  
   private ResourceSparseApplyRmsProp(Operation operation) {
     super(operation);
   }
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 781714d8121..c5de40fc91b 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
@@ -63,7 +63,6 @@ public static Save create(Scope scope, Operand prefix, Operand
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "SaveV2";
   
-  
   private Save(Operation operation) {
     super(operation);
   }
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 e8e67190e63..73325d1d1bc 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
@@ -89,7 +89,6 @@ public static SaveSlices create(Scope scope, Operand filename, Operand<
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "SaveSlices";
   
-  
   private SaveSlices(Operation operation) {
     super(operation);
   }
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 24c6d53ef9d..748a2eacaec 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
@@ -56,7 +56,6 @@ public static SdcaShrinkL1 create(Scope scope, Iterable> weigh
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "SdcaShrinkL1";
   
-  
   private SdcaShrinkL1(Operation operation) {
     super(operation);
   }
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 d1172f8e96f..b18a86458ca 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
@@ -55,7 +55,6 @@ public static  Send create(Scope scope, Operand tensor, Stri
   /** The name of this op, as known by TensorFlow core engine */
   public static final String OP_NAME = "XlaSend";
   
-  
   private Send(Operation operation) {
     super(operation);
   }

From 44f530f292fdba34164de696fb454b30108064d3 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 18:53:44 -0400
Subject: [PATCH 25/33] Changed back to non-generic Operand until we resolve
 how to handle generics.

---
 .../org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java   | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
index f3caa0c4926..8447b985bb0 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
@@ -79,7 +79,7 @@ public static  Operand softmaxCrossEntrop
       axis += logits.asOutput().shape().numDimensions();
     }
 
-    Operand preciseLogits =
+    Operand preciseLogits =
         (Operand)
             logits; // cannot use generics cause logits of bool gets cast to TFloat32
 
@@ -90,7 +90,7 @@ public static  Operand softmaxCrossEntrop
       preciseLogits = Cast.create(scope, logits, TFloat32.DTYPE);
     }
     /* cannot use generics on DataType because preciseLogits may have been cast. */
-    DataType dtype = preciseLogits.asOutput().dataType();
+    DataType dtype = preciseLogits.asOutput().dataType();
     Operand castLabels = Cast.create(scope, labels, dtype);
     Operand inputRank = Cast.create(scope, Rank.create(scope, preciseLogits), TInt64.DTYPE);
     Shape shape = logits.asOutput().shape();

From b8d3ac2d001251c95bd55ed9cd902431108468bd Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Thu, 3 Sep 2020 18:55:55 -0400
Subject: [PATCH 26/33] Regenerated due to creation of
 SoftmaxCrossEntropyWithLogits.java,  SigmoidCrossEntropyWithLogits.java, and
 SparseSoftmaxCrossEntropyWithLogits.java under package org.tensorflow.op.nn
 in

---
 .../annotations/org/tensorflow/op/NnOps.java  | 136 ++++++++++++------
 1 file changed, 89 insertions(+), 47 deletions(-)

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 8374a864ec2..e15cccdd339 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
@@ -20,7 +20,6 @@
 import java.util.List;
 import org.tensorflow.DataType;
 import org.tensorflow.Operand;
-import org.tensorflow.op.core.NN;
 import org.tensorflow.op.nn.AvgPool;
 import org.tensorflow.op.nn.AvgPool3d;
 import org.tensorflow.op.nn.AvgPool3dGrad;
@@ -84,10 +83,13 @@
 import org.tensorflow.op.nn.Relu;
 import org.tensorflow.op.nn.Relu6;
 import org.tensorflow.op.nn.Selu;
+import org.tensorflow.op.nn.SigmoidCrossEntropyWithLogits;
 import org.tensorflow.op.nn.Softmax;
+import org.tensorflow.op.nn.SoftmaxCrossEntropyWithLogits;
 import org.tensorflow.op.nn.Softsign;
 import org.tensorflow.op.nn.SpaceToBatch;
 import org.tensorflow.op.nn.SpaceToDepth;
+import org.tensorflow.op.nn.SparseSoftmaxCrossEntropyWithLogits;
 import org.tensorflow.op.nn.TopK;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
@@ -1756,49 +1758,53 @@ public  Selu selu(Operand features) {
   }
 
   /**
-   * Computes sigmoid cross entropy given `logits`.
+   * Computes sigmoid cross entropy given logits.
    *
    *  
Measures the probability error in discrete classification tasks in which each class is
    *  independent and not mutually exclusive. For instance, one could perform multilabel
    *  classification where a picture can contain both an elephant and a dog at the same time.
    *
-   *  
For brevity, let `x = logits`, `z = labels`. The logistic loss is
+   *  
For brevity, let x = logits, z = labels. The logistic loss in
+   *  pseudo-code is
    *
    *  
-   *      z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
-   *      = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
-   *      = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
-   *      = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
-   *      = (1 - z) * x + log(1 + exp(-x))
-   *      = x - x * z + log(1 + exp(-x))
+   *  z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
+   *   = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))
+   *   = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))
+   *   = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))
+   *   = (1 - z) * x + log(1 + exp(-x))
+   *   = x - x * z + log(1 + exp(-x))
    *  

    *
-   *  
For x < 0, to avoid overflow in exp(-x), we reformulate the above
+   *  
For x < 0, to avoid overflow in exp(-x), we reformulate the above
    *
    *  
-   *       x - x * z + log(1 + exp(-x))
-   *       = log(exp(x)) - x * z + log(1 + exp(-x))
-   *       = - x * z + log(1 + exp(x))
+   *  x - x * z + log(1 + exp(-x))
+   *   = log(exp(x)) - x * z + log(1 + exp(-x))
+   *   = - x * z + log(1 + exp(x))
    *  

    *
    *  
Hence, to ensure stability and avoid overflow, the implementation uses this equivalent
    *  formulation
    *
    *  
-   *      max(x, 0) - x * z + log(1 + exp(-abs(x)))
+   *    max(x, 0) - x * z + log(1 + exp(-abs(x)))
    *  

    *
-   *  
`logits` and `labels` must have the same type and shape.
+   *  
logits and labels must have the same type and shape.
+   *
+   *  

    *
    * @param scope The TensorFlow scope
    * @param labels the labels
    * @param logits the logits of type float32 or float64
    * @param  the type of labels and logits
    * @return the component-wise logistic losses.
+   * @throws IllegalArgumentException if logits' and labels' do not have the same shape
    */
   public  Operand sigmoidCrossEntropyWithLogits(Operand labels,
       Operand logits) {
-    return NN.sigmoidCrossEntropyWithLogits(scope, labels, logits);
+    return SigmoidCrossEntropyWithLogits.sigmoidCrossEntropyWithLogits(scope, labels, logits);
   }
 
   /**
@@ -1817,48 +1823,55 @@ public  Softmax softmax(Operand logits) {
   }
 
   /**
-   * Computes softmax cross entropy between `logits` and `labels`.
+   * Computes softmax cross entropy between logits and labels.
    *
    *  
Measures the probability error in discrete classification tasks in which the classes are
    *  mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is
    *  labeled with one and only one label: an image can be a dog or a truck, but not both.
    *
-   *  
**NOTE:** While the classes are mutually exclusive, their probabilities need not be. All
-   *  that is required is that each row of `labels` is a valid probability distribution. If they are
-   *  not, the computation of the gradient will be incorrect.
+   *  
NOTE:
+   *
+   *  
While the classes are mutually exclusive, their probabilities need not be. All that is
+   *  required is that each row of labels is a valid probability distribution. If they
+   *  are not, the computation of the gradient will be incorrect.
    *
-   *  
If using exclusive `labels` (wherein one and only one class is true at a time), see
-   *  `sparse_softmax_cross_entropy_with_logits`.
+   *  
If using exclusive labels (wherein one and only one class is true at a time),
+   *  see {@link org.tensorflow.op.NnOps#sparseSoftmaxCrossEntropyWithLogits}
    *
    *  
Usage:
    *
    *  
-   *    >>> logits = [[4.0, 2.0, 1.0], [0.0, 5.0, 1.0]]
-   *    >>> labels = [[1.0, 0.0, 0.0], [0.0, 0.8, 0.2]]
-   *    >>> tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits)
-   *    
+   *    Operand<TFloat32> logits =
+   *        tf.constant(new float[][] {{4.0F, 2.0F, 1.0F}, {0.0F, 5.0F, 1.0F}} );
+   *    Operand<TFloat32> labels =
+   *        tf.constant(new float[][] {{1.0F, 0.0F, 0.0F}, {0.0F, 0.8F, 0.2F}} );
+   *    Operand<TFloat32> output =
+   *        tf.nn.softmaxCrossEntropyWithLogits(labels, logits, -1);
+   *    // output Shape = [2]
+   *    // dataType = FLOAT (1)
+   *    // values { 0.169846, 0.824745 }
    *  

    *
-   *  
Backpropagation will happen into both `logits` and `labels`. To disallow backpropagation
-   *  into `labels`, pass label tensors through `tf.stop_gradient` before feeding it to this
-   *  function.
+   *  
Backpropagation will happen into both logits and labels. To
+   *  disallow backpropagation into labels, pass label tensors through 
+   *  tf.stopGradient before feeding it to this function.
    *
    * @param scope current scope
    * @param labels Each vector along the class dimension should hold a valid probability
-   *      distribution e.g. for the case in which labels are of shape `[batch_size, num_classes]`,
-   *      each row of `labels[i]` must be a valid probability distribution.
+   *      distribution e.g. for the case in which labels are of shape [batch_size, num_classes]
+   *      , each row of labels[i] must be a valid probability distribution.
    * @param logits Per-label activations, typically a linear output. These activation energies are
    *      interpreted as unnormalized log probabilities.
    * @param axis The class dimension. -1 is the last dimension.
-   * @param  the data type of the logits
+   * @param  the data type of the logits
    * @param  the number type of the operands
-   * @return the softmax cross entropy loss. Its type is the same as `logits` and its shape is the
-   *      same as `labels` except that it does not have the last dimension of `labels`.
+   * @return the softmax cross entropy loss. Its type is the same as logits and its
+   *      shape is the same as labels except that it does not have the last dimension of
+   *      labels.
    */
   public  Operand softmaxCrossEntropyWithLogits(
       Operand labels, Operand logits, int axis) {
-    return NN.softmaxCrossEntropyWithLogits(scope, labels, logits, axis);
+    return SoftmaxCrossEntropyWithLogits.softmaxCrossEntropyWithLogits(scope, labels, logits, axis);
   }
 
   /**
@@ -2050,22 +2063,51 @@ public  SpaceToDepth spaceToDepth(Operand input, Long blo
   }
 
   /**
-   * Computes sparse softmax cross entropy between `logits` and `labels`.
+   * Computes sparse softmax cross entropy between logits and labels.
+   *
+   *  
Measures the probability error in discrete classification tasks in which the classes are
+   *  mutually exclusive (each entry is in exactly one class). For example, each CIFAR-10 image is
+   *  labeled with one and only one label: an image can be a dog or a truck, but not both.
+   *
+   *  
NOTE:
+   *
+   *  
For this operation, the probability of a given label is considered exclusive. That is, soft
+   *  classes are not allowed, and the labels vector must provide a single specific
+   *  index for the true class for each row of logits (each minibatch entry). For soft
+   *  softmax classification with a probability distribution for each entry, {@link
+   *  org.tensorflow.op.NnOps#softmaxCrossEntropyWithLogits}.
+   *
+   *  
WARNING:
+   *
+   *  
This op expects unscaled logits, since it performs a softmax on logits
+   *   internally for efficiency. Do not call this op with the output of softmax,
+   *  as it will produce incorrect results.
+   *
+   *  
A common use case is to have logits of shape [batchSize, numClasses] and have
+   *  labels of shape [batchSize], but higher dimensions are supported, in which case
+   *  the dim-th dimension is assumed to be of size numClasses. 
+   *  logits must have the dataType of TFloat16, TFloat32
+   *  , or TFloat64, and labels must have the dtype of TInt32
+   *  or TInt64.
    *
    * @param scope current scope
-   * @param labels `Tensor` of shape `[d_0, d_1, ..., d_{r-1}]` (where `r` is rank of `labels` and
-   *      result) and dtype `int32` or `int64`. Each entry in `labels` must be an index in `[0,
-   *      num_classes)`. Other values will raise an exception when this op is run on CPU, and return
-   *      `NaN` for corresponding loss and gradient rows on GPU.
-   * @param logits Per-label activations (typically a linear output) of shape `[d_0, d_1, ...,
-   *      d_{r-1}, num_classes]` and dtype `float16`, `float32`, or `float64`. These activation
-   *      energies are interpreted as unnormalized log probabilities.
-   * @return A `Tensor` of the same shape as `labels` and of the same type as `logits` with the
-   *      softmax cross entropy loss.
+   * @param labels Tensor of shape [d_0, d_1, ..., d_{r-1}] (where r
+   *       is rank of labels and result) and the dataType is TInt32
+   *      or TInt64. Each entry in labels must be an index in [0,
+   *      numClasses). Other values will raise an exception when this op is run on CPU, and
+   *      return NaN for corresponding loss and gradient rows on GPU.
+   * @param logits Per-label activations (typically a linear output) of shape [d_0, d_1, ...,
+   *      d_{r-1}, numClasses] and dataType of TFloat16, TFloat32,
+   *      or TFloat64. These activation energies are interpreted as unnormalized log
+   *      probabilities.
+   * @return A Tensor of the same shape as labels and of the same type as
+   *      logits with the softmax cross entropy loss.
+   * @throws IllegalArgumentException If logits are scalars (need to have rank >= 1) or if the rank
+   *      of the labels is not equal to the rank of the logits minus one.
    */
   public  Operand sparseSoftmaxCrossEntropyWithLogits(
       Operand labels, Operand logits) {
-    return NN.sparseSoftmaxCrossEntropyWithLogits(scope, labels, logits);
+    return SparseSoftmaxCrossEntropyWithLogits.sparseSoftmaxCrossEntropyWithLogits(scope, labels, logits);
   }
 
   /**

From c32fc5be951166ffde8d8763dcc99dd7e5879e86 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Mon, 7 Sep 2020 14:15:30 -0400
Subject: [PATCH 27/33] change snake case to camel case. format code

---
 .../keras/optimizers/AdaDeltaTest.java        | 330 +++++------
 .../keras/optimizers/AdaGradDATest.java       |  64 +--
 .../keras/optimizers/AdaGradTest.java         |  97 ++--
 .../tensorflow/keras/optimizers/AdamTest.java | 143 ++---
 .../keras/optimizers/AdamaxTest.java          | 115 ++--
 .../tensorflow/keras/optimizers/FtrlTest.java | 196 +++----
 .../keras/optimizers/NadamTest.java           | 140 ++---
 .../keras/optimizers/RMSPropTest.java         | 514 +++++++++---------
 .../tensorflow/keras/optimizers/SGDTest.java  | 114 ++--
 9 files changed, 721 insertions(+), 992 deletions(-)

diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java
index 8a7c8af9fae..52de6b6b0e1 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java
@@ -14,26 +14,8 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
-import static org.tensorflow.framework.optimizers.AdaDelta.ACCUMULATOR;
-import static org.tensorflow.framework.optimizers.AdaDelta.ACCUMULATOR_UPDATE;
+import org.junit.jupiter.api.*;
 import org.tensorflow.framework.optimizers.Optimizer.GradAndVar;
-import static org.tensorflow.keras.optimizers.AdaDelta.EPSILON_DEFAULT;
-import static org.tensorflow.keras.optimizers.AdaDelta.EPSILON_KEY;
-import static org.tensorflow.keras.optimizers.AdaDelta.LEARNING_RATE_DEFAULT;
-import static org.tensorflow.keras.optimizers.AdaDelta.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.AdaDelta.RHO_DEFAULT;
-import static org.tensorflow.keras.optimizers.AdaDelta.RHO_RATE_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
@@ -42,185 +24,167 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.tensorflow.framework.optimizers.AdaDelta.ACCUMULATOR;
+import static org.tensorflow.framework.optimizers.AdaDelta.ACCUMULATOR_UPDATE;
 
 /** Test cases for AdaDelta Optimizer */
 public class AdaDeltaTest {
 
-    private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
-    private int index;
+  public AdaDeltaTest() {}
 
-    public AdaDeltaTest() {
-    }
+  @BeforeAll
+  public static void setUpClass() {}
 
-    @BeforeAll
-    public static void setUpClass() {
-    }
+  @AfterAll
+  public static void tearDownClass() {}
 
-    @AfterAll
-    public static void tearDownClass() {
-    }
+  @BeforeEach
+  public void setUp() {}
 
-    @BeforeEach
-    public void setUp() {
-    }
-
-    @AfterEach
-    public void tearDown() {
-    }
+  @AfterEach
+  public void tearDown() {}
 
-    /**
-     * Test of create method, of class AdaDelta.
-     */
-    @Test
-    public void testCreate() {
-         try (TestSession session = TestSession.createTestSession(tf_mode)) {
-            Ops tf = session.getTF();
-            Map config = new HashMap<>();
-            config.put(NAME_KEY, "AdaDelta");
-            config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-            config.put(RHO_RATE_KEY, RHO_DEFAULT);
-            config.put(EPSILON_KEY, EPSILON_DEFAULT);
-            AdaDelta expResult = new AdaDelta(tf);
-            AdaDelta result = AdaDelta.create(tf, config);
-            assertEquals(expResult.getConfig(), result.getConfig());
-        }
-    }
+  @Test
+  public void testConstructAdadeltaWithLR() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Ops tf = session.getTF();
+      AdaDelta opt = new AdaDelta(tf, 1.0F, 0.9F, 1.F);
+      AdaDelta opt2 = new AdaDelta(tf, 0.1F, 0.9F, 1.F);
+      AdaDelta opt3 = new AdaDelta(tf, 0.1F, 0.9F, 1e-8F);
+      String format = "AdaDelta{learningRate=%s, rho=%s, epsilon=%s}";
+      String optExpected = String.format(format, 1.0F, 0.9F, 1.F);
+      String opt2Expected = String.format(format, 0.1F, 0.9F, 1.F);
+      String opt3Expected = String.format(format, 0.1F, 0.9F, 1e-8F);
 
-    @Test
-    public void testConstructAdadeltaWithLR() {
-         try (TestSession session = TestSession.createTestSession(tf_mode)) {
-            Ops tf = session.getTF();
-            AdaDelta opt = new AdaDelta(tf, 1.0F, 0.9F, 1.F);
-            AdaDelta opt2 = new AdaDelta(tf, 0.1F, 0.9F, 1.F);
-            AdaDelta opt3 = new AdaDelta(tf, 0.1F, 0.9F, 1e-8F);
-            String format = "AdaDelta{learningRate=%s, rho=%s, epsilon=%s}";
-            String optExpected = String.format(format, 1.0F, 0.9F, 1.F);
-            String opt2Expected = String.format(format, 0.1F, 0.9F, 1.F);
-            String opt3Expected = String.format(format, 0.1F, 0.9F, 1e-8F);
-
-            String optString = opt.toString();
-            String opt2String = opt2.toString();
-            String opt3String = opt3.toString();
-
-            assertEquals(optExpected, optString);
-            assertEquals(opt2Expected, opt2String);
-            assertEquals(opt3Expected, opt3String);
-        }
+      String optString = opt.toString();
+      String opt2String = opt2.toString();
+      String opt3String = opt3.toString();
 
+      assertEquals(optExpected, optString);
+      assertEquals(opt2Expected, opt2String);
+      assertEquals(opt3Expected, opt3String);
     }
-
-    @Test
-    public void testConstructAdadeltaWithEpsilonValues() {
-         try (TestSession session = TestSession.createTestSession(tf_mode)) {
-            Ops tf = session.getTF();
-            AdaDelta opt = new AdaDelta(tf);
-            Map config = opt.getConfig();
-            assertEquals(EPSILON_DEFAULT, (float) config.get(EPSILON_KEY));
-
-            opt = new AdaDelta(tf, LEARNING_RATE_DEFAULT, RHO_DEFAULT, 1e-8F);
-            config = opt.getConfig();
-            assertEquals(1e-8F, (float) config.get(EPSILON_KEY));
-        }
+  }
+
+  @Test
+  public void testConstructOptions() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Ops tf = session.getTF();
+      AdaDelta.Options options =
+          AdaDelta.Options.builder()
+              .name("myAdaDelta")
+              .learningRate(1.0F)
+              .rho(0.9F)
+              .epsilon(1.F)
+              .build();
+      AdaDelta opt = new AdaDelta(tf, options);
+
+      String format = "AdaDelta{learningRate=%s, rho=%s, epsilon=%s}";
+      String optExpected = String.format(format, 1.0F, 0.9F, 1.F);
+
+      String optString = opt.toString();
+
+      assertEquals(optExpected, optString);
     }
-
-    @Test
-    public void testBasic() {
-        int num_updates = 4; // # number of ADADELTA steps to perform
-        float[] grads = {0.2F, 0.1F, 0.01F};
-        float[] lrs = {1.0F, 0.5F, 0.1F};
-        for (float grad : grads) {
-            for (float lr : lrs) {
-                 try (TestSession session = TestSession.createTestSession(tf_mode)) {
-                    Ops tf = session.getTF();
-                    float[] var0_init = {1.0F, 2.0F};
-                    float[] var1_init = {3.0F, 4.0F};
-                    float[] fgrads = {grad, grad};
-                    Shape shape = Shape.of(var0_init.length);
-                    Variable var0 = tf.withName("var0").variable(shape, TFloat32.DTYPE);
-                    Variable var1 = tf.withName("var1").variable(shape, TFloat32.DTYPE);
-
-                    Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-                    Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
-
-                    Constant cgrads = tf.constant(fgrads);
-
-                    float accum = 0.0F;
-                    float accum_update = 0.0F;
-                    float rho = 0.95F;
-                    float epsilon = 1e-8F;
-                    float epsilon1 = 1e-5F;
-
-                    /* build the GradsAnvVars */
-                    List gradsAndVars = new ArrayList<>();
-                    gradsAndVars.add(new GradAndVar<>(cgrads.asOutput(), var0.asOutput()));
-                    gradsAndVars.add(new GradAndVar<>(cgrads.asOutput(), var1.asOutput()));
-
-                    /* get the Optimizer */
-                    AdaDelta adaDelta = new AdaDelta(tf, lr, rho, epsilon);
-
-                    /**
-                     * apply gradients
-                     */
-                    Op adadelta_update = adaDelta.applyGradients(gradsAndVars, "AdaDeltaTest");
-
-                    /* Create and validae the shapes of the slota */
-                    Variable[] slots = new Variable[2];
-                    Variable[] slotUpdates = new Variable[2];
-
-                    slots[0] = adaDelta.getSlot(var0.asOutput(), ACCUMULATOR).get();
-                    assertEquals(slots[0].asOutput().shape(), var0.asOutput().shape());
-
-                    slotUpdates[0] = adaDelta.getSlot(var0.asOutput(), ACCUMULATOR_UPDATE).get();
-                    assertEquals(slotUpdates[0].asOutput().shape(), var0.asOutput().shape());
-
-                    slots[1] = adaDelta.getSlot(var1.asOutput(), ACCUMULATOR).get();
-                    assertEquals(slots[1].asOutput().shape(), var1.asOutput().shape());
-
-                    slotUpdates[1] = adaDelta.getSlot(var1.asOutput(), ACCUMULATOR_UPDATE).get();
-                    assertEquals(slotUpdates[1].asOutput().shape(), var1.asOutput().shape());
-
-                    /* initialize the local variables */
-                    session.run(var0Initializer);
-                    session.run(var1Initializer);
-
-                    /**
-                     * initialize the accumulators
-                     */
-                    session.run(tf.init());
-
-                    /**
-                     * make sure the variables were initialized properly
-                     */
-                    session.evaluate(var0_init, var0);
-                    session.evaluate(var1_init, var1);
-
-                    float[] updates = new float[num_updates];
-                    float tot_update = 0;
-                    for (int step = 0; step < num_updates; step++) {
-                        session.run(adadelta_update);
-                        accum = accum * rho + (float) Math.pow(grad, 2) * (1.0F - rho);
-                        updates[step] = ((float) Math.sqrt(accum_update + epsilon)
-                                * (float) (1 / Math.sqrt(accum + epsilon)) * grad);
-                        accum_update = (accum_update * rho + ((float) Math.pow(updates[step], 2) * (1.0F - rho)));
-                        tot_update += updates[step] * lr;
-                        
-                        for (int i = 0; i < 2; i++) {
-                            session.evaluate(accum, slots[i]);
-                            session.evaluate(accum_update, slotUpdates[i]);
-                        }
-
-                        Float[] var0_initUpdate = {var0_init[0] - tot_update, var0_init[1] - tot_update};
-                        Float[] var1_initUpdate = {var1_init[0] - tot_update, var1_init[1] - tot_update};
-                        
-                        session.evaluate(var0_initUpdate, var0);
-                        session.evaluate(var1_initUpdate, var1);
-
-                    }
-
-                }
+  }
+
+  @Test
+  public void testBasic() {
+    int numUpdates = 4; // # number of ADADELTA steps to perform
+    float[] grads = {0.2F, 0.1F, 0.01F};
+    float[] lrs = {1.0F, 0.5F, 0.1F};
+    for (float grad : grads) {
+      for (float lr : lrs) {
+        try (TestSession session = TestSession.createTestSession(tfMode)) {
+          Ops tf = session.getTF();
+          float[] var0Init = {1.0F, 2.0F};
+          float[] var1Init = {3.0F, 4.0F};
+          float[] fgrads = {grad, grad};
+          Shape shape = Shape.of(var0Init.length);
+          Variable var0 = tf.withName("var0").variable(shape, TFloat32.DTYPE);
+          Variable var1 = tf.withName("var1").variable(shape, TFloat32.DTYPE);
+
+          Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+          Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
+
+          Constant cgrads = tf.constant(fgrads);
+
+          float accum = 0.0F;
+          float accumUpdate = 0.0F;
+          float rho = 0.95F;
+          float epsilon = 1e-8F;
+
+          /* build the GradsAnvVars */
+          List> gradsAndVars = new ArrayList<>();
+          gradsAndVars.add(new GradAndVar<>(cgrads.asOutput(), var0.asOutput()));
+          gradsAndVars.add(new GradAndVar<>(cgrads.asOutput(), var1.asOutput()));
+
+          /* get the Optimizer */
+          AdaDelta adaDelta = new AdaDelta(tf, lr, rho, epsilon);
+
+          /*apply gradients */
+          Op adadeltaUpdate = adaDelta.applyGradients(gradsAndVars, "AdaDeltaTest");
+
+          /* Create and validate the shapes of the slota */
+          Variable[] slots = new Variable[2];
+          Variable[] slotUpdates = new Variable[2];
+
+          slots[0] = adaDelta.getSlot(var0.asOutput(), ACCUMULATOR).get();
+          assertEquals(slots[0].asOutput().shape(), var0.asOutput().shape());
+
+          slotUpdates[0] = adaDelta.getSlot(var0.asOutput(), ACCUMULATOR_UPDATE).get();
+          assertEquals(slotUpdates[0].asOutput().shape(), var0.asOutput().shape());
+
+          slots[1] = adaDelta.getSlot(var1.asOutput(), ACCUMULATOR).get();
+          assertEquals(slots[1].asOutput().shape(), var1.asOutput().shape());
+
+          slotUpdates[1] = adaDelta.getSlot(var1.asOutput(), ACCUMULATOR_UPDATE).get();
+          assertEquals(slotUpdates[1].asOutput().shape(), var1.asOutput().shape());
+
+          /* initialize the local variables */
+          session.run(var0Initializer);
+          session.run(var1Initializer);
+
+          /* initialize the accumulators */
+          session.run(tf.init());
+
+          /* make sure the variables were initialized properly */
+          session.evaluate(var0Init, var0);
+          session.evaluate(var1Init, var1);
+
+          float[] updates = new float[numUpdates];
+          float totUpdate = 0;
+          for (int step = 0; step < numUpdates; step++) {
+            session.run(adadeltaUpdate);
+            accum = accum * rho + (float) Math.pow(grad, 2) * (1.0F - rho);
+            updates[step] =
+                ((float) Math.sqrt(accumUpdate + epsilon)
+                    * (float) (1 / Math.sqrt(accum + epsilon))
+                    * grad);
+            accumUpdate = (accumUpdate * rho + ((float) Math.pow(updates[step], 2) * (1.0F - rho)));
+            totUpdate += updates[step] * lr;
+
+            for (int i = 0; i < 2; i++) {
+              session.evaluate(accum, slots[i]);
+              session.evaluate(accumUpdate, slotUpdates[i]);
             }
+
+            Float[] var0InitUpdate = {var0Init[0] - totUpdate, var0Init[1] - totUpdate};
+            Float[] var1InitUpdate = {var1Init[0] - totUpdate, var1Init[1] - totUpdate};
+
+            session.evaluate(var0InitUpdate, var0);
+            session.evaluate(var1InitUpdate, var1);
+          }
         }
+      }
     }
-
+  }
 }
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
index 3931db4da97..57a5f5c0bd8 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
@@ -14,20 +14,8 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
+import org.junit.jupiter.api.*;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.keras.optimizers.AdaGradDA.INITIAL_ACCUM_KEY;
-import static org.tensorflow.keras.optimizers.AdaGradDA.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
@@ -37,10 +25,13 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
+import java.util.ArrayList;
+import java.util.List;
+
 /** Test cases for AdaGradDA Optimizer */
 public class AdaGradDATest {
 
-  private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
   int index;
 
@@ -58,42 +49,27 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of create method, of class AdaGradDA. */
-  @Test
-  public void testCreate() {
-    try (TestSession testSession = TestSession.createTestSession(tf_mode)) {
-      Ops tf = testSession.getTF();
-      Map config = new HashMap<>();
-      config.put(NAME_KEY, "AdaDelta");
-      config.put(LEARNING_RATE_KEY, 2.0F);
-      config.put(INITIAL_ACCUM_KEY, 0.1F);
-      AdaGradDA expResult = new AdaGradDA(tf, 2.0F, 0.1F, 0.0F, 0.0F);
-      AdaGradDA result = AdaGradDA.create(tf, config);
-      assertEquals(expResult.getConfig(), result.getConfig());
-    }
-  }
-
   @Test
   public void testBasic() {
-    float[] var0_init = {0.0F, 0.0F};
-    float[] var1_init = {0.0F, 0.0F};
-    float[] grads0_init = {0.1F, 0.2F};
-    float[] grads1_init = {0.01F, 0.02F};
+    float[] var0Init = {0.0F, 0.0F};
+    float[] var1Init = {0.0F, 0.0F};
+    float[] grads0Init = {0.1F, 0.2F};
+    float[] grads1Init = {0.01F, 0.02F};
     float epsilon = 1e-8F;
     float epsilon1 = 1e-5F;
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       /* initialize the local variables */
       /* initialize the local variables */
@@ -109,14 +85,14 @@ public void testBasic() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      Op ada_update = instance.applyGradients(gradsAndVars, "AdGradDATest");
+      Op adaUpdate = instance.applyGradients(gradsAndVars, "AdGradDATest");
 
       /** initialize the accumulators */
       session.run(tf.init());
 
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
-      session.run(ada_update);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
+      session.run(adaUpdate);
       float[] expected0 = {-0.904534F, -1.603567F};
       session.evaluate(expected0, var0);
       float[] expected1 = {-0.094821f, -0.189358f};
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
index 28c45c4c8c3..92701b37d67 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
@@ -14,21 +14,8 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
-import static org.tensorflow.framework.optimizers.AdaGrad.ACCUMULATOR;
+import org.junit.jupiter.api.*;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.keras.optimizers.AdaGrad.INITIAL_ACCUM_KEY;
-import static org.tensorflow.keras.optimizers.AdaGrad.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import org.tensorflow.keras.utils.ND;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -41,10 +28,15 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.tensorflow.framework.optimizers.AdaGrad.ACCUMULATOR;
+
 /** Test cases for AdaGrad Optimizer */
 public class AdaGradTest {
-  private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
-  int index;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
   public AdaGradTest() {}
 
@@ -60,53 +52,38 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of create method, of class AdaGrad. */
-  @Test
-  public void testCreate() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
-      Ops tf = session.getTF();
-      Map config = new HashMap<>();
-      config.put(NAME_KEY, "AdaDelta");
-      config.put(LEARNING_RATE_KEY, 2.0F);
-      config.put(INITIAL_ACCUM_KEY, 0.1F);
-      AdaGrad expResult = new AdaGrad(tf, 2.0F, 0.1F);
-      AdaGrad result = AdaGrad.create(tf, config);
-      assertEquals(expResult.getConfig(), result.getConfig());
-    }
-  }
-
   @Test
   public void testBasic() {
     int numSteps = 3;
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {3.0F, 4.0F};
-    float[] grads0_init = {0.1F, 0.1F};
-    float[] grads1_init = {0.01F, 0.01F};
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {3.0F, 4.0F};
+    float[] grads0Init = {0.1F, 0.1F};
+    float[] grads1Init = {0.01F, 0.01F};
     float epsilon = 1e-8F;
     float epsilon1 = 1e-5F;
     float[] accum0 = {0.1f, 0.1f};
     float[] accum1 = {0.1f, 0.1f};
 
-    FloatNdArray var0_np = NdArrays.vectorOf(var0_init);
-    FloatNdArray var1_np = NdArrays.vectorOf(var1_init);
-    FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init);
-    FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init);
-    FloatNdArray accum0_np = NdArrays.vectorOf(accum0);
-    FloatNdArray accum1_np = NdArrays.vectorOf(accum1);
+    FloatNdArray var0Np = NdArrays.vectorOf(var0Init);
+    FloatNdArray var1Np = NdArrays.vectorOf(var1Init);
+    FloatNdArray grads0Np = NdArrays.vectorOf(grads0Init);
+    FloatNdArray grads1Np = NdArrays.vectorOf(grads1Init);
+    FloatNdArray accum0Np = NdArrays.vectorOf(accum0);
+    FloatNdArray accum1Np = NdArrays.vectorOf(accum1);
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       float learningRate = 3.0F;
 
@@ -117,7 +94,7 @@ public void testBasic() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      Op ada_update = instance.applyGradients(gradsAndVars, "AdGradTest");
+      Op adaUpdate = instance.applyGradients(gradsAndVars, "AdGradTest");
 
       Variable[] accumulatorSlots = new Variable[2];
       accumulatorSlots[0] = instance.getSlot(var0.asOutput(), ACCUMULATOR).get();
@@ -134,25 +111,25 @@ public void testBasic() {
       session.run(tf.init());
 
       /** make sure the variables were initialized properly */
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       for (int step = 0; step < numSteps; step++) {
-        session.run(ada_update);
+        session.run(adaUpdate);
 
-        accum0_np = caclulateAccum(accum0_np, grads0_np);
-        var0_np = calculate(var0_np, accum0_np, grads0_np, learningRate);
-        session.evaluate(var0_np, var0);
+        accum0Np = caclulateAccum(accum0Np, grads0Np);
+        var0Np = calculate(var0Np, accum0Np, grads0Np, learningRate);
+        session.evaluate(var0Np, var0);
 
-        accum1_np = caclulateAccum(accum1_np, grads1_np);
-        var1_np = calculate(var1_np, accum1_np, grads1_np, learningRate);
-        session.evaluate(var1_np, var1);
+        accum1Np = caclulateAccum(accum1Np, grads1Np);
+        var1Np = calculate(var1Np, accum1Np, grads1Np, learningRate);
+        session.evaluate(var1Np, var1);
       }
     }
   }
 
   private FloatNdArray caclulateAccum(FloatNdArray accum, FloatNdArray grads) {
-    // accum + g_t * g_t
+    // accum + gT * gT
     FloatNdArray squareG = ND.square(grads);
     FloatNdArray result = ND.add(accum, squareG);
     return result;
@@ -160,7 +137,7 @@ private FloatNdArray caclulateAccum(FloatNdArray accum, FloatNdArray grads) {
 
   private FloatNdArray calculate(
       FloatNdArray param, FloatNdArray accum, FloatNdArray grads, float learningRate) {
-    // param - lr * g_t / (np.sqrt(accum_t) + epsilon)
+    // param - lr * gT / (np.sqrt(accumT) + epsilon)
     FloatNdArray divisor = ND.add(ND.sqrt(accum), 1e-07f);
     FloatNdArray dividend = ND.mul(learningRate, grads);
     FloatNdArray quotient = ND.div(dividend, divisor);
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
index 6f1d13d83d6..75c2fd9c610 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
@@ -14,29 +14,9 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
+import org.junit.jupiter.api.*;
 import org.tensorflow.Tensor;
-import static org.tensorflow.framework.optimizers.Adam.FIRST_MOMENT;
-import static org.tensorflow.framework.optimizers.Adam.SECOND_MOMENT;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.keras.optimizers.Adam.BETA_ONE_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adam.BETA_ONE_KEY;
-import static org.tensorflow.keras.optimizers.Adam.BETA_TWO_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adam.BETA_TWO_KEY;
-import static org.tensorflow.keras.optimizers.Adam.EPSILON_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adam.EPSILON_KEY;
-import static org.tensorflow.keras.optimizers.Adam.LEARNING_RATE_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adam.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import org.tensorflow.keras.utils.ND;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -49,9 +29,16 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.tensorflow.framework.optimizers.Adam.FIRST_MOMENT;
+import static org.tensorflow.framework.optimizers.Adam.SECOND_MOMENT;
+
 /** Test cases for Adam Optimizer */
 public class AdamTest {
-  private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
   int index;
 
@@ -69,55 +56,38 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of create method, of class Adam. */
-  @Test
-  public void testCreate() {
-    try (TestSession testSession = TestSession.createTestSession(tf_mode)) {
-      Ops tf = testSession.getTF();
-      Map config = new HashMap<>();
-      config.put(NAME_KEY, "AdaDelta");
-      config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-      config.put(BETA_ONE_KEY, BETA_ONE_DEFAULT);
-      config.put(BETA_TWO_KEY, BETA_TWO_DEFAULT);
-      config.put(EPSILON_KEY, EPSILON_DEFAULT);
-      AdaDelta expResult = new AdaDelta(tf);
-      AdaDelta result = AdaDelta.create(tf, config);
-      assertEquals(expResult.getConfig(), result.getConfig());
-    }
-  }
-
   @Test
   public void testBasic() {
     float m0 = 0.0F;
     float v0 = 0.0F;
     float m1 = 0.0F;
     float v1 = 0.0F;
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {3.0F, 4.0F};
-    float[] grads0_init = {0.1F, 0.1F};
-    float[] grads1_init = {0.01F, 0.01F};
-    FloatNdArray var0_np = NdArrays.vectorOf(var0_init);
-    FloatNdArray var1_np = NdArrays.vectorOf(var1_init);
-    FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init);
-    FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init);
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {3.0F, 4.0F};
+    float[] grads0Init = {0.1F, 0.1F};
+    float[] grads1Init = {0.01F, 0.01F};
+    FloatNdArray var0Np = NdArrays.vectorOf(var0Init);
+    FloatNdArray var1Np = NdArrays.vectorOf(var1Init);
+    FloatNdArray grads0Np = NdArrays.vectorOf(grads0Init);
+    FloatNdArray grads1Np = NdArrays.vectorOf(grads1Init);
 
     float epsilon1 = 1e-3F;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
       session.setEpsilon(epsilon1);
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       /* initialize the local variables */
       session.run(var0Initializer);
@@ -153,16 +123,16 @@ public void testBasic() {
       secondMomentSlots[1] = instance.getSlot(var1.asOutput(), SECOND_MOMENT).get();
       assertEquals(secondMomentSlots[1].asOutput().shape(), var1.asOutput().shape());
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
-      FloatNdArray m0_np = NdArrays.ofFloats(shape1);
-      FloatNdArray v0_np = NdArrays.ofFloats(shape1);
-      FloatNdArray m1_np = NdArrays.ofFloats(shape1);
-      FloatNdArray v1_np = NdArrays.ofFloats(shape1);
+      FloatNdArray m0Np = NdArrays.ofFloats(shape0);
+      FloatNdArray v0Np = NdArrays.ofFloats(shape0);
+      FloatNdArray m1Np = NdArrays.ofFloats(shape1);
+      FloatNdArray v1Np = NdArrays.ofFloats(shape1);
 
       for (int step = 0; step < 3; step++) {
 
@@ -175,7 +145,7 @@ public void testBasic() {
             session
                 .getGraphSession()
                 .runner()
-                .fetch("beta1_power")
+                .fetch("beta1Power")
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
@@ -191,7 +161,7 @@ public void testBasic() {
             session
                 .getGraphSession()
                 .runner()
-                .fetch("beta2_power")
+                .fetch("beta2Power")
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
@@ -205,57 +175,54 @@ public void testBasic() {
         }
         session.run(update);
 
-        float lr_t =
+        float lrT =
             learningRate
                 * (float) Math.sqrt(1 - (float) Math.pow(beta2, (step + 1)))
                 / (1 - (float) Math.pow(beta1, (step + 1)));
 
-        m0_np = calculateM(m0_np, grads0_np, beta1);
-        v0_np = calculateV(v0_np, grads0_np, beta2);
-        var0_np = calculateParam(var0_np, lr_t, m0_np, v0_np, 1e-7F);
+        m0Np = calculateM(m0Np, grads0Np, beta1);
+        v0Np = calculateV(v0Np, grads0Np, beta2);
+        var0Np = calculateParam(var0Np, lrT, m0Np, v0Np, 1e-7F);
 
-        m1_np = calculateM(m1_np, grads1_np, beta1);
-        v1_np = calculateV(v1_np, grads1_np, beta2);
-        var1_np = calculateParam(var1_np, lr_t, m1_np, v1_np, 1e-7F);
+        m1Np = calculateM(m1Np, grads1Np, beta1);
+        v1Np = calculateV(v1Np, grads1Np, beta2);
+        var1Np = calculateParam(var1Np, lrT, m1Np, v1Np, 1e-7F);
 
         // evaluate var 0 and var1
-        session.evaluate(var0_np, var0);
-        session.evaluate(var1_np, var1);
+        session.evaluate(var0Np, var0);
+        session.evaluate(var1Np, var1);
 
         // first moment
-        session.evaluate(m0_np, firstMomentSlots[0]);
-        session.evaluate(m1_np, firstMomentSlots[1]);
+        session.evaluate(m0Np, firstMomentSlots[0]);
+        session.evaluate(m1Np, firstMomentSlots[1]);
 
         // second moment
-        session.evaluate(v0_np, secondMomentSlots[0]);
-        session.evaluate(v1_np, secondMomentSlots[1]);
+        session.evaluate(v0Np, secondMomentSlots[0]);
+        session.evaluate(v1Np, secondMomentSlots[1]);
       }
     }
   }
 
-  private FloatNdArray calculateM(FloatNdArray m, FloatNdArray g_t, float beta) {
-    // m_t = beta1 * m + (1 - beta1) * g_t
-    return ND.add(ND.mul(m, beta), ND.mul(g_t, (1 - beta)));
+  private FloatNdArray calculateM(FloatNdArray m, FloatNdArray gT, float beta) {
+    // mT = beta1 * m + (1 - beta1) * gT
+    return ND.add(ND.mul(m, beta), ND.mul(gT, (1 - beta)));
   }
 
-  private FloatNdArray calculateV(FloatNdArray v, FloatNdArray g_t, float beta) {
-    // beta2 * v + (1 - beta2) * g_t * g_t
+  private FloatNdArray calculateV(FloatNdArray v, FloatNdArray gT, float beta) {
+    // beta2 * v + (1 - beta2) * gT * gT
     FloatNdArray mul1 = ND.mul(v, beta);
-    FloatNdArray squareG = ND.square(g_t);
+    FloatNdArray squareG = ND.square(gT);
     FloatNdArray mul2 = ND.mul((1 - beta), squareG);
     FloatNdArray add = ND.add(mul1, mul2);
     return add;
-
-    // return ND.add(ND.mul(v, beta),
-    //     ND.mul((1-beta), ND.square(g_t)));
   }
 
   private FloatNdArray calculateParam(
-      FloatNdArray param, float lr_t, FloatNdArray m, FloatNdArray v, float epsilon) {
-    //  param - lr_t * m_t / (np.sqrt(v_t) + epsilon)
+      FloatNdArray param, float lrT, FloatNdArray m, FloatNdArray v, float epsilon) {
+    //  param - lrT * mT / (np.sqrt(vT) + epsilon)
     FloatNdArray sqrt = ND.sqrt(v);
     FloatNdArray divisor = ND.add(sqrt, epsilon);
-    FloatNdArray dividend = ND.mul(lr_t, m);
+    FloatNdArray dividend = ND.mul(lrT, m);
     FloatNdArray quotient = ND.div(dividend, divisor);
     FloatNdArray result = ND.sub(param, quotient);
     return result;
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
index 1d3dc9e76bf..9460984d124 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
@@ -14,29 +14,9 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
+import org.junit.jupiter.api.*;
 import org.tensorflow.Tensor;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.keras.optimizers.Adamax.BETA_ONE_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adamax.BETA_ONE_KEY;
-import static org.tensorflow.keras.optimizers.Adamax.BETA_TWO_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adamax.BETA_TWO_KEY;
-import static org.tensorflow.keras.optimizers.Adamax.EPSILON_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adamax.EPSILON_KEY;
-import static org.tensorflow.keras.optimizers.Adamax.FIRST_MOMENT;
-import static org.tensorflow.keras.optimizers.Adamax.LEARNING_RATE_DEFAULT;
-import static org.tensorflow.keras.optimizers.Adamax.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.Adamax.SECOND_MOMENT;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import org.tensorflow.keras.utils.ND;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -49,16 +29,20 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.tensorflow.keras.optimizers.Adamax.*;
+
 /** Test cases for Adamax Optimizer */
 public class AdamaxTest {
-  private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
   private static final int VAR = 0;
   private static final int M = 1;
   private static final int V = 2;
 
-  int index;
-
   public AdamaxTest() {}
 
   @BeforeAll
@@ -73,27 +57,10 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of create method, of class Adamax. */
-  @Test
-  public void testCreate() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
-      Ops tf = session.getTF();
-      Map config = new HashMap<>();
-      config.put(NAME_KEY, "AdaDelta");
-      config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-      config.put(BETA_ONE_KEY, BETA_ONE_DEFAULT);
-      config.put(BETA_TWO_KEY, BETA_TWO_DEFAULT);
-      config.put(EPSILON_KEY, EPSILON_DEFAULT);
-      AdaDelta expResult = new AdaDelta(tf);
-      AdaDelta result = AdaDelta.create(tf, config);
-      assertEquals(expResult.getConfig(), result.getConfig());
-    }
-  }
-
   /** Test of getOptimizerName method, of class Adamax. */
   @Test
   public void testGetOptimizerName() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
       Adamax instance = new Adamax(tf);
       String expResult = "Adamax";
@@ -108,37 +75,37 @@ public void testBasic() {
 
     int numSteps = 3;
 
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {3.0F, 4.0F};
-    float[] grads0_init = {0.1F, 0.1F};
-    float[] grads1_init = {0.01F, 0.01F};
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {3.0F, 4.0F};
+    float[] grads0Init = {0.1F, 0.1F};
+    float[] grads1Init = {0.01F, 0.01F};
 
     float[] zeros = {0.0F, 0.0F};
     FloatNdArray m0 = NdArrays.vectorOf(zeros);
     FloatNdArray v0 = NdArrays.vectorOf(zeros);
     FloatNdArray m1 = NdArrays.vectorOf(zeros);
     FloatNdArray v1 = NdArrays.vectorOf(zeros);
-    FloatNdArray var0_np = NdArrays.vectorOf(var0_init);
-    FloatNdArray var1_np = NdArrays.vectorOf(var1_init);
-    FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init);
-    FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init);
+    FloatNdArray var0Np = NdArrays.vectorOf(var0Init);
+    FloatNdArray var1Np = NdArrays.vectorOf(var1Init);
+    FloatNdArray grads0Np = NdArrays.vectorOf(grads0Init);
+    FloatNdArray grads1Np = NdArrays.vectorOf(grads1Init);
 
     float epsilon = 1e-6f;
     float epsilon1 = 1e-3F;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       /* initialize the local variables */
       session.run(var0Initializer);
@@ -177,13 +144,13 @@ public void testBasic() {
       session.setEpsilon(epsilon1);
       for (int step = 0; step < numSteps; step++) {
         // Test powers
-        final float beta1_power = (float) Math.pow(BETA_ONE_DEFAULT, step + 1);
+        final float beta1Power = (float) Math.pow(BETA_ONE_DEFAULT, step + 1);
 
         try (Tensor result =
             session
                 .getGraphSession()
                 .runner()
-                .fetch("beta1_power")
+                .fetch("beta1Power")
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
@@ -192,31 +159,31 @@ public void testBasic() {
               .scalars()
               .forEach(
                   f -> {
-                    assertEquals(beta1_power, f.getFloat(), epsilon1);
+                    assertEquals(beta1Power, f.getFloat(), epsilon1);
                   });
         }
         session.run(update);
 
-        FloatNdArray[] resultNP = calculate(var0_np, grads0_np, step, m0, v0);
-        var0_np = resultNP[VAR];
+        FloatNdArray[] resultNP = calculate(var0Np, grads0Np, step, m0, v0);
+        var0Np = resultNP[VAR];
         m0 = resultNP[M];
         v0 = resultNP[V];
 
-        resultNP = calculate(var1_np, grads1_np, step, m1, v1);
-        var1_np = resultNP[VAR];
+        resultNP = calculate(var1Np, grads1Np, step, m1, v1);
+        var1Np = resultNP[VAR];
         m1 = resultNP[M];
         v1 = resultNP[V];
 
         // evaluate  var0 and var1
 
-        session.evaluate(var0_np, var0);
-        session.evaluate(var1_np, var1);
+        session.evaluate(var0Np, var0);
+        session.evaluate(var1Np, var1);
       }
     }
   }
 
   private FloatNdArray[] calculate(
-      FloatNdArray var_np, FloatNdArray grads_np, int step, FloatNdArray m, FloatNdArray v) {
+      FloatNdArray varNp, FloatNdArray gradsNp, int step, FloatNdArray m, FloatNdArray v) {
     float alpha = 0.001F;
     float beta1 = BETA_ONE_DEFAULT;
     float beta2 = BETA_TWO_DEFAULT;
@@ -226,15 +193,15 @@ private FloatNdArray[] calculate(
     float oneMinusBeta1Pow = 1.F - (float) Math.pow(beta1, step + 1);
     float alpha1 = alpha / oneMinusBeta1Pow;
 
-    // beta1 * m + (1 - beta1) * g_t;
-    m = ND.add(ND.mul(beta1, m), ND.mul(oneMinusBeta1, grads_np));
-    // np.maximum(beta2 * v, np.abs(g_t))
-    v = ND.max(ND.mul(beta2, v), ND.abs(grads_np));
-    // param_t = param - (alpha / (1 - beta1**(t + 1))) * (m_t / (v_t + epsilon))
-    var_np = ND.sub(var_np, ND.mul(alpha1, ND.div(m, ND.add(v, espilon))));
+    // beta1 * m + (1 - beta1) * gT;
+    m = ND.add(ND.mul(beta1, m), ND.mul(oneMinusBeta1, gradsNp));
+    // np.maximum(beta2 * v, np.abs(gT))
+    v = ND.max(ND.mul(beta2, v), ND.abs(gradsNp));
+    // paramT = param - (alpha / (1 - beta1**(t + 1))) * (mT / (vT + epsilon))
+    varNp = ND.sub(varNp, ND.mul(alpha1, ND.div(m, ND.add(v, espilon))));
 
     FloatNdArray[] result = new FloatNdArray[3];
-    result[VAR] = var_np;
+    result[VAR] = varNp;
     result[M] = m;
     result[V] = v;
     return result;
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
index d61197348af..4f1eb25246b 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
@@ -14,24 +14,8 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
+import org.junit.jupiter.api.*;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.keras.optimizers.Ftrl.INITIAL_ACCUM_VALUE_KEY;
-import static org.tensorflow.keras.optimizers.Ftrl.L1STRENGTH_KEY;
-import static org.tensorflow.keras.optimizers.Ftrl.L2STRENGTH_KEY;
-import static org.tensorflow.keras.optimizers.Ftrl.L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY;
-import static org.tensorflow.keras.optimizers.Ftrl.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.Ftrl.LEARNING_RATE_POWER_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
@@ -41,9 +25,14 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
 /** Test cases for Ftrl Optimizer */
 public class FtrlTest {
-  private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
+  private TestSession.Mode tfMode = TestSession.Mode.GRAPH;
   int index;
 
   public FtrlTest() {}
@@ -60,29 +49,10 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of initConfig method, of class Ftrl. */
-  @Test
-  public void testInitConfig() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
-      Ops tf = session.getTF();
-      Map config = new HashMap<>();
-      config.put(NAME_KEY, "Ftrl");
-      config.put(LEARNING_RATE_KEY, 2.0F);
-      config.put(LEARNING_RATE_POWER_KEY, -0.5F);
-      config.put(INITIAL_ACCUM_VALUE_KEY, 0.1F);
-      config.put(L1STRENGTH_KEY, 0.0F);
-      config.put(L2STRENGTH_KEY, 0.0F);
-      config.put(L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY, 0.0F);
-      Ftrl expResult = new Ftrl(tf, 2.0F);
-      Ftrl result = Ftrl.create(tf, config);
-      assertEquals(expResult.getConfig(), result.getConfig());
-    }
-  }
-
   /** Test of getOptimizerName method, of class Ftrl. */
   @Test
   public void testGetOptimizerName() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
       Ftrl instance = new Ftrl(tf);
       String expResult = "Ftrl";
@@ -92,29 +62,29 @@ public void testGetOptimizerName() {
   }
 
   @Test
-  public void testFtrlWithL1_L2_L2Shrinkage() {
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {4.0F, 3.0F};
-    float[] grads0_init = {0.1F, 0.2F};
-    float[] grads1_init = {0.01F, 0.02F};
+  public void testFtrlWithL1L2L2Shrinkage() {
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {4.0F, 3.0F};
+    float[] grads0Init = {0.1F, 0.2F};
+    float[] grads1Init = {0.01F, 0.02F};
     float epsilon = 1e-8F;
     float epsilon1 = 1e-5F;
 
     int numSteps = 10;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       float learningRate = 3.0F;
 
@@ -123,10 +93,10 @@ public void testFtrlWithL1_L2_L2Shrinkage() {
               tf,
               learningRate,
               -0.5F, // learningRatePower
-              0.1F, // initial_accumulator_value
-              0.001F, // l1_regularization_strength
-              2.0F, // l2_regularization_strength
-              0.1F // l2_shrinkage_regularization_strength
+              0.1F, // initialAccumulatorValue
+              0.001F, // l1RegularizationStrength
+              2.0F, // l2RegularizationStrength
+              0.1F // l2ShrinkageRegularizationStrength
               );
 
       /* build the GradsAnvVars */
@@ -134,7 +104,7 @@ public void testFtrlWithL1_L2_L2Shrinkage() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest");
+      Op ftrlUpdate = instance.applyGradients(gradsAndVars, "FtrlTest");
 
       /* initialize the local variables */
       session.run(var0Initializer);
@@ -143,11 +113,11 @@ public void testFtrlWithL1_L2_L2Shrinkage() {
       /** initialize the accumulators */
       session.run(tf.init());
 
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       for (int i = 0; i < numSteps; i++) {
-        session.run(ftrl_update);
+        session.run(ftrlUpdate);
       }
 
       float[] expectedVar0 = {-0.22578995F, -0.44345796F};
@@ -159,28 +129,28 @@ public void testFtrlWithL1_L2_L2Shrinkage() {
 
   @Test
   public void testFtrlWithL1() {
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {4.0F, 3.0F};
-    float[] grads0_init = {0.1F, 0.2F};
-    float[] grads1_init = {0.01F, 0.02F};
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {4.0F, 3.0F};
+    float[] grads0Init = {0.1F, 0.2F};
+    float[] grads1Init = {0.01F, 0.02F};
     float epsilon = 1e-8F;
     float epsilon1 = 1e-5F;
 
     int numSteps = 10;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       float learningRate = 3.0F;
 
@@ -189,11 +159,10 @@ public void testFtrlWithL1() {
               tf,
               learningRate,
               Ftrl.LEARNING_RATE_POWER_DEFAULT, // learningRatePower
-              0.1F, // initial_accumulator_value
-              0.001F, // l1_regularization_strength
-              0.0F, // l2_regularization_strength
-              Ftrl
-                  .L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT // l2_shrinkage_regularization_strength
+              0.1F, // initialAccumulatorValue
+              0.001F, // l1RegularizationStrength
+              0.0F, // l2RegularizationStrength
+              Ftrl.L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT // l2ShrinkageRegularizationStrength
               );
 
       /* build the GradsAnvVars */
@@ -201,7 +170,7 @@ public void testFtrlWithL1() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest");
+      Op ftrlUpdate = instance.applyGradients(gradsAndVars, "FtrlTest");
 
       /* initialize the local variables */
       session.run(var0Initializer);
@@ -210,11 +179,11 @@ public void testFtrlWithL1() {
       /** initialize the accumulators */
       session.run(tf.init());
 
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       for (int i = 0; i < numSteps; i++) {
-        session.run(ftrl_update);
+        session.run(ftrlUpdate);
       }
 
       float[] expectedVar0 = {-7.66718769F, -10.91273689F};
@@ -226,29 +195,29 @@ public void testFtrlWithL1() {
   }
 
   @Test
-  public void testFtrlWithL1_L2() {
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {4.0F, 3.0F};
-    float[] grads0_init = {0.1F, 0.2F};
-    float[] grads1_init = {0.01F, 0.02F};
+  public void testFtrlWithL1L2() {
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {4.0F, 3.0F};
+    float[] grads0Init = {0.1F, 0.2F};
+    float[] grads1Init = {0.01F, 0.02F};
     float epsilon = 1e-8F;
     float epsilon1 = 1e-5F;
 
     int numSteps = 10;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       float learningRate = 3.0F;
 
@@ -257,11 +226,10 @@ public void testFtrlWithL1_L2() {
               tf,
               learningRate,
               Ftrl.LEARNING_RATE_POWER_DEFAULT, // learningRatePower
-              0.1F, // initial_accumulator_value
-              0.001F, // l1_regularization_strength
-              2.0F, // l2_regularization_strength
-              Ftrl
-                  .L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT // l2_shrinkage_regularization_strength
+              0.1F, // initialAccumulatorValue
+              0.001F, // l1RegularizationStrength
+              2.0F, // l2RegularizationStrength
+              Ftrl.L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT // l2ShrinkageRegularizationStrength
               );
 
       /* build the GradsAnvVars */
@@ -269,7 +237,7 @@ public void testFtrlWithL1_L2() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest");
+      Op ftrlUpdate = instance.applyGradients(gradsAndVars, "FtrlTest");
 
       /* initialize the local variables */
       session.run(var0Initializer);
@@ -278,11 +246,11 @@ public void testFtrlWithL1_L2() {
       /** initialize the accumulators */
       session.run(tf.init());
 
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       for (int i = 0; i < numSteps; i++) {
-        session.run(ftrl_update);
+        session.run(ftrlUpdate);
       }
 
       float[] expectedVar0 = {-0.24059935F, -0.46829352F};
@@ -295,28 +263,28 @@ public void testFtrlWithL1_L2() {
 
   @Test
   public void doTestFtrlwithoutRegularization() {
-    float[] var0_init = {0.0F, 0.0F};
-    float[] var1_init = {0.0F, 0.0F};
-    float[] grads0_init = {0.1F, 0.2F};
-    float[] grads1_init = {0.01F, 0.02F};
+    float[] var0Init = {0.0F, 0.0F};
+    float[] var1Init = {0.0F, 0.0F};
+    float[] grads0Init = {0.1F, 0.2F};
+    float[] grads1Init = {0.01F, 0.02F};
     float epsilon = 1e-8F;
     float epsilon1 = 1e-5F;
 
     int numSteps = 3;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       float learningRate = 3.0F;
 
@@ -326,7 +294,7 @@ public void doTestFtrlwithoutRegularization() {
       List gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
-      Op ftrl_update = instance.applyGradients(gradsAndVars, "FtrlTest");
+      Op ftrlUpdate = instance.applyGradients(gradsAndVars, "FtrlTest");
 
       /* initialize the local variables */
       session.run(var0Initializer);
@@ -335,11 +303,11 @@ public void doTestFtrlwithoutRegularization() {
       /** initialize the accumulators */
       session.run(tf.init());
 
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       for (int i = 0; i < numSteps; i++) {
-        session.run(ftrl_update);
+        session.run(ftrlUpdate);
       }
 
       float[] expectedVar0 = {-2.60260963F, -4.29698515F};
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
index 2b8bce40471..3eab6288268 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
@@ -14,29 +14,9 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
+import org.junit.jupiter.api.*;
 import org.tensorflow.Tensor;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.keras.optimizers.Adamax.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.Nadam.BETA_ONE_DEFAULT;
-import static org.tensorflow.keras.optimizers.Nadam.BETA_ONE_KEY;
-import static org.tensorflow.keras.optimizers.Nadam.BETA_TWO_DEFAULT;
-import static org.tensorflow.keras.optimizers.Nadam.BETA_TWO_KEY;
-import static org.tensorflow.keras.optimizers.Nadam.EPSILON_DEFAULT;
-import static org.tensorflow.keras.optimizers.Nadam.EPSILON_KEY;
-import static org.tensorflow.keras.optimizers.Nadam.FIRST_MOMENT;
-import static org.tensorflow.keras.optimizers.Nadam.LEARNING_RATE_DEFAULT;
-import static org.tensorflow.keras.optimizers.Nadam.SECOND_MOMENT;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
 import org.tensorflow.keras.utils.ND;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -49,15 +29,21 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.tensorflow.keras.optimizers.Nadam.FIRST_MOMENT;
+import static org.tensorflow.keras.optimizers.Nadam.SECOND_MOMENT;
+
 /** Test cases for Nadam Optimizer */
 public class NadamTest {
-  private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
   private static final int VAR = 0;
   private static final int M = 1;
   private static final int V = 2;
 
-  int index = 0;
   float momentum = 1;
 
   public NadamTest() {}
@@ -74,27 +60,10 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of create method, of class Nadam. */
-  @Test
-  public void testCreate() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
-      Ops tf = session.getTF();
-      Map config = new HashMap<>();
-      config.put(NAME_KEY, "AdaDelta");
-      config.put(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-      config.put(BETA_ONE_KEY, BETA_ONE_DEFAULT);
-      config.put(BETA_TWO_KEY, BETA_TWO_DEFAULT);
-      config.put(EPSILON_KEY, EPSILON_DEFAULT);
-      AdaDelta expResult = new AdaDelta(tf);
-      AdaDelta result = AdaDelta.create(tf, config);
-      assertEquals(expResult.getConfig(), result.getConfig());
-    }
-  }
-
   /** Test of getOptimizerName method, of class Nadam. */
   @Test
   public void testGetOptimizerName() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
       Nadam instance = new Nadam(tf);
       String expResult = "Nadam";
@@ -109,10 +78,10 @@ public void testBasic() {
 
     int numSteps = 3;
 
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {3.0F, 4.0F};
-    float[] grads0_init = {0.1F, 0.1F};
-    float[] grads1_init = {0.01F, 0.01F};
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {3.0F, 4.0F};
+    float[] grads0Init = {0.1F, 0.1F};
+    float[] grads1Init = {0.01F, 0.01F};
 
     float[] zeros = {0.0F, 0.0F};
     float[] ones = {1.0F, 1.0F};
@@ -121,27 +90,27 @@ public void testBasic() {
     FloatNdArray m1 = NdArrays.vectorOf(zeros);
     FloatNdArray v1 = NdArrays.vectorOf(zeros);
     FloatNdArray mcache = NdArrays.vectorOf(ones);
-    FloatNdArray var0_np = NdArrays.vectorOf(var0_init);
-    FloatNdArray var1_np = NdArrays.vectorOf(var1_init);
-    FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init);
-    FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init);
+    FloatNdArray var0Np = NdArrays.vectorOf(var0Init);
+    FloatNdArray var1Np = NdArrays.vectorOf(var1Init);
+    FloatNdArray grads0Np = NdArrays.vectorOf(grads0Init);
+    FloatNdArray grads1Np = NdArrays.vectorOf(grads1Init);
 
     float epsilon = 1e-6f;
     float epsilon1 = 1e-3F;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       Nadam instance = new Nadam(tf);
       /* build the GradsAnvVars */
@@ -176,8 +145,8 @@ public void testBasic() {
 
       session.setEpsilon(epsilon1);
 
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       try (Tensor result =
           session
@@ -222,13 +191,13 @@ public void testBasic() {
                   });
         }
         mcache = ND.mul(mcache, momentum);
-        FloatNdArray[] resultsNP = nadam_update_numpy(var0_np, grads0_np, step, m0, v0, mcache);
-        var0_np = resultsNP[VAR];
+        FloatNdArray[] resultsNP = nadamUpdateNdArray(var0Np, grads0Np, step, m0, v0, mcache);
+        var0Np = resultsNP[VAR];
         m0 = resultsNP[M];
         v0 = resultsNP[V];
 
-        resultsNP = nadam_update_numpy(var1_np, grads1_np, step, m1, v1, mcache);
-        var1_np = resultsNP[VAR];
+        resultsNP = nadamUpdateNdArray(var1Np, grads1Np, step, m1, v1, mcache);
+        var1Np = resultsNP[VAR];
         m1 = resultsNP[M];
         v1 = resultsNP[V];
 
@@ -241,46 +210,41 @@ public void testBasic() {
         session.evaluate(v1, secondMomentSlots[1]);
 
         // evaluate var0 and var1
-        session.evaluate(var0_np, var0);
-        session.evaluate(var1_np, var1);
+        session.evaluate(var0Np, var0);
+        session.evaluate(var1Np, var1);
       }
     }
   }
 
-  private FloatNdArray update_m_cache(FloatNdArray mcache, int t) {
-    float mu_t = 0.9F * (1.0F - 0.5F * (float) Math.pow(0.96, (0.004 * (t + 1))));
-    return ND.mul(mu_t, mcache);
-  }
-
-  private FloatNdArray[] nadam_update_numpy(
-      FloatNdArray var_np,
-      FloatNdArray grads_np,
+  private FloatNdArray[] nadamUpdateNdArray(
+      FloatNdArray varNp,
+      FloatNdArray gradsNp,
       int t,
       FloatNdArray m,
       FloatNdArray v,
-      FloatNdArray m_cache) {
+      FloatNdArray mCache) {
 
     float alpha = 0.001F;
     float beta1 = 0.9F;
     float beta2 = 0.999F;
     float epsilon = 1e-8F;
-    float mu_t = beta1 * (1F - 0.5F * (float) Math.pow(0.96, 0.004 * (t + 1)));
-    float mu_t_1 = beta1 * (1F - 0.5F * (float) Math.pow(0.96, (0.004 * (t + 2))));
-    FloatNdArray m_cache_t_1 = ND.mul(m_cache, mu_t_1);
-    FloatNdArray g_prime_t = ND.div(grads_np, ND.sub(1.0F, m_cache));
-    FloatNdArray m_t = ND.add(ND.mul(beta1, m), ND.mul((1 - beta1), grads_np));
-    FloatNdArray v_t = ND.add(ND.mul(beta2, v), ND.mul((1 - beta2), ND.square(grads_np)));
-
-    FloatNdArray m_prime_t = ND.div(m_t, ND.sub(1.F, m_cache_t_1));
-    FloatNdArray v_prime_t = ND.div(v_t, 1.F - (float) Math.pow(beta2, t + 1));
-    FloatNdArray m_bar_t = ND.add(ND.mul((1 - mu_t), g_prime_t), ND.mul(mu_t_1, m_prime_t));
-    FloatNdArray param_t =
-        ND.sub(var_np, ND.div(ND.mul(alpha, m_bar_t), ND.add(ND.sqrt(v_prime_t), epsilon)));
+    float muT = beta1 * (1F - 0.5F * (float) Math.pow(0.96, 0.004 * (t + 1)));
+    float muT1 = beta1 * (1F - 0.5F * (float) Math.pow(0.96, (0.004 * (t + 2))));
+    FloatNdArray mCacheT1 = ND.mul(mCache, muT1);
+    FloatNdArray gPrimeT = ND.div(gradsNp, ND.sub(1.0F, mCache));
+    FloatNdArray mT = ND.add(ND.mul(beta1, m), ND.mul((1 - beta1), gradsNp));
+    FloatNdArray vT = ND.add(ND.mul(beta2, v), ND.mul((1 - beta2), ND.square(gradsNp)));
+
+    FloatNdArray mPrimeT = ND.div(mT, ND.sub(1.F, mCacheT1));
+    FloatNdArray vPrimeT = ND.div(vT, 1.F - (float) Math.pow(beta2, t + 1));
+    FloatNdArray mBarT = ND.add(ND.mul((1 - muT), gPrimeT), ND.mul(muT1, mPrimeT));
+    FloatNdArray paramT =
+        ND.sub(varNp, ND.div(ND.mul(alpha, mBarT), ND.add(ND.sqrt(vPrimeT), epsilon)));
 
     FloatNdArray[] results = new FloatNdArray[3];
-    results[VAR] = param_t;
-    results[M] = m_t;
-    results[V] = v_t;
+    results[VAR] = paramT;
+    results[M] = mT;
+    results[V] = vT;
     return results;
   }
 }
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
index b8fb4f40ee9..cabf869536c 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
@@ -14,30 +14,8 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
+import org.junit.jupiter.api.*;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.framework.optimizers.RMSProp.MG;
-import static org.tensorflow.framework.optimizers.RMSProp.MOMENTUM;
-import static org.tensorflow.framework.optimizers.RMSProp.RMS;
-import static org.tensorflow.keras.optimizers.Ftrl.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
-import static org.tensorflow.keras.optimizers.RMSProp.CENTERED_DEFAULT;
-import static org.tensorflow.keras.optimizers.RMSProp.CENTERED_KEY;
-import static org.tensorflow.keras.optimizers.RMSProp.DECAY_DEFAULT;
-import static org.tensorflow.keras.optimizers.RMSProp.DECAY_KEY;
-import static org.tensorflow.keras.optimizers.RMSProp.EPSILON_DEFAULT;
-import static org.tensorflow.keras.optimizers.RMSProp.EPSILON_KEY;
-import static org.tensorflow.keras.optimizers.RMSProp.MOMENTUM_DEFAULT;
-import static org.tensorflow.keras.optimizers.RMSProp.MOMENTUM_KEY;
 import org.tensorflow.keras.utils.ND;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -50,258 +28,254 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
-/** Test cases for RMSProp Optimizer */
-public class RMSPropTest {
-    private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
-    
-    final int VAR_T = 0;
-    final int MG_T = 1;
-    final int RMS_T = 2;
-    final int MOM_T = 3;
-
-    int index;
-
-    public RMSPropTest() {
-    }
-
-    @BeforeAll
-    public static void setUpClass() {
-    }
-
-    @AfterAll
-    public static void tearDownClass() {
-    }
-
-    @BeforeEach
-    public void setUp() {
-    }
-
-    @AfterEach
-    public void tearDown() {
-    }
-
-    /**
-     * Test of create method, of class RMSProp.
-     */
-    @Test
-    public void testCreate() {
-        try (TestSession session = TestSession.createTestSession(tf_mode)) {
-            Ops tf = session.getTF();
-            Map config = new HashMap<>();
-            config.put(NAME_KEY, "Ftrl");
-            config.put(LEARNING_RATE_KEY, 2.0F);
-            config.put(DECAY_KEY, DECAY_DEFAULT);
-            config.put(MOMENTUM_KEY, MOMENTUM_DEFAULT);
-            config.put(EPSILON_KEY, EPSILON_DEFAULT);
-            config.put(CENTERED_KEY, CENTERED_DEFAULT);
-            Ftrl expResult = new Ftrl(tf, 2.0F);
-            Ftrl result = Ftrl.create(tf, config);
-            assertEquals(expResult.getConfig(), result.getConfig());
-        }
-    }
+import java.util.ArrayList;
+import java.util.List;
 
-    Object[][] _test_param_values = {
-        // learning_rate, rho (decay), momentum, epsilon, centered
-        {0.05F, 0.9F, 0.0F, 1e-3F, true},
-        {0.05F, 0.9F, 0.0F, 1e-3F, false},
-        {0.1F, 0.9F, 0.0F, 1e-3F, true},
-        {0.01F, 0.9F, 0.0F, 1e-5F, true},
-        {0.01F, 0.9F, 0.9F, 1e-5F, true}
-    };
-
-    @Test
-    public void testDense() {
-
-        int numSteps = 3;
-
-        for (int run = 0; run < _test_param_values.length; run++) {
-            try (TestSession session = TestSession.createTestSession(tf_mode)) {
-                Ops tf = session.getTF();
-                session.setEpsilon(1e-2f);
-                float[] var0_init = {1.0F, 2.0F};
-                float[] var1_init = {3.0F, 4.0F};
-                float[] grads0_init = {0.1F, 0.2F};
-                float[] grads1_init = {0.01F, 0.2F};
-                final float epsilon1 = 1e-2F;
-
-                FloatNdArray var0_np = NdArrays.vectorOf(var0_init);
-                FloatNdArray var1_np = NdArrays.vectorOf(var1_init);
-                FloatNdArray grads0_np = NdArrays.vectorOf(grads0_init);
-                FloatNdArray grads1_np = NdArrays.vectorOf(grads1_init);
-
-                Shape shape0 = Shape.of(var0_init.length);
-                Shape shape1 = Shape.of(var1_init.length);
-                Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-                Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
-
-                Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-                Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
-
-                Constant grads0 = tf.constant(grads0_init);
-                Constant grads1 = tf.constant(grads1_init);
-
-                // learning_rate, rho (decay), momentum, epsilon, centered
-                float learningRate = (float) (float) _test_param_values[run][0];
-                float decay = (float) _test_param_values[run][1];
-                float momentum = (float) _test_param_values[run][2];
-                float epsilon = (float) _test_param_values[run][3];
-                boolean centered = (boolean) _test_param_values[run][4];
-
-                RMSProp instance = new RMSProp(tf,
-                        learningRate,
-                        decay,
-                        momentum,
-                        epsilon,
-                        centered);
-
-                /* build the GradsAnvVars */
-                List gradsAndVars = new ArrayList<>();
-                gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
-                gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
-
-                Op update = instance.applyGradients(gradsAndVars, "RMSPropTest");
-
-                /* initialize the local variables */
-                session.run(var0Initializer);
-                session.run(var1Initializer);
-
-                /**
-                 * initialize the accumulators
-                 */
-                session.run(tf.init());
-
-                /**
-                 * make sure the variables were initialized properly
-                 */
-                session.evaluate(var0_init, var0);
-                session.evaluate(var1_init, var1);
-
-                Variable mg0 = centered ? instance.getSlot(var0.asOutput(), MG).get() : null;
-                Variable mg1 = centered ? instance.getSlot(var1.asOutput(), MG).get() : null;
-                Variable mom0 = momentum > 0.F ? instance.getSlot(var0.asOutput(), MOMENTUM).get() : null;
-                Variable mom1 = momentum > 0.F ? instance.getSlot(var1.asOutput(), MOMENTUM).get() : null;
-                Variable rms0 = instance.getSlot(var0.asOutput(), RMS).get();
-                Variable rms1 = instance.getSlot(var1.asOutput(), RMS).get();
-
-                float[] zeros = {0.0F, 0.0F};
-                float[] ones = {1.0F, 1.0F}; // temp to match RMSProp
-                FloatNdArray mg0_np = NdArrays.vectorOf(zeros);
-                FloatNdArray mg1_np = NdArrays.vectorOf(zeros);
-                FloatNdArray rms0_np = NdArrays.vectorOf(ones);
-                FloatNdArray rms1_np = NdArrays.vectorOf(ones);
-                FloatNdArray mom0_np = NdArrays.vectorOf(zeros);
-                FloatNdArray mom1_np = NdArrays.vectorOf(zeros);
-
-               
-
-                for (int i = 0; i < numSteps; i++) {
-                    session.run(update);
-                    FloatNdArray[] result0 = calc(var0_np, grads0_np, mg0_np, rms0_np,
-                            mom0_np, learningRate, decay, momentum, epsilon, centered);
-                    var0_np = result0[VAR_T];
-                    mg0_np = result0[MG_T];
-                    rms0_np = result0[RMS_T];
-                    mom0_np = result0[MOM_T];
-
-                    FloatNdArray[] result1 = calc(var1_np, grads1_np, mg1_np, rms1_np,
-                            mom1_np, learningRate, decay, momentum, epsilon, centered);
-
-                    var1_np = result1[VAR_T];
-                    mg1_np = result1[MG_T];
-                    rms1_np = result1[RMS_T];
-                    mom1_np = result1[MOM_T];
-
-                    if (centered) {
-                        session.evaluate(mg0_np, mg0);
-                        session.evaluate(mg0_np, mg0);
-                    }
-                    if (momentum > 0.F) {
-                        session.evaluate(mom0_np, mom0);
-                        session.evaluate(mom1_np, mom1);
-                    }
-
-                    /*     TODO the values returned from rms slot, do not match what I see in the python test */
-                    session.evaluate(rms0_np, rms0);
-                    session.evaluate(rms1_np, rms1);
-                    
-                    session.evaluate(var0_np, var0);
-                    session.evaluate(var1_np, var1);
-                }
-            }
-        }
-    }
+import static org.tensorflow.framework.optimizers.RMSProp.*;
 
-    FloatNdArray[] calc(FloatNdArray var_np, FloatNdArray grad_np, FloatNdArray mg_np,
-            FloatNdArray rms_np, FloatNdArray mom, float lr, float decay, float momentum,
-            float epsilon, boolean centered) {
-
-        FloatNdArray[] result = new FloatNdArray[4]; // var_t, mg_t, rms_t, mom_t
-        result[RMS_T] = calcRMS(rms_np, grad_np, decay); // RMS
-
-        FloatNdArray denom_t;
-        if (centered) {
-            result[MG_T] = calcMG(mg_np, grad_np, decay);
-            //rms_t - mg_t * mg_t
-            denom_t = ND.sub(result[RMS_T], ND.square(result[MG_T]));
-        } else {
-            result[MG_T] = mg_np;
-            denom_t = rms_np;
-        }
-        if (momentum > 0.F) {
-            //momentum * mom + lr * g / (np.sqrt(denom_t + epsilon))
-            result[MOM_T] = calcMom(momentum, mom, lr, grad_np, denom_t, epsilon);
-            //var_t = var - mom_t
-            result[VAR_T] = ND.sub(var_np, result[MOM_T]);
-        } else {
-            result[MOM_T] = mom;
-            result[VAR_T] = calcVar(var_np, grad_np, lr, denom_t, epsilon);
+/** Test cases for RMSProp Optimizer */
+public class RMSPropTest {
+  final int VAR_T = 0;
+  final int MG_T = 1;
+  final int RMS_T = 2;
+  final int MOM_T = 3;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
+  int index;
+  Object[][] TestParamValues = {
+    // learningRate, rho (decay), momentum, epsilon, centered
+    {0.05F, 0.9F, 0.0F, 1e-3F, true},
+    {0.05F, 0.9F, 0.0F, 1e-3F, false},
+    {0.1F, 0.9F, 0.0F, 1e-3F, true},
+    {0.01F, 0.9F, 0.0F, 1e-5F, true},
+    {0.01F, 0.9F, 0.9F, 1e-5F, true}
+  };
+
+  public RMSPropTest() {}
+
+  @BeforeAll
+  public static void setUpClass() {}
+
+  @AfterAll
+  public static void tearDownClass() {}
+
+  @BeforeEach
+  public void setUp() {}
+
+  @AfterEach
+  public void tearDown() {}
+
+  @Test
+  public void testDense() {
+
+    int numSteps = 3;
+
+    for (int run = 0; run < TestParamValues.length; run++) {
+      try (TestSession session = TestSession.createTestSession(tfMode)) {
+        Ops tf = session.getTF();
+        session.setEpsilon(1e-2f);
+        float[] var0Init = {1.0F, 2.0F};
+        float[] var1Init = {3.0F, 4.0F};
+        float[] grads0Init = {0.1F, 0.2F};
+        float[] grads1Init = {0.01F, 0.2F};
+        final float epsilon1 = 1e-2F;
+
+        FloatNdArray var0Np = NdArrays.vectorOf(var0Init);
+        FloatNdArray var1Np = NdArrays.vectorOf(var1Init);
+        FloatNdArray grads0Np = NdArrays.vectorOf(grads0Init);
+        FloatNdArray grads1Np = NdArrays.vectorOf(grads1Init);
+
+        Shape shape0 = Shape.of(var0Init.length);
+        Shape shape1 = Shape.of(var1Init.length);
+        Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
+        Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+
+        Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+        Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
+
+        Constant grads0 = tf.constant(grads0Init);
+        Constant grads1 = tf.constant(grads1Init);
+
+        // learningRate, rho (decay), momentum, epsilon, centered
+        float learningRate = (float) (float) TestParamValues[run][0];
+        float decay = (float) TestParamValues[run][1];
+        float momentum = (float) TestParamValues[run][2];
+        float epsilon = (float) TestParamValues[run][3];
+        boolean centered = (boolean) TestParamValues[run][4];
+
+        RMSProp instance = new RMSProp(tf, learningRate, decay, momentum, epsilon, centered);
+
+        /* build the GradsAnvVars */
+        List gradsAndVars = new ArrayList<>();
+        gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
+        gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
+
+        Op update = instance.applyGradients(gradsAndVars, "RMSPropTest");
+
+        /* initialize the local variables */
+        session.run(var0Initializer);
+        session.run(var1Initializer);
+
+        /** initialize the accumulators */
+        session.run(tf.init());
+
+        /** make sure the variables were initialized properly */
+        session.evaluate(var0Init, var0);
+        session.evaluate(var1Init, var1);
+
+        Variable mg0 = centered ? instance.getSlot(var0.asOutput(), MG).get() : null;
+        Variable mg1 = centered ? instance.getSlot(var1.asOutput(), MG).get() : null;
+        Variable mom0 =
+            momentum > 0.F ? instance.getSlot(var0.asOutput(), MOMENTUM).get() : null;
+        Variable mom1 =
+            momentum > 0.F ? instance.getSlot(var1.asOutput(), MOMENTUM).get() : null;
+        Variable rms0 = instance.getSlot(var0.asOutput(), RMS).get();
+        Variable rms1 = instance.getSlot(var1.asOutput(), RMS).get();
+
+        float[] zeros = {0.0F, 0.0F};
+        float[] ones = {1.0F, 1.0F}; // temp to match RMSProp
+        FloatNdArray mg0Np = NdArrays.vectorOf(zeros);
+        FloatNdArray mg1Np = NdArrays.vectorOf(zeros);
+        FloatNdArray rms0Np = NdArrays.vectorOf(ones);
+        FloatNdArray rms1Np = NdArrays.vectorOf(ones);
+        FloatNdArray mom0Np = NdArrays.vectorOf(zeros);
+        FloatNdArray mom1Np = NdArrays.vectorOf(zeros);
+
+        for (int i = 0; i < numSteps; i++) {
+          session.run(update);
+          FloatNdArray[] result0 =
+              calc(
+                  var0Np,
+                  grads0Np,
+                  mg0Np,
+                  rms0Np,
+                  mom0Np,
+                  learningRate,
+                  decay,
+                  momentum,
+                  epsilon,
+                  centered);
+          var0Np = result0[VAR_T];
+          mg0Np = result0[MG_T];
+          rms0Np = result0[RMS_T];
+          mom0Np = result0[MOM_T];
+
+          FloatNdArray[] result1 =
+              calc(
+                  var1Np,
+                  grads1Np,
+                  mg1Np,
+                  rms1Np,
+                  mom1Np,
+                  learningRate,
+                  decay,
+                  momentum,
+                  epsilon,
+                  centered);
+
+          var1Np = result1[VAR_T];
+          mg1Np = result1[MG_T];
+          rms1Np = result1[RMS_T];
+          mom1Np = result1[MOM_T];
+
+          if (centered) {
+            session.evaluate(mg0Np, mg0);
+            session.evaluate(mg0Np, mg0);
+          }
+          if (momentum > 0.F) {
+            session.evaluate(mom0Np, mom0);
+            session.evaluate(mom1Np, mom1);
+          }
+
+          /*     TODO the values returned from rms slot, do not match what I see in the python test */
+          session.evaluate(rms0Np, rms0);
+          session.evaluate(rms1Np, rms1);
+
+          session.evaluate(var0Np, var0);
+          session.evaluate(var1Np, var1);
         }
-    
-
-        return result;
-
+      }
     }
-
-    private FloatNdArray calcRMS(FloatNdArray rms_np, FloatNdArray grad_np, float decay) {
-        //rms * rho + (1 - rho) * g * g
-        FloatNdArray rms_rho = ND.mul(rms_np, decay);
-        FloatNdArray squareG = ND.square(grad_np);
-        float oneRHO = 1.0F - decay;
-        FloatNdArray decayG2 = ND.mul(oneRHO, squareG);
-        FloatNdArray result = ND.add(rms_rho, decayG2);
-        return result;
-    }
-
-    private FloatNdArray calcMG(FloatNdArray mg_np, FloatNdArray grad_np, float decay) {
-        //mg_t = mg * rho + (1 - rho) * g
-        FloatNdArray mg_rho = ND.mul(mg_np, decay);
-        float oneRHO = 1.0F - decay;
-        FloatNdArray decayG = ND.mul(oneRHO, grad_np);
-        FloatNdArray result = ND.add(mg_rho, decayG);
-        return result;
-
+  }
+
+  FloatNdArray[] calc(
+      FloatNdArray varNp,
+      FloatNdArray gradNp,
+      FloatNdArray mgNp,
+      FloatNdArray rmsNp,
+      FloatNdArray mom,
+      float lr,
+      float decay,
+      float momentum,
+      float epsilon,
+      boolean centered) {
+
+    FloatNdArray[] result = new FloatNdArray[4]; // varT, mgT, rmsT, momT
+    result[RMS_T] = calcRMS(rmsNp, gradNp, decay); // RMS
+
+    FloatNdArray denomT;
+    if (centered) {
+      result[MG_T] = calcMG(mgNp, gradNp, decay);
+      // rmsT - mgT * mgT
+      denomT = ND.sub(result[RMS_T], ND.square(result[MG_T]));
+    } else {
+      result[MG_T] = mgNp;
+      denomT = rmsNp;
     }
-
-    private FloatNdArray calcMom(float momentum, FloatNdArray mom, float lr,
-            FloatNdArray grad_np, FloatNdArray denom_t, float epsilon) {
-        // momentum * mom + lr * g / (np.sqrt(denom_t + epsilon))
-        FloatNdArray moMo = ND.mul(momentum, mom);
-        FloatNdArray dividend = ND.mul(lr, grad_np);
-        FloatNdArray divisor = ND.sqrt(ND.add(denom_t, epsilon));
-        FloatNdArray quotient = ND.div(dividend, divisor);
-        FloatNdArray result = ND.add(moMo, quotient);
-        return result;
-
+    if (momentum > 0.F) {
+      // momentum * mom + lr * g / (np.sqrt(denomT + epsilon))
+      result[MOM_T] = calcMom(momentum, mom, lr, gradNp, denomT, epsilon);
+      // varT = var - momT
+      result[VAR_T] = ND.sub(varNp, result[MOM_T]);
+    } else {
+      result[MOM_T] = mom;
+      result[VAR_T] = calcVar(varNp, gradNp, lr, denomT, epsilon);
     }
 
-    private FloatNdArray calcVar(FloatNdArray var_np, FloatNdArray grad_np, float lr,
-            FloatNdArray denom_t, float epsilon) {
-        // var - lr * g / (np.sqrt(denom_t) + epsilon)
-        FloatNdArray dividend = ND.mul(lr, grad_np);
-        FloatNdArray divisor = ND.add(ND.sqrt(denom_t), epsilon);
-        FloatNdArray quotient = ND.div(dividend, divisor);
-        FloatNdArray result = ND.sub(var_np, quotient);
-        return result;
-
-    }
+    return result;
+  }
+
+  private FloatNdArray calcRMS(FloatNdArray rmsNp, FloatNdArray gradNp, float decay) {
+    // rms * rho + (1 - rho) * g * g
+    FloatNdArray rmsRho = ND.mul(rmsNp, decay);
+    FloatNdArray squareG = ND.square(gradNp);
+    float oneRHO = 1.0F - decay;
+    FloatNdArray decayG2 = ND.mul(oneRHO, squareG);
+    FloatNdArray result = ND.add(rmsRho, decayG2);
+    return result;
+  }
+
+  private FloatNdArray calcMG(FloatNdArray mgNp, FloatNdArray gradNp, float decay) {
+    // mgT = mg * rho + (1 - rho) * g
+    FloatNdArray mgRho = ND.mul(mgNp, decay);
+    float oneRHO = 1.0F - decay;
+    FloatNdArray decayG = ND.mul(oneRHO, gradNp);
+    FloatNdArray result = ND.add(mgRho, decayG);
+    return result;
+  }
+
+  private FloatNdArray calcMom(
+      float momentum,
+      FloatNdArray mom,
+      float lr,
+      FloatNdArray gradNp,
+      FloatNdArray denomT,
+      float epsilon) {
+    // momentum * mom + lr * g / (np.sqrt(denomT + epsilon))
+    FloatNdArray moMo = ND.mul(momentum, mom);
+    FloatNdArray dividend = ND.mul(lr, gradNp);
+    FloatNdArray divisor = ND.sqrt(ND.add(denomT, epsilon));
+    FloatNdArray quotient = ND.div(dividend, divisor);
+    FloatNdArray result = ND.add(moMo, quotient);
+    return result;
+  }
+
+  private FloatNdArray calcVar(
+      FloatNdArray varNp, FloatNdArray gradNp, float lr, FloatNdArray denomT, float epsilon) {
+    // var - lr * g / (np.sqrt(denomT) + epsilon)
+    FloatNdArray dividend = ND.mul(lr, gradNp);
+    FloatNdArray divisor = ND.add(ND.sqrt(denomT), epsilon);
+    FloatNdArray quotient = ND.div(dividend, divisor);
+    FloatNdArray result = ND.sub(varNp, quotient);
+    return result;
+  }
 }
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
index 7e12b957f84..b36851a561e 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
@@ -14,24 +14,8 @@
 =======================================================================*/
 package org.tensorflow.keras.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import org.junit.jupiter.api.AfterEach;
-import org.junit.jupiter.api.AfterAll;
-import org.junit.jupiter.api.BeforeEach;
-import org.junit.jupiter.api.BeforeAll;
-import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
-import static org.tensorflow.framework.optimizers.Momentum.MOMENTUM;
+import org.junit.jupiter.api.*;
 import org.tensorflow.framework.optimizers.Optimizer;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
-import static org.tensorflow.keras.optimizers.SGD.LEARNING_RATE_KEY;
-import static org.tensorflow.keras.optimizers.SGD.MOMENTUM_DEFAULT;
-import static org.tensorflow.keras.optimizers.SGD.MOMENTUM_KEY;
-import static org.tensorflow.keras.optimizers.SGD.NESTEROV_DEFAULT;
-import static org.tensorflow.keras.optimizers.SGD.NESTEROV_KEY;
 import org.tensorflow.keras.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
@@ -41,12 +25,16 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
 
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.tensorflow.framework.optimizers.Momentum.MOMENTUM;
+
 /** Test cases for SGD Optimizer */
 public class SGDTest {
 
-  private TestSession.Mode tf_mode = TestSession.Mode.GRAPH;
-
-  int index;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
   public SGDTest() {}
 
@@ -62,26 +50,10 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of create method, of class SGD. */
-  @Test
-  public void testCreate() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
-      Ops tf = session.getTF();
-      Map config = new HashMap<>();
-      config.put(NAME_KEY, "Ftrl");
-      config.put(LEARNING_RATE_KEY, 2.0F);
-      config.put(MOMENTUM_KEY, MOMENTUM_DEFAULT);
-      config.put(NESTEROV_KEY, NESTEROV_DEFAULT);
-      SGD expResult = new SGD(tf, 2.0F);
-      SGD result = SGD.create(tf, config);
-      assertEquals(expResult.getConfig(), result.getConfig());
-    }
-  }
-
   /** Test of getOptimizerName method, of class SGD. */
   @Test
   public void testGetOptimizerName() {
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
       SGD instance = new SGD(tf);
       String expResult = "SGD";
@@ -92,28 +64,28 @@ public void testGetOptimizerName() {
 
   @Test
   public void testBasic() {
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {3.0F, 4.0F};
-    float[] grads0_init = {0.1F, 0.1F};
-    float[] grads1_init = {0.01F, 0.01F};
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {3.0F, 4.0F};
+    float[] grads0Init = {0.1F, 0.1F};
+    float[] grads1Init = {0.01F, 0.01F};
     float learningRate = 3.0F;
 
     float epsilon = 1e-6F;
     float epsilon1 = 1e-2F;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       /* build the GradsAnvVars */
       List gradsAndVars = new ArrayList<>();
@@ -131,8 +103,8 @@ public void testBasic() {
       session.run(tf.init());
 
       /** make sure the variables were initialized properly */
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       session.run(update); // 1 step
 
@@ -145,10 +117,10 @@ public void testBasic() {
 
   @Test
   public void testMomentum() {
-    float[] var0_init = {1.0F, 2.0F};
-    float[] var1_init = {3.0F, 4.0F};
-    float[] grads0_init = {0.1F, 0.1F};
-    float[] grads1_init = {0.01F, 0.01F};
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {3.0F, 4.0F};
+    float[] grads0Init = {0.1F, 0.1F};
+    float[] grads1Init = {0.01F, 0.01F};
 
     float learningRate = 2.0F;
     float momentum = 0.9F;
@@ -156,19 +128,19 @@ public void testMomentum() {
     float epsilon = 1e-6F;
     float epsilon1 = 1e-2F;
 
-    try (TestSession session = TestSession.createTestSession(tf_mode)) {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
-      Shape shape0 = Shape.of(var0_init.length);
-      Shape shape1 = Shape.of(var1_init.length);
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
       Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
 
-      Assign var0Initializer = tf.assign(var0, tf.constant(var0_init));
-      Assign var1Initializer = tf.assign(var1, tf.constant(var1_init));
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
 
-      Constant grads0 = tf.constant(grads0_init);
-      Constant grads1 = tf.constant(grads1_init);
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
 
       /* build the GradsAnvVars */
       List gradsAndVars = new ArrayList<>();
@@ -191,8 +163,8 @@ public void testMomentum() {
       session.run(tf.init());
 
       /** make sure the variables were initialized properly */
-      session.evaluate(var0_init, var0);
-      session.evaluate(var1_init, var1);
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
 
       session.run(update); // 1 step
 
@@ -208,20 +180,20 @@ public void testMomentum() {
 
       session.run(update); // step 2
 
-      float[] expectedMomentum0_2 = {(0.9f * 0.1f + 0.1f), (0.9f * 0.1f + 0.1f)};
-      float[] expectedMomentum1_2 = {(0.9f * 0.01f + 0.01f), (0.9f * 0.01f + 0.01f)};
-      session.evaluate(expectedMomentum0_2, momentumSlot0);
-      session.evaluate(expectedMomentum1_2, momentumSlot1);
+      float[] expectedMomentum02 = {(0.9f * 0.1f + 0.1f), (0.9f * 0.1f + 0.1f)};
+      float[] expectedMomentum12 = {(0.9f * 0.01f + 0.01f), (0.9f * 0.01f + 0.01f)};
+      session.evaluate(expectedMomentum02, momentumSlot0);
+      session.evaluate(expectedMomentum12, momentumSlot1);
 
-      float[] expectedVar0_2 = {
+      float[] expectedVar02 = {
         1.0F - (0.1F * 2.0F) - ((0.9F * 0.1F + 0.1F) * 2.0F),
         2.0F - (0.1F * 2.0F) - ((0.9F * 0.1F + 0.1F) * 2.0F)
       };
-      float[] expectedVar1_2 = {
+      float[] expectedVar12 = {
         2.98F - ((0.9F * 0.01F + 0.01F) * 2.0F), 3.98F - ((0.9F * 0.01F + 0.01F) * 2.0F)
       };
-      session.evaluate(expectedVar0_2, var0);
-      session.evaluate(expectedVar1_2, var1);
+      session.evaluate(expectedVar02, var0);
+      session.evaluate(expectedVar12, var1);
     }
   }
 }

From 171cd2f4f9878b00e35f3175b0a8c7954ef21f07 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Mon, 7 Sep 2020 14:38:12 -0400
Subject: [PATCH 28/33] clean upd warning,  format code

---
 .../keras/optimizers/AdaGradDATest.java       |  9 ++--
 .../keras/optimizers/AdaGradTest.java         | 15 +++---
 .../tensorflow/keras/optimizers/AdamTest.java | 34 +++-----------
 .../keras/optimizers/AdamaxTest.java          | 26 ++++------
 .../tensorflow/keras/optimizers/FtrlTest.java | 28 ++++-------
 .../keras/optimizers/NadamTest.java           | 22 ++-------
 .../keras/optimizers/RMSPropTest.java         | 47 +++++++++----------
 .../tensorflow/keras/optimizers/SGDTest.java  | 19 +++-----
 8 files changed, 68 insertions(+), 132 deletions(-)

diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
index 57a5f5c0bd8..7275e9f8113 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
@@ -24,6 +24,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -33,8 +34,6 @@ public class AdaGradDATest {
 
   private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
-  int index;
-
   public AdaGradDATest() {}
 
   @BeforeAll
@@ -55,8 +54,6 @@ public void testBasic() {
     float[] var1Init = {0.0F, 0.0F};
     float[] grads0Init = {0.1F, 0.2F};
     float[] grads1Init = {0.01F, 0.02F};
-    float epsilon = 1e-8F;
-    float epsilon1 = 1e-5F;
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
@@ -81,13 +78,13 @@ public void testBasic() {
       AdaGrad instance = new AdaGrad(tf, learningRate);
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
       Op adaUpdate = instance.applyGradients(gradsAndVars, "AdGradDATest");
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
       session.evaluate(var0Init, var0);
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
index 92701b37d67..d407209b87a 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
@@ -27,6 +27,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -59,8 +60,6 @@ public void testBasic() {
     float[] var1Init = {3.0F, 4.0F};
     float[] grads0Init = {0.1F, 0.1F};
     float[] grads1Init = {0.01F, 0.01F};
-    float epsilon = 1e-8F;
-    float epsilon1 = 1e-5F;
     float[] accum0 = {0.1f, 0.1f};
     float[] accum1 = {0.1f, 0.1f};
 
@@ -90,7 +89,7 @@ public void testBasic() {
       AdaGrad instance = new AdaGrad(tf, learningRate);
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -107,10 +106,10 @@ public void testBasic() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
-      /** make sure the variables were initialized properly */
+      /* make sure the variables were initialized properly */
       session.evaluate(var0Init, var0);
       session.evaluate(var1Init, var1);
 
@@ -131,8 +130,7 @@ public void testBasic() {
   private FloatNdArray caclulateAccum(FloatNdArray accum, FloatNdArray grads) {
     // accum + gT * gT
     FloatNdArray squareG = ND.square(grads);
-    FloatNdArray result = ND.add(accum, squareG);
-    return result;
+    return ND.add(accum, squareG);
   }
 
   private FloatNdArray calculate(
@@ -141,7 +139,6 @@ private FloatNdArray calculate(
     FloatNdArray divisor = ND.add(ND.sqrt(accum), 1e-07f);
     FloatNdArray dividend = ND.mul(learningRate, grads);
     FloatNdArray quotient = ND.div(dividend, divisor);
-    FloatNdArray result = ND.sub(param, quotient);
-    return result;
+    return ND.sub(param, quotient);
   }
 }
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
index 75c2fd9c610..82a47afbbbb 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
@@ -28,6 +28,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -40,8 +41,6 @@
 public class AdamTest {
   private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
-  int index;
-
   public AdamTest() {}
 
   @BeforeAll
@@ -58,10 +57,6 @@ public void tearDown() {}
 
   @Test
   public void testBasic() {
-    float m0 = 0.0F;
-    float v0 = 0.0F;
-    float m1 = 0.0F;
-    float v1 = 0.0F;
     float[] var0Init = {1.0F, 2.0F};
     float[] var1Init = {3.0F, 4.0F};
     float[] grads0Init = {0.1F, 0.1F};
@@ -96,10 +91,9 @@ public void testBasic() {
       float learningRate = 0.001F;
       float beta1 = 0.9F;
       float beta2 = 0.999F;
-      float epsilon = 1e-8F;
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -107,7 +101,7 @@ public void testBasic() {
 
       Op update = instance.applyGradients(gradsAndVars, "AdamTest");
 
-      /* Create and validae the shapes of the slota */
+      /* Create and validate the shapes of the slots */
       Variable[] firstMomentSlots = new Variable[2];
       Variable[] secondMomentSlots = new Variable[2];
 
@@ -149,13 +143,7 @@ public void testBasic() {
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
-          result
-              .data()
-              .scalars()
-              .forEach(
-                  f -> {
-                    assertEquals(powers[0], f.getFloat(), epsilon1);
-                  });
+          result.data().scalars().forEach(f -> assertEquals(powers[0], f.getFloat(), epsilon1));
         }
         try (Tensor result =
             session
@@ -165,13 +153,7 @@ public void testBasic() {
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
-          result
-              .data()
-              .scalars()
-              .forEach(
-                  f -> {
-                    assertEquals(powers[1], f.getFloat(), epsilon1);
-                  });
+          result.data().scalars().forEach(f -> assertEquals(powers[1], f.getFloat(), epsilon1));
         }
         session.run(update);
 
@@ -213,8 +195,7 @@ private FloatNdArray calculateV(FloatNdArray v, FloatNdArray gT, float beta) {
     FloatNdArray mul1 = ND.mul(v, beta);
     FloatNdArray squareG = ND.square(gT);
     FloatNdArray mul2 = ND.mul((1 - beta), squareG);
-    FloatNdArray add = ND.add(mul1, mul2);
-    return add;
+    return ND.add(mul1, mul2);
   }
 
   private FloatNdArray calculateParam(
@@ -224,7 +205,6 @@ private FloatNdArray calculateParam(
     FloatNdArray divisor = ND.add(sqrt, epsilon);
     FloatNdArray dividend = ND.mul(lrT, m);
     FloatNdArray quotient = ND.div(dividend, divisor);
-    FloatNdArray result = ND.sub(param, quotient);
-    return result;
+    return ND.sub(param, quotient);
   }
 }
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
index 9460984d124..3376d65aab4 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
@@ -28,6 +28,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -90,7 +91,6 @@ public void testBasic() {
     FloatNdArray grads0Np = NdArrays.vectorOf(grads0Init);
     FloatNdArray grads1Np = NdArrays.vectorOf(grads1Init);
 
-    float epsilon = 1e-6f;
     float epsilon1 = 1e-3F;
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
@@ -113,7 +113,7 @@ public void testBasic() {
 
       Adamax instance = new Adamax(tf);
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -135,7 +135,7 @@ public void testBasic() {
       secondMomentSlots[1] = instance.getSlot(var1.asOutput(), SECOND_MOMENT).get();
       assertEquals(secondMomentSlots[1].asOutput().shape(), var1.asOutput().shape());
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
       /* initialize the local variables */
@@ -154,13 +154,7 @@ public void testBasic() {
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
-          result
-              .data()
-              .scalars()
-              .forEach(
-                  f -> {
-                    assertEquals(beta1Power, f.getFloat(), epsilon1);
-                  });
+          result.data().scalars().forEach(f -> assertEquals(beta1Power, f.getFloat(), epsilon1));
         }
         session.run(update);
 
@@ -185,18 +179,16 @@ public void testBasic() {
   private FloatNdArray[] calculate(
       FloatNdArray varNp, FloatNdArray gradsNp, int step, FloatNdArray m, FloatNdArray v) {
     float alpha = 0.001F;
-    float beta1 = BETA_ONE_DEFAULT;
-    float beta2 = BETA_TWO_DEFAULT;
     float espilon = 1e-8F;
 
-    float oneMinusBeta1 = 1.F - beta1;
-    float oneMinusBeta1Pow = 1.F - (float) Math.pow(beta1, step + 1);
+    float oneMinusBeta1 = 1.F - BETA_ONE_DEFAULT;
+    float oneMinusBeta1Pow = 1.F - (float) Math.pow(BETA_ONE_DEFAULT, step + 1);
     float alpha1 = alpha / oneMinusBeta1Pow;
 
     // beta1 * m + (1 - beta1) * gT;
-    m = ND.add(ND.mul(beta1, m), ND.mul(oneMinusBeta1, gradsNp));
-    // np.maximum(beta2 * v, np.abs(gT))
-    v = ND.max(ND.mul(beta2, v), ND.abs(gradsNp));
+    m = ND.add(ND.mul(BETA_ONE_DEFAULT, m), ND.mul(oneMinusBeta1, gradsNp));
+    // np.maximum(BETA_TWO_DEFAULT * v, np.abs(gT))
+    v = ND.max(ND.mul(BETA_TWO_DEFAULT, v), ND.abs(gradsNp));
     // paramT = param - (alpha / (1 - beta1**(t + 1))) * (mT / (vT + epsilon))
     varNp = ND.sub(varNp, ND.mul(alpha1, ND.div(m, ND.add(v, espilon))));
 
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
index 4f1eb25246b..cda32704506 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
@@ -24,6 +24,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -32,8 +33,7 @@
 
 /** Test cases for Ftrl Optimizer */
 public class FtrlTest {
-  private TestSession.Mode tfMode = TestSession.Mode.GRAPH;
-  int index;
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
   public FtrlTest() {}
 
@@ -67,8 +67,6 @@ public void testFtrlWithL1L2L2Shrinkage() {
     float[] var1Init = {4.0F, 3.0F};
     float[] grads0Init = {0.1F, 0.2F};
     float[] grads1Init = {0.01F, 0.02F};
-    float epsilon = 1e-8F;
-    float epsilon1 = 1e-5F;
 
     int numSteps = 10;
 
@@ -100,7 +98,7 @@ public void testFtrlWithL1L2L2Shrinkage() {
               );
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -110,7 +108,7 @@ public void testFtrlWithL1L2L2Shrinkage() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
       session.evaluate(var0Init, var0);
@@ -133,8 +131,6 @@ public void testFtrlWithL1() {
     float[] var1Init = {4.0F, 3.0F};
     float[] grads0Init = {0.1F, 0.2F};
     float[] grads1Init = {0.01F, 0.02F};
-    float epsilon = 1e-8F;
-    float epsilon1 = 1e-5F;
 
     int numSteps = 10;
 
@@ -166,7 +162,7 @@ public void testFtrlWithL1() {
               );
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -176,7 +172,7 @@ public void testFtrlWithL1() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
       session.evaluate(var0Init, var0);
@@ -200,8 +196,6 @@ public void testFtrlWithL1L2() {
     float[] var1Init = {4.0F, 3.0F};
     float[] grads0Init = {0.1F, 0.2F};
     float[] grads1Init = {0.01F, 0.02F};
-    float epsilon = 1e-8F;
-    float epsilon1 = 1e-5F;
 
     int numSteps = 10;
 
@@ -233,7 +227,7 @@ public void testFtrlWithL1L2() {
               );
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -243,7 +237,7 @@ public void testFtrlWithL1L2() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
       session.evaluate(var0Init, var0);
@@ -267,8 +261,6 @@ public void doTestFtrlwithoutRegularization() {
     float[] var1Init = {0.0F, 0.0F};
     float[] grads0Init = {0.1F, 0.2F};
     float[] grads1Init = {0.01F, 0.02F};
-    float epsilon = 1e-8F;
-    float epsilon1 = 1e-5F;
 
     int numSteps = 3;
 
@@ -291,7 +283,7 @@ public void doTestFtrlwithoutRegularization() {
       Ftrl instance = new Ftrl(tf, learningRate);
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
       Op ftrlUpdate = instance.applyGradients(gradsAndVars, "FtrlTest");
@@ -300,7 +292,7 @@ public void doTestFtrlwithoutRegularization() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
       session.evaluate(var0Init, var0);
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
index 3eab6288268..d720460b2f2 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
@@ -28,6 +28,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -95,7 +96,6 @@ public void testBasic() {
     FloatNdArray grads0Np = NdArrays.vectorOf(grads0Init);
     FloatNdArray grads1Np = NdArrays.vectorOf(grads1Init);
 
-    float epsilon = 1e-6f;
     float epsilon1 = 1e-3F;
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
@@ -114,7 +114,7 @@ public void testBasic() {
 
       Nadam instance = new Nadam(tf);
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -140,7 +140,7 @@ public void testBasic() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
       session.setEpsilon(epsilon1);
@@ -156,13 +156,7 @@ public void testBasic() {
               .run()
               .get(0)
               .expect(TFloat32.DTYPE)) {
-        result
-            .data()
-            .scalars()
-            .forEach(
-                f -> {
-                  assertEquals(1F, f.getFloat(), epsilon1);
-                });
+        result.data().scalars().forEach(f -> assertEquals(1F, f.getFloat(), epsilon1));
       }
       momentum = 1F;
 
@@ -182,13 +176,7 @@ public void testBasic() {
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
-          result
-              .data()
-              .scalars()
-              .forEach(
-                  f -> {
-                    assertEquals(momentum, f.getFloat(), epsilon1);
-                  });
+          result.data().scalars().forEach(f -> assertEquals(momentum, f.getFloat(), epsilon1));
         }
         mcache = ND.mul(mcache, momentum);
         FloatNdArray[] resultsNP = nadamUpdateNdArray(var0Np, grads0Np, step, m0, v0, mcache);
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
index cabf869536c..078288ed1e7 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
@@ -27,6 +27,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -40,7 +41,7 @@ public class RMSPropTest {
   final int RMS_T = 2;
   final int MOM_T = 3;
   private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
-  int index;
+
   Object[][] TestParamValues = {
     // learningRate, rho (decay), momentum, epsilon, centered
     {0.05F, 0.9F, 0.0F, 1e-3F, true},
@@ -69,7 +70,7 @@ public void testDense() {
 
     int numSteps = 3;
 
-    for (int run = 0; run < TestParamValues.length; run++) {
+    for (Object[] testParamValue : TestParamValues) {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         session.setEpsilon(1e-2f);
@@ -77,7 +78,6 @@ public void testDense() {
         float[] var1Init = {3.0F, 4.0F};
         float[] grads0Init = {0.1F, 0.2F};
         float[] grads1Init = {0.01F, 0.2F};
-        final float epsilon1 = 1e-2F;
 
         FloatNdArray var0Np = NdArrays.vectorOf(var0Init);
         FloatNdArray var1Np = NdArrays.vectorOf(var1Init);
@@ -96,18 +96,18 @@ public void testDense() {
         Constant grads1 = tf.constant(grads1Init);
 
         // learningRate, rho (decay), momentum, epsilon, centered
-        float learningRate = (float) (float) TestParamValues[run][0];
-        float decay = (float) TestParamValues[run][1];
-        float momentum = (float) TestParamValues[run][2];
-        float epsilon = (float) TestParamValues[run][3];
-        boolean centered = (boolean) TestParamValues[run][4];
+        float learningRate = (float) (float) testParamValue[0];
+        float decay = (float) testParamValue[1];
+        float momentum = (float) testParamValue[2];
+        float epsilon = (float) testParamValue[3];
+        boolean centered = (boolean) testParamValue[4];
 
         RMSProp instance = new RMSProp(tf, learningRate, decay, momentum, epsilon, centered);
 
         /* build the GradsAnvVars */
-        List gradsAndVars = new ArrayList<>();
-        gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
-        gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
+        List> gradsAndVars = new ArrayList<>();
+        gradsAndVars.add(new GradAndVar<>(grads0.asOutput(), var0.asOutput()));
+        gradsAndVars.add(new GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
         Op update = instance.applyGradients(gradsAndVars, "RMSPropTest");
 
@@ -115,10 +115,10 @@ public void testDense() {
         session.run(var0Initializer);
         session.run(var1Initializer);
 
-        /** initialize the accumulators */
+        /* initialize the accumulators */
         session.run(tf.init());
 
-        /** make sure the variables were initialized properly */
+        /* make sure the variables were initialized properly */
         session.evaluate(var0Init, var0);
         session.evaluate(var1Init, var1);
 
@@ -179,13 +179,12 @@ public void testDense() {
 
           if (centered) {
             session.evaluate(mg0Np, mg0);
-            session.evaluate(mg0Np, mg0);
-          }
-          if (momentum > 0.F) {
-            session.evaluate(mom0Np, mom0);
-            session.evaluate(mom1Np, mom1);
+            session.evaluate(mg1Np, mg1);
           }
 
+          if (mom0 != null) session.evaluate(mom0Np, mom0);
+          if (mom1 != null) session.evaluate(mom1Np, mom1);
+
           /*     TODO the values returned from rms slot, do not match what I see in the python test */
           session.evaluate(rms0Np, rms0);
           session.evaluate(rms1Np, rms1);
@@ -240,8 +239,7 @@ private FloatNdArray calcRMS(FloatNdArray rmsNp, FloatNdArray gradNp, float deca
     FloatNdArray squareG = ND.square(gradNp);
     float oneRHO = 1.0F - decay;
     FloatNdArray decayG2 = ND.mul(oneRHO, squareG);
-    FloatNdArray result = ND.add(rmsRho, decayG2);
-    return result;
+    return ND.add(rmsRho, decayG2);
   }
 
   private FloatNdArray calcMG(FloatNdArray mgNp, FloatNdArray gradNp, float decay) {
@@ -249,8 +247,7 @@ private FloatNdArray calcMG(FloatNdArray mgNp, FloatNdArray gradNp, float decay)
     FloatNdArray mgRho = ND.mul(mgNp, decay);
     float oneRHO = 1.0F - decay;
     FloatNdArray decayG = ND.mul(oneRHO, gradNp);
-    FloatNdArray result = ND.add(mgRho, decayG);
-    return result;
+    return ND.add(mgRho, decayG);
   }
 
   private FloatNdArray calcMom(
@@ -265,8 +262,7 @@ private FloatNdArray calcMom(
     FloatNdArray dividend = ND.mul(lr, gradNp);
     FloatNdArray divisor = ND.sqrt(ND.add(denomT, epsilon));
     FloatNdArray quotient = ND.div(dividend, divisor);
-    FloatNdArray result = ND.add(moMo, quotient);
-    return result;
+    return ND.add(moMo, quotient);
   }
 
   private FloatNdArray calcVar(
@@ -275,7 +271,6 @@ private FloatNdArray calcVar(
     FloatNdArray dividend = ND.mul(lr, gradNp);
     FloatNdArray divisor = ND.add(ND.sqrt(denomT), epsilon);
     FloatNdArray quotient = ND.div(dividend, divisor);
-    FloatNdArray result = ND.sub(varNp, quotient);
-    return result;
+    return ND.sub(varNp, quotient);
   }
 }
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
index b36851a561e..a8e363b4332 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
+++ b/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
@@ -24,6 +24,7 @@
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -70,9 +71,6 @@ public void testBasic() {
     float[] grads1Init = {0.01F, 0.01F};
     float learningRate = 3.0F;
 
-    float epsilon = 1e-6F;
-    float epsilon1 = 1e-2F;
-
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
@@ -88,7 +86,7 @@ public void testBasic() {
       Constant grads1 = tf.constant(grads1Init);
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -99,10 +97,10 @@ public void testBasic() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
-      /** make sure the variables were initialized properly */
+      /* make sure the variables were initialized properly */
       session.evaluate(var0Init, var0);
       session.evaluate(var1Init, var1);
 
@@ -125,9 +123,6 @@ public void testMomentum() {
     float learningRate = 2.0F;
     float momentum = 0.9F;
 
-    float epsilon = 1e-6F;
-    float epsilon1 = 1e-2F;
-
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
 
@@ -143,7 +138,7 @@ public void testMomentum() {
       Constant grads1 = tf.constant(grads1Init);
 
       /* build the GradsAnvVars */
-      List gradsAndVars = new ArrayList<>();
+      List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
@@ -159,10 +154,10 @@ public void testMomentum() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      /** initialize the accumulators */
+      /* initialize the accumulators */
       session.run(tf.init());
 
-      /** make sure the variables were initialized properly */
+      /* make sure the variables were initialized properly */
       session.evaluate(var0Init, var0);
       session.evaluate(var1Init, var1);
 

From e9c3134742e9155e457be157515d67b5c0bb7ac4 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Wed, 9 Sep 2020 16:14:20 -0400
Subject: [PATCH 29/33] Added Adamax, Ftrl, and Nadam Optimizers. Added
 Optimizers enum for easy inclusion of a default optimizer. Cleaned up JavaDoc

---
 .../framework/optimizers/AdaDelta.java        | 113 ++++++-
 .../framework/optimizers/AdaGrad.java         |  97 +++++-
 .../framework/optimizers/AdaGradDA.java       | 174 ++++++++--
 .../tensorflow/framework/optimizers/Adam.java | 153 +++++++--
 .../framework/optimizers/Adamax.java          | 190 +++++++++++
 .../framework}/optimizers/Ftrl.java           | 219 ++++---------
 .../framework/optimizers/GradientDescent.java |  38 ++-
 .../framework/optimizers/Momentum.java        | 106 ++++--
 .../framework/optimizers/Nadam.java           | 302 ++++++++++++++++++
 .../framework/optimizers/Optimizer.java       | 164 ++++++----
 .../framework/optimizers/Optimizers.java      |  41 +++
 .../framework/optimizers/RMSProp.java         | 164 ++++++++--
 12 files changed, 1420 insertions(+), 341 deletions(-)
 create mode 100644 tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java
 rename {tensorflow-keras/src/main/java/org/tensorflow/keras => tensorflow-framework/src/main/java/org/tensorflow/framework}/optimizers/Ftrl.java (55%)
 create mode 100644 tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java
 create mode 100644 tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java

diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java
index b5dc2434d60..1bdeffe4dcb 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.optimizers;
 
-import java.util.List;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
@@ -23,15 +22,51 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.family.TType;
 
+import java.util.List;
+
 /**
  * Optimizer that implements the Adadelta algorithm.
- * 

- * See the paper.
+ *
+ * 
Adadelta optimization is a stochastic gradient descent method that is based on adaptive
+ * learning rate per dimension to address two drawbacks:
+ *
+ * 

+ * 
  • the continual decay of learning rates throughout training
+ * 
  • the need for a manually selected global learning rate 
+ *
+ *     
    
+ *
+ *     
    Adadelta is a more robust extension of Adagrad that adapts learning rates based on a
+ *     moving window of gradient updates, instead of accumulating all past gradients. This way,
+ *     Adadelta continues learning even when many updates have been done. Compared to Adagrad, in
+ *     the original version of Adadelta you don't have to set an initial learning rate. In this
+ *     version, initial learning rate can be set, as in most other optimizers.
+ *
+ *     
    
+ *
+ *     
    According to section 4.3 ("Effective Learning rates"), near the end of training step sizes
+ *     converge to 1 which is effectively a high learning rate which would cause divergence. This
+ *     occurs only near the end of the training as gradients and step sizes are small, and the
+ *     epsilon constant in the numerator and denominator dominate past gradients and parameter
+ *     updates which converge the learning rate to 1.
+ *
+ *     
    
+ *
+ *     
    According to section 4.4("Speech Data"),where a large neural network with 4 hidden layers
+ *     was trained on a corpus of US English data, ADADELTA was used with 100 network replicas.The
+ *     epsilon used is 1e-6 with rho=0.95 which converged faster than ADAGRAD, by the following
+ *     construction:  new AdaDelta(graph, 1.0f, 0.95f, 1e-6f); 
+ *
+ * @see Zeiler, M., 2012 ADADELTA: An Adaptive Learning
+ *     Rate Method.
  */
 public class AdaDelta extends Optimizer {
 
   public static final String ACCUMULATOR = "accum";
   public static final String ACCUMULATOR_UPDATE = "accum_update";
+  public static final float LEARNING_RATE_DEFAULT = 0.001f;
+  public static final float RHO_DEFAULT = 0.95f;
+  public static final float EPSILON_DEFAULT = 1e-7f;
 
   private final float learningRate;
 
@@ -39,10 +74,28 @@ public class AdaDelta extends Optimizer {
 
   private final float epsilon;
 
+  public AdaDelta(Graph graph) {
+    this(graph, LEARNING_RATE_DEFAULT, RHO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates an AdaDelta Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   */
   public AdaDelta(Graph graph, float learningRate) {
-    this(graph, learningRate, 0.95f, 1e-8f);
+    this(graph, learningRate, RHO_DEFAULT, EPSILON_DEFAULT);
   }
 
+  /**
+   * Creates an AdaDelta Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   * @param rho The decay factor
+   * @param epsilon A constant epsilon used to better conditioning the grad update
+   */
   public AdaDelta(Graph graph, float learningRate, float rho, float epsilon) {
     super(graph);
     this.learningRate = learningRate;
@@ -50,10 +103,26 @@ public AdaDelta(Graph graph, float learningRate, float rho, float epsilon) {
     this.epsilon = epsilon;
   }
 
+  /**
+   * Creates an AdaDelta Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name for this Optimizer (defaults to 'Adadelta')
+   * @param learningRate the learning rate
+   */
   public AdaDelta(Graph graph, String name, float learningRate) {
     this(graph, name, learningRate, 0.95f, 1e-8f);
   }
 
+  /**
+   * Creates an AdaDelta Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name for this Optimizer (defaults to 'Adadelta')
+   * @param learningRate the learning rate
+   * @param rho The decay factor
+   * @param epsilon A constant epsilon used to better conditioning the grad update
+   */
   public AdaDelta(Graph graph, String name, float learningRate, float rho, float epsilon) {
     super(graph, name);
     this.learningRate = learningRate;
@@ -61,6 +130,7 @@ public AdaDelta(Graph graph, String name, float learningRate, float rho, float e
     this.epsilon = epsilon;
   }
 
+  /** {@inheritDoc} */
   @Override
   protected void createSlots(List> variables) {
     for (Output v : variables) {
@@ -68,35 +138,50 @@ protected void createSlots(List> variables) {
     }
   }
 
+  /**
+   * Creates an AdaDelta Slot
+   *
+   * @param v the variable to install in the slot
+   * @param  the datatype of the variable.
+   */
   private  void createAdaDeltaSlot(Output v) {
-    Operand accumulatorInitializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand accumulatorInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
     createSlot(v.asOutput(), ACCUMULATOR, accumulatorInitializer);
-    Operand updateInitializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand updateInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
     createSlot(v.asOutput(), ACCUMULATOR_UPDATE, updateInitializer);
   }
 
+  /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
     Variable accumSlot = getSlot(variable, ACCUMULATOR).get();
     Variable accumUpdateSlot = getSlot(variable, ACCUMULATOR_UPDATE).get();
-    return tf.train.applyAdadelta(variable, accumSlot, accumUpdateSlot,
+    return tf.train.applyAdadelta(
+        variable,
+        accumSlot,
+        accumUpdateSlot,
         tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
         tf.dtypes.cast(tf.constant(rho), gradient.dataType()),
         tf.dtypes.cast(tf.constant(epsilon), gradient.dataType()),
         gradient);
   }
 
+  /** {@inheritDoc} */
   @Override
   public String toString() {
-    return "AdaDelta{" +
-        "learningRate=" + learningRate +
-        ", rho=" + rho +
-        ", epsilon=" + epsilon +
-        '}';
+    return "AdaDelta{"
+        + "learningRate="
+        + learningRate
+        + ", rho="
+        + rho
+        + ", epsilon="
+        + epsilon
+        + '}';
   }
 
+  /** {@inheritDoc} */
   @Override
   public String getOptimizerName() {
     return "Adadelta";
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java
index 4dfabb21357..6855be30759 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.optimizers;
 
-import java.util.List;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
@@ -23,40 +22,102 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.family.TType;
 
+import java.util.List;
+
 /**
  * Optimizer that implements the Adagrad algorithm.
+ *
+ * 
    Adagrad is an optimizer with parameter-specific learning rates, which are adapted relative to
+ * how frequently a parameter gets updated during training. The more updates a parameter receives,
+ * the smaller the updates.
+ *
  * 
    
- * See the paper or this intro.
+ *
+ * @see Duchi, J, et al., 2011,
+ *     Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
+ * @see Duchi, J, et al.,
+ *     2013, Proximal and First-Order Methods for Convex Optimization, Introduction Section 1.
  */
 public class AdaGrad extends Optimizer {
 
   public static final String ACCUMULATOR = "accumulator";
+  public static final float LEARNING_RATE_DEFAULT = 0.001f;
+  public static final float INITIAL_ACCUMULATOR_DEFAULT = 0.01f;
 
   private final float learningRate;
 
   private final float initialAccumulatorValue;
 
+  /**
+   * Creates an AdaGrad Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   */
+  public AdaGrad(Graph graph) {
+    this(graph, LEARNING_RATE_DEFAULT, INITIAL_ACCUMULATOR_DEFAULT);
+  }
+
+  /**
+   * Creates an AdaGrad Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   */
   public AdaGrad(Graph graph, float learningRate) {
-    this(graph, learningRate, 0.01f);
+    this(graph, learningRate, INITIAL_ACCUMULATOR_DEFAULT);
   }
 
+  /**
+   * Creates an AdaGrad Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   * @param initialAccumulatorValue Starting value for the accumulators, must be non-negative.
+   * @throws java.lang.IllegalArgumentException if initialAccumulatorValue is negative
+   */
   public AdaGrad(Graph graph, float learningRate, float initialAccumulatorValue) {
     super(graph);
+    if (initialAccumulatorValue < 0F) {
+      throw new IllegalArgumentException(
+          String.format(
+              "initialAccumulatorValue must be non-negative: %f", initialAccumulatorValue));
+    }
     this.learningRate = learningRate;
     this.initialAccumulatorValue = initialAccumulatorValue;
   }
 
+  /**
+   * Creates an AdaGrad Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name for this Optimizer (defaults to 'Adagrad')
+   * @param learningRate the learning rate
+   */
   public AdaGrad(Graph graph, String name, float learningRate) {
     this(graph, name, learningRate, 0.01f);
   }
 
+  /**
+   * Creates an AdaGrad Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name for this Optimizer (defaults to 'Adagrad')
+   * @param learningRate the learning rate
+   * @param initialAccumulatorValue Starting value for the accumulators, must be non-negative.
+   * @throws java.lang.IllegalArgumentException if initialAccumulatorValue is negative
+   */
   public AdaGrad(Graph graph, String name, float learningRate, float initialAccumulatorValue) {
     super(graph, name);
+    if (initialAccumulatorValue < 0F) {
+      throw new IllegalArgumentException(
+          String.format(
+              "initialAccumulatorValue must be non-negative: %f", initialAccumulatorValue));
+    }
     this.learningRate = learningRate;
     this.initialAccumulatorValue = initialAccumulatorValue;
   }
 
+  /** {@inheritDoc} */
   @Override
   protected void createSlots(List> variables) {
     for (Output v : variables) {
@@ -64,28 +125,38 @@ protected void createSlots(List> variables) {
     }
   }
 
+  /**
+   * Creates an AdaGrad Slot
+   *
+   * @param v the variable to install in the slot
+   * @param  the datatype of the variable.
+   */
   private  void createAdaGradSlot(Output v) {
-    Operand initializer = tf.fill(tf.shape(v),
-        tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType()));
+    Operand initializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType()));
     createSlot(v.asOutput(), ACCUMULATOR, initializer);
   }
 
+  /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
     Variable slot = getSlot(variable, ACCUMULATOR).get();
-    return tf.train
-        .applyAdagrad(variable, slot, tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
-            gradient);
+    return tf.train.applyAdagrad(
+        variable, slot, tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), gradient);
   }
 
+  /** {@inheritDoc} */
   @Override
   public String toString() {
-    return "AdaGrad{" +
-        "learningRate=" + learningRate +
-        ", initialAccumulatorValue=" + initialAccumulatorValue +
-        '}';
+    return "AdaGrad{"
+        + "learningRate="
+        + learningRate
+        + ", initialAccumulatorValue="
+        + initialAccumulatorValue
+        + '}';
   }
 
+  /** {@inheritDoc} */
   @Override
   public String getOptimizerName() {
     return "Adagrad";
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java
index 0544309dc7f..e74a1d85359 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java
@@ -15,64 +15,175 @@
  */
 package org.tensorflow.framework.optimizers;
 
-import java.util.List;
-import java.util.Optional;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.core.Assign;
 import org.tensorflow.op.core.Variable;
-import org.tensorflow.ndarray.Shape;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
 
+import java.util.List;
+import java.util.Optional;
+
 /**
  * Optimizer that implements the Adagrad Dual-Averaging algorithm.
+ *
+ * 
    This optimizer takes care of regularization of unseen features in a mini batch by updating
+ * them when they are seen with a closed form update rule that is equivalent to having updated them
+ * on every mini-batch.
+ *
+ * 
    AdagradDA is typically used when there is a need for large sparsity in the trained model. This
+ * optimizer only guarantees sparsity for linear models. Be careful when using AdagradDA for deep
+ * networks as it will require careful initialization of the gradient accumulators for it to train.
+ *
  * 
    
- * See the paper.
+ *
+ * @see Duchi, J, et al., 2011,
+ *     Adaptive Subgradient Methods for Online Learning and Stochastic Optimization.
  */
 public class AdaGradDA extends Optimizer {
 
   public static final String ACCUMULATOR = "gradient_accumulator";
   public static final String SQUARED_ACCUMULATOR = "gradient_squared_accumulator";
+  public static final float LEARNING_RATE_DEFAULT = 0.001F;
+  public static final float INITIAL_ACCUMULATOR_DEFAULT = 0.1f;
+  public static final float L1_STRENGTH_DEFAULT = 0.0F;
+  public static final float L2_STRENGTH_DEFAULT = 0.0F;
+
   private final float learningRate;
   private final float initialAccumulatorValue;
   private final float l1Strength;
   private final float l2Strength;
   private Variable globalStep;
 
+  /**
+   * Creates an AdaGradDA Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   */
+  public AdaGradDA(Graph graph) {
+    this(
+        graph,
+        LEARNING_RATE_DEFAULT,
+        INITIAL_ACCUMULATOR_DEFAULT,
+        L1_STRENGTH_DEFAULT,
+        L2_STRENGTH_DEFAULT);
+  }
+
+  /**
+   * Creates an AdaGradDA Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   */
   public AdaGradDA(Graph graph, float learningRate) {
-    this(graph, learningRate, 0.1f, 0.0f, 0.0f);
+    this(
+        graph, learningRate, INITIAL_ACCUMULATOR_DEFAULT, L1_STRENGTH_DEFAULT, L2_STRENGTH_DEFAULT);
   }
 
-  public AdaGradDA(Graph graph, float learningRate, float initialAccumulatorValue, float l1Strength,
+  /**
+   * Creates an AdaGradDA Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   * @param initialAccumulatorValue Starting value for the accumulators, must be greater than zero.
+   * @param l1Strength l1 regularization strength, must be greater than or equal to zero.
+   * @param l2Strength l2 regularization strength, must be greater than or equal to zero.
+   * @throws java.lang.IllegalArgumentException if initialAccumulatorValue is not greater than zero,
+   *     or l1Strength or l2Strength is less than zero
+   */
+  public AdaGradDA(
+      Graph graph,
+      float learningRate,
+      float initialAccumulatorValue,
+      float l1Strength,
       float l2Strength) {
     super(graph);
+    if (initialAccumulatorValue <= 0F) {
+      throw new IllegalArgumentException(
+          String.format(
+              "initialAccumulatorValue must be greater than zero: %f", initialAccumulatorValue));
+    }
+    if (l1Strength < 0F) {
+      throw new IllegalArgumentException(
+          String.format("l1Strength must not be negative: %f", l1Strength));
+    }
+    if (l2Strength < 0F) {
+      throw new IllegalArgumentException(
+          String.format("l2Strength must not be negative: %f", l2Strength));
+    }
     this.learningRate = learningRate;
     this.initialAccumulatorValue = initialAccumulatorValue;
     this.l1Strength = l1Strength;
     this.l2Strength = l2Strength;
   }
 
+  /**
+   * Creates an AdaGradDA Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name for this Optimizer (defaults to 'adagrad-da')
+   * @param learningRate the learning rate
+   */
   public AdaGradDA(Graph graph, String name, float learningRate) {
-    this(graph, name, learningRate, 0.1f, 0.0f, 0.0f);
+    this(
+        graph,
+        name,
+        learningRate,
+        INITIAL_ACCUMULATOR_DEFAULT,
+        L1_STRENGTH_DEFAULT,
+        L2_STRENGTH_DEFAULT);
   }
 
-  public AdaGradDA(Graph graph, String name, float learningRate, float initialAccumulatorValue, float l1Strength,
+  /**
+   * Creates an AdaGradDA Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name for this Optimizer (defaults to 'adagrad-da')
+   * @param learningRate the learning rate
+   * @param initialAccumulatorValue Starting value for the accumulators, must be positive
+   * @param l1Strength l1 regularization strength, must be greater than or equal to zero.
+   * @param l2Strength l2 regularization strength, must be greater than or equal to zero.
+   * @throws java.lang.IllegalArgumentException if initialAccumulatorValue is not greater than zero,
+   *     or * l1Strength or l2Strength is less than zero
+   */
+  public AdaGradDA(
+      Graph graph,
+      String name,
+      float learningRate,
+      float initialAccumulatorValue,
+      float l1Strength,
       float l2Strength) {
     super(graph, name);
+    if (initialAccumulatorValue <= 0F) {
+      throw new IllegalArgumentException(
+          String.format(
+              "initialAccumulatorValue must be greater than zero: %f", initialAccumulatorValue));
+    }
+    if (l1Strength < 0F) {
+      throw new IllegalArgumentException(
+          String.format("l1Strength must not be negative: %f", l1Strength));
+    }
+    if (l2Strength < 0F) {
+      throw new IllegalArgumentException(
+          String.format("l2Strength must not be negative: %f", l2Strength));
+    }
     this.learningRate = learningRate;
     this.initialAccumulatorValue = initialAccumulatorValue;
     this.l1Strength = l1Strength;
     this.l2Strength = l2Strength;
   }
 
+  /** {@inheritDoc} */
   @Override
   protected Optional prepare(String name) {
     return Optional.of(tf.assignAdd(globalStep, tf.constant(1L)));
   }
 
+  /** {@inheritDoc} */
   @Override
   protected void createSlots(List> variables) {
     for (Output v : variables) {
@@ -83,20 +194,30 @@ protected void createSlots(List> variables) {
     graph.addInitializer(globalStepInitializer);
   }
 
+  /**
+   * Creates an AdaGradDA Slot
+   *
+   * @param v the variable to install in the slot
+   * @param  the datatype of the variable.
+   */
   private  void createAdaGradDASlot(Output v) {
-    Operand initializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand initializer = tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
     createSlot(v.asOutput(), ACCUMULATOR, initializer);
-    Operand sqInitializer = tf.fill(tf.shape(v),
-        tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType()));
+    Operand sqInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType()));
     createSlot(v.asOutput(), SQUARED_ACCUMULATOR, sqInitializer);
   }
 
+  /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
     Variable gradSlot = getSlot(variable, ACCUMULATOR).get();
     Variable gradSquaredSlot = getSlot(variable, SQUARED_ACCUMULATOR).get();
-    return tf.train.applyAdagradDa(variable, gradSlot, gradSquaredSlot, gradient,
+    return tf.train.applyAdagradDa(
+        variable,
+        gradSlot,
+        gradSquaredSlot,
+        gradient,
         tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
         tf.dtypes.cast(tf.constant(l1Strength), gradient.dataType()),
         tf.dtypes.cast(tf.constant(l2Strength), gradient.dataType()),
@@ -105,11 +226,11 @@ protected  Op applyDense(Output gradient, Output variable
 
   /**
    * Gathers up the update operations into a single op that can be used as a run target.
-   * 
    
-   * Adds the global step update to the end of the updates list.
+   *
+   * 
    Adds the global step update to the end of the updates list.
    *
    * @param updateOperations The update operations.
-   * @param name             The name of the run target.
+   * @param name The name of the run target.
    * @return A NoOp with a control dependency on each update operation.
    */
   @Override
@@ -118,17 +239,24 @@ protected Op finish(List updateOperations, String name) {
     return super.finish(updateOperations, name);
   }
 
+  /** {@inheritDoc} */
   @Override
   public String toString() {
-    return "AdaGradDA{" +
-        "globalStep=" + globalStep +
-        ", learningRate=" + learningRate +
-        ", initialAccumulatorValue=" + initialAccumulatorValue +
-        ", l1Strength=" + l1Strength +
-        ", l2Strength=" + l2Strength +
-        '}';
+    return "AdaGradDA{"
+        + "globalStep="
+        + globalStep
+        + ", learningRate="
+        + learningRate
+        + ", initialAccumulatorValue="
+        + initialAccumulatorValue
+        + ", l1Strength="
+        + l1Strength
+        + ", l2Strength="
+        + l2Strength
+        + '}';
   }
 
+  /** {@inheritDoc} */
   @Override
   public String getOptimizerName() {
     return "adagrad-da";
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java
index 11ab4be6b64..8f620678781 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java
@@ -15,11 +15,10 @@
  */
 package org.tensorflow.framework.optimizers;
 
-import java.util.List;
-import java.util.Optional;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -27,14 +26,24 @@
 import org.tensorflow.op.core.Assign;
 import org.tensorflow.op.core.Constant;
 import org.tensorflow.op.core.Variable;
-import org.tensorflow.ndarray.Shape;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TType;
 
+import java.util.List;
+import java.util.Optional;
+
 /**
  * Optimizer that implements the Adam algorithm.
- * 
    
- * See the paper.
+ *
+ * 
    Adam optimization is a stochastic gradient descent method that is based on adaptive estimation
+ * of first-order and second-order moments.
+ *
+ * 
    According to Kingma et al., 2014, the method is "computationally efficient, has little memory
+ * requirement, invariant to diagonal rescaling of gradients, and is well suited for problems that
+ * are large in terms of data/parameters".
+ *
+ * 
    @see Kingma et al., 2014, Adam: A Method for
+ * Stochastic Optimization.
  */
 @Operator
 public class Adam extends Optimizer {
@@ -42,6 +51,11 @@ public class Adam extends Optimizer {
   public static final String FIRST_MOMENT = "m";
   public static final String SECOND_MOMENT = "v";
 
+  public static final float LEARNING_RATE_DEFAULT = 0.001f;
+  public static final float EPSILON_DEFAULT = 1e-8f;
+  public static final float BETA_ONE_DEFAULT = 0.9f;
+  public static final float BETA_TWO_DEFAULT = 0.999f;
+
   private final float learningRate;
 
   private final float betaOne;
@@ -57,10 +71,36 @@ public class Adam extends Optimizer {
   private Variable betaOnePower;
   private Variable betaTwoPower;
 
+  /**
+   * Creates an Adam optimizer
+   *
+   * @param graph the TensorFlow graph
+   */
+  public Adam(Graph graph) {
+    this(graph, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates an Adam optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate
+   */
   public Adam(Graph graph, float learningRate) {
-    this(graph, learningRate, 0.9f, 0.999f, 1e-8f);
+    this(graph, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
   }
 
+  /**
+   * Creates an Adam optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate
+   * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9.
+   * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999.
+   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
+   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
+   *     1 of the paper. Defaults to 1e-8.
+   */
   public Adam(Graph graph, float learningRate, float betaOne, float betaTwo, float epsilon) {
     super(graph);
     this.learningRate = learningRate;
@@ -69,11 +109,31 @@ public Adam(Graph graph, float learningRate, float betaOne, float betaTwo, float
     this.epsilon = epsilon;
   }
 
+  /**
+   * Creates an Adam optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param name the Optimizer name, defaults to "Adam"
+   * @param learningRate the learning rate
+   */
   public Adam(Graph graph, String name, float learningRate) {
-    this(graph, name, learningRate, 0.9f, 0.999f, 1e-8f);
+    this(graph, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
   }
 
-  public Adam(Graph graph, String name, float learningRate, float betaOne, float betaTwo, float epsilon) {
+  /**
+   * Creates an Adam optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param name the Optimizer name, defaults to "Adam"
+   * @param learningRate the learning rate
+   * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9.
+   * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999.
+   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
+   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
+   *     1 of the paper. Defaults to 1e-8.
+   */
+  public Adam(
+      Graph graph, String name, float learningRate, float betaOne, float betaTwo, float epsilon) {
     super(graph, name);
     this.learningRate = learningRate;
     this.betaOne = betaOne;
@@ -81,9 +141,30 @@ public Adam(Graph graph, String name, float learningRate, float betaOne, float b
     this.epsilon = epsilon;
   }
 
+  /**
+   * Creates the Operation that minimizes the loss
+   *
+   * @param scope the TensorFlow scope
+   * @param loss the loss to minimize
+   * @param learningRate the learning rate
+   * @param betaOne The exponential decay rate for the 1st moment estimates.
+   * @param betaTwo The exponential decay rate for the 2nd moment estimates.
+   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
+   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
+   *     1 of the paper.
+   * @param options Optional Optimizer attributes
+   * @param  the data type for the loss
+   * @return the Operation that minimizes the loss
+   * @throws java.lang.IllegalArgumentException if scope does not represent a Graph
+   */
   @Endpoint(name = "adam_minimize")
-  public static  Op createAdamMinimize(Scope scope, Operand loss,
-      float learningRate, float betaOne, float betaTwo, float epsilon,
+  public static  Op createAdamMinimize(
+      Scope scope,
+      Operand loss,
+      float learningRate,
+      float betaOne,
+      float betaTwo,
+      float epsilon,
       Optimizer.Options... options) {
     if (!(scope.env() instanceof Graph)) {
       throw new IllegalArgumentException("Optimizers are only supported on Graphs");
@@ -102,21 +183,21 @@ public static  Op createAdamMinimize(Scope scope, Operand lo
     }
   }
 
+  /** {@inheritDoc} */
   @Override
   protected void createSlots(List> variables) {
     for (Output v : variables) {
       createAdamSlot(v.asOutput());
     }
     betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
-    Assign betaOnePowerInit = tf
-        .assign(betaOnePower, tf.constant(betaOne));
+    Assign betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
     graph.addInitializer(betaOnePowerInit);
     betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.DTYPE);
-    Assign betaTwoPowerInit = tf
-        .assign(betaTwoPower, tf.constant(betaTwo));
+    Assign betaTwoPowerInit = tf.assign(betaTwoPower, tf.constant(betaTwo));
     graph.addInitializer(betaTwoPowerInit);
   }
 
+  /** {@inheritDoc} */
   @Override
   protected Optional prepare(String scopeName) {
     betaOneConst = tf.constant(betaOne);
@@ -126,20 +207,30 @@ protected Optional prepare(String scopeName) {
     return Optional.empty();
   }
 
+  /**
+   * Creates an Adam Slot
+   *
+   * @param v the variable to install in the slot
+   * @param  the datatype of the variable.
+   */
   private  void createAdamSlot(Output v) {
-    Operand firstMomentInitializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand firstMomentInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
     createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
-    Operand secondMomentInitializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand secondMomentInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
     createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
   }
 
+  /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
     Variable firstMomentSlot = getSlot(variable, FIRST_MOMENT).get();
     Variable secondMomentSlot = getSlot(variable, SECOND_MOMENT).get();
-    return tf.train.applyAdam(variable, firstMomentSlot, secondMomentSlot,
+    return tf.train.applyAdam(
+        variable,
+        firstMomentSlot,
+        secondMomentSlot,
         tf.dtypes.cast(betaOnePower, gradient.dataType()),
         tf.dtypes.cast(betaTwoPower, gradient.dataType()),
         tf.dtypes.cast(learningRateConst, gradient.dataType()),
@@ -151,11 +242,11 @@ protected  Op applyDense(Output gradient, Output variable
 
   /**
    * Gathers up the update operations into a single op that can be used as a run target.
-   * 
    
-   * Adds the betaOne and betaTwo updates to the end of the updates list.
+   *
+   * 
    Adds the betaOne and betaTwo updates to the end of the updates list.
    *
    * @param updateOperations The update operations.
-   * @param name             The name of the run target.
+   * @param name The name of the run target.
    * @return A NoOp with a control dependency on each update operation.
    */
   @Override
@@ -165,16 +256,22 @@ protected Op finish(List updateOperations, String name) {
     return super.finish(updateOperations, name);
   }
 
+  /** {@inheritDoc} */
   @Override
   public String toString() {
-    return "Adam{" +
-        "learningRate=" + learningRate +
-        ", betaOne=" + betaOne +
-        ", betaTwo=" + betaTwo +
-        ", epsilon=" + epsilon +
-        '}';
+    return "Adam{"
+        + "learningRate="
+        + learningRate
+        + ", betaOne="
+        + betaOne
+        + ", betaTwo="
+        + betaTwo
+        + ", epsilon="
+        + epsilon
+        + '}';
   }
 
+  /** {@inheritDoc} */
   @Override
   public String getOptimizerName() {
     return "Adam";
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java
new file mode 100644
index 00000000000..335d83cedfa
--- /dev/null
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java
@@ -0,0 +1,190 @@
+package org.tensorflow.framework.optimizers;
+
+import org.tensorflow.Graph;
+import org.tensorflow.Operand;
+import org.tensorflow.Output;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Op;
+import org.tensorflow.op.core.Assign;
+import org.tensorflow.op.core.Constant;
+import org.tensorflow.op.core.Variable;
+import org.tensorflow.op.train.ApplyAdaMax;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
+
+import java.util.List;
+import java.util.Optional;
+
+/**
+ * Optimizer that implements the Adamax algorithm.
+ *
+ * 
    It is a variant of Adam based on the infinity norm. Default parameters follow those provided
+ * in the paper. Adamax is sometimes superior to adam, specially in models with embeddings.
+ *
+ * @see Kingma et al., 2014
+ */
+public class Adamax extends Optimizer {
+
+  public static final String FIRST_MOMENT = "m";
+  public static final String SECOND_MOMENT = "v";
+
+  public static final float LEARNING_RATE_DEFAULT = 0.001f;
+  public static final float EPSILON_DEFAULT = 1e-07f;
+  public static final float BETA_ONE_DEFAULT = 0.9f;
+  public static final float BETA_TWO_DEFAULT = 0.999f;
+
+  private float learningRate;
+  private final float betaOne;
+  private final float betaTwo;
+  private final float epsilon;
+
+  private Constant learningRateConst;
+  private Constant epsilonConst;
+  private Constant betaOneConst;
+  private Constant betaTwoConst;
+  private Variable betaOnePower;
+
+  /**
+   * Creates an Optimizer that implements the Adamax algorithm.
+   *
+   * @param graph the TensorFlow graph
+   */
+  public Adamax(Graph graph) {
+    this(graph, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates an Optimizer that implements the Adamax algorithm.
+   *
+   * @param graph the TensorFlow graph
+   * @param name name for the operations Created when applying gradients. Defaults to "Adamax".
+   */
+  public Adamax(Graph graph, String name) {
+    this(graph, name, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates an Optimizer that implements the Adamax algorithm.
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate The learning rate.
+   */
+  public Adamax(Graph graph, float learningRate) {
+    this(graph, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates an Optimizer that implements the Adamax algorithm.
+   *
+   * @param graph the TensorFlow graph
+   * @param name name for the operations Created when applying gradients. Defaults to "Adamax".
+   * @param learningRate The learning rate.
+   */
+  public Adamax(Graph graph, String name, float learningRate) {
+    this(graph, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates an Optimizer that implements the Adamax algorithm.
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate The learning rate.
+   * @param betaOne The exponential decay rate for the 1st moment estimates.
+   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm.
+   * @param epsilon A small constant for numerical stability.
+   */
+  public Adamax(Graph graph, float learningRate, float betaOne, float betaTwo, float epsilon) {
+    super(graph);
+    this.learningRate = learningRate;
+    this.betaOne = betaOne;
+    this.betaTwo = betaTwo;
+    this.epsilon = epsilon;
+  }
+
+  /**
+   * Creates an Optimizer that implements the Adamax algorithm.
+   *
+   * @param graph the TensorFlow graph
+   * @param name name for the operations Created when applying gradients. Defaults to "Adamax".
+   * @param learningRate The learning rate.
+   * @param betaOne The exponential decay rate for the 1st moment estimates.
+   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm.
+   * @param epsilon A small constant for numerical stability.
+   */
+  public Adamax(
+      Graph graph, String name, float learningRate, float betaOne, float betaTwo, float epsilon) {
+    super(graph, name);
+    this.learningRate = learningRate;
+    this.betaOne = betaOne;
+    this.betaTwo = betaTwo;
+    this.epsilon = epsilon;
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  protected Optional prepare(String scopeName) {
+    betaOneConst = tf.constant(betaOne);
+    betaTwoConst = tf.constant(betaTwo);
+    learningRateConst = tf.constant(learningRate);
+    epsilonConst = tf.constant(epsilon);
+
+    return Optional.empty();
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  protected void createSlots(List> variables) {
+    for (Output v : variables) {
+      createAdamaxSlot(v.asOutput());
+    }
+    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    Assign betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
+    ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit);
+  }
+
+  /**
+   * Creates the first and second moment slots
+   *
+   * @param v the variable
+   * @param  the datatype of the variable
+   */
+  private  void createAdamaxSlot(Output v) {
+    Operand firstMomentInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
+    Operand secondMomentInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  protected  Op applyDense(Output gradient, Output variable) {
+    Variable firstMomentSlot = getSlot(variable, FIRST_MOMENT).get();
+    Variable secondMomentSlot = getSlot(variable, SECOND_MOMENT).get();
+    return ApplyAdaMax.create(
+        this.tf.scope(),
+        variable,
+        firstMomentSlot,
+        secondMomentSlot,
+        tf.dtypes.cast(betaOnePower, gradient.dataType()),
+        tf.dtypes.cast(learningRateConst, gradient.dataType()),
+        tf.dtypes.cast(betaOneConst, gradient.dataType()),
+        tf.dtypes.cast(betaTwoConst, gradient.dataType()),
+        tf.dtypes.cast(epsilonConst, gradient.dataType()),
+        gradient);
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  protected Op finish(List updateOperations, String name) {
+    updateOperations.add(tf.assign(betaOnePower, tf.math.mul(betaOnePower, betaOneConst)));
+    return super.finish(updateOperations, name);
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  public String getOptimizerName() {
+    return "Adamax";
+  }
+}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Ftrl.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Ftrl.java
similarity index 55%
rename from tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Ftrl.java
rename to tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Ftrl.java
index db73f60c77e..13f68e4bbef 100644
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Ftrl.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Ftrl.java
@@ -1,59 +1,35 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+package org.tensorflow.framework.optimizers;
 
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
+import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
-import org.tensorflow.Session;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-import org.tensorflow.op.core.Assign;
-import org.tensorflow.op.core.Placeholder;
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.op.train.ApplyFtrl;
-import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TType;
 
-/** Ftrl (Follow the Regularized Leader) Optimizer that implements the FTRL algorithm. */
-public class Ftrl extends org.tensorflow.framework.optimizers.Optimizer
-    implements OptimizerInterface {
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String LEARNING_RATE_POWER_KEY = "learning_rate_power";
-  public static final String INITIAL_ACCUM_VALUE_KEY = "initial_accumulator_value";
-  public static final String L1STRENGTH_KEY = "l1_regularization_strength";
-  public static final String L2STRENGTH_KEY = "l2_regularization_strength";
-  public static final String L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY =
-      "l2_shrinkage_regularization_strength";
+import java.util.List;
 
-  public static final float LEARNING_RATE_DEFAULT = 0.001F;
-  public static final float LEARNING_RATE_POWER_DEFAULT = -0.5F;
-  public static final float INITIAL_ACCUM_VALUE_DEFAULT = 0.1F;
-  public static final float L1STRENGTH_DEFAULT = 0.0F;
-  public static final float L2STRENGTH_DEFAULT = 0.0F;
-  public static final float L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT = 0.0F;
+/**
+ * Optimizer that implements the FTRL algorithm.
+ *
+ * @see McMahan, et
+ *     al., 2013, Algorithm 1
+ *     
    This version has support for both online L2 (the L2 penalty given in the paper above) and
+ *     shrinkage-type L2 (which is the addition of an L2 penalty to the loss function).
+ */
+public class Ftrl extends Optimizer {
 
   public static final String ACCUMULATOR = "gradient_accumulator";
   public static final String LINEAR_ACCUMULATOR = "linear_accumulator";
 
-  private final String name;
+  public static final float LEARNING_RATE_DEFAULT = 0.001f;
+  public static final float LEARNING_RATE_POWER_DEFAULT = -0.5f;
+  public static final float INITIAL_ACCUMULATOR_VALUE_DEFAULT = 0.1f;
+  public static final float L1STRENGTH_DEFAULT = 0.0f;
+  public static final float L2STRENGTH_DEFAULT = 0.0f;
+  public static final float L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT = 0.0f;
+
   private float learningRate;
   private final float learningRatePower;
   private final float initialAccumulatorValue;
@@ -61,84 +37,80 @@ public class Ftrl extends org.tensorflow.framework.optimizers.Optimizer
   private final float l2RegularizationStrength;
   private final float l2ShrinkageRegularizationStrength;
 
-  private Map config = new HashMap<>();
-
-  private boolean useLocking = true;
-
   /**
-   * Create a Ftrl Optimizer
+   * Creates a Ftrl Optimizer
    *
-   * @param tf the TensorFlow Ops
+   * @param graph the TensorFlow Graph
    */
-  public Ftrl(Ops tf) {
+  public Ftrl(Graph graph) {
     this(
-        tf,
+        graph,
         LEARNING_RATE_DEFAULT,
         LEARNING_RATE_POWER_DEFAULT,
-        INITIAL_ACCUM_VALUE_DEFAULT,
+        INITIAL_ACCUMULATOR_VALUE_DEFAULT,
         L1STRENGTH_DEFAULT,
         L2STRENGTH_DEFAULT,
         L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT);
   }
 
   /**
-   * Create a Ftrl Optimizer
+   * Creates a Ftrl Optimizer
    *
-   * @param tf the TensorFlow Ops
-   * @param name the Optmizer name
+   * @param graph the TensorFlow Graph
+   * @param name the name of this Optimizer
    */
-  public Ftrl(Ops tf, String name) {
+  public Ftrl(Graph graph, String name) {
     this(
-        tf,
+        graph,
         name,
         LEARNING_RATE_DEFAULT,
         LEARNING_RATE_POWER_DEFAULT,
-        INITIAL_ACCUM_VALUE_DEFAULT,
+        INITIAL_ACCUMULATOR_VALUE_DEFAULT,
         L1STRENGTH_DEFAULT,
         L2STRENGTH_DEFAULT,
         L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT);
   }
 
   /**
-   * Create a Ftrl Optimizer
+   * Creates a Ftrl Optimizer
    *
-   * @param tf the TensorFlow Ops
+   * @param graph the TensorFlow Graph
    * @param learningRate the learning rate
    */
-  public Ftrl(Ops tf, float learningRate) {
+  public Ftrl(Graph graph, float learningRate) {
     this(
-        tf,
+        graph,
         learningRate,
         LEARNING_RATE_POWER_DEFAULT,
-        INITIAL_ACCUM_VALUE_DEFAULT,
+        INITIAL_ACCUMULATOR_VALUE_DEFAULT,
         L1STRENGTH_DEFAULT,
         L2STRENGTH_DEFAULT,
         L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT);
   }
 
   /**
-   * Create a Ftrl Optimizer
+   * Creates a Ftrl Optimizer
    *
-   * @param tf the TensorFlow Ops
-   * @param name the Optmizer name
+   * @param graph the TensorFlow Graph
+   * @param name the name of this Optimizer
    * @param learningRate the learning rate
    */
-  public Ftrl(Ops tf, String name, float learningRate) {
+  public Ftrl(Graph graph, String name, float learningRate) {
     this(
-        tf,
+        graph,
         name,
         learningRate,
         LEARNING_RATE_POWER_DEFAULT,
-        INITIAL_ACCUM_VALUE_DEFAULT,
+        INITIAL_ACCUMULATOR_VALUE_DEFAULT,
         L1STRENGTH_DEFAULT,
         L2STRENGTH_DEFAULT,
         L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT);
   }
 
   /**
-   * Create a Ftrl Optimizer
+   * Creates a Ftrl Optimizer
    *
-   * @param tf the TensorFlow Ops
+   * @param graph the TensorFlow Graph
    * @param learningRate the learning rate
    * @param learningRatePower Controls how the learning rate decreases during training. Use zero for
    *     a fixed learning rate.
@@ -149,17 +121,19 @@ public Ftrl(Ops tf, String name, float learningRate) {
    * @param l2ShrinkageRegularizationStrength This differs from L2 above in that the L2 above is a
    *     stabilization penalty, whereas this L2 shrinkage is a magnitude penalty. must be greater
    *     than or equal to zero.
+   * @throws java.lang.IllegalArgumentException if the initialAccumulatorValue,
+   *     l1RegularizationStrength, l2RegularizationStrength, or l2ShrinkageRegularizationStrength
+   *     are less than 0.0, or learningRatePower is greater than 0.0.
    */
   public Ftrl(
-      Ops tf,
+      Graph graph,
       float learningRate,
       float learningRatePower,
       float initialAccumulatorValue,
       float l1Strength,
       float l2Strength,
       float l2ShrinkageRegularizationStrength) {
-    super(assertGraph(tf));
-    this.name = getOptimizerName();
+    super(graph);
     this.learningRate = learningRate;
     this.learningRatePower = learningRatePower;
     this.initialAccumulatorValue = initialAccumulatorValue;
@@ -167,14 +141,13 @@ public Ftrl(
     this.l2RegularizationStrength = l2Strength;
     this.l2ShrinkageRegularizationStrength = l2ShrinkageRegularizationStrength;
     validateParams();
-    initConfig();
   }
 
   /**
-   * Create a Ftrl Optimizer
+   * Creates a Ftrl Optimizer
    *
-   * @param tf the TensorFlow Ops
-   * @param name the name of this Ftrl Optimizer
+   * @param graph the TensorFlow Graph
+   * @param name the name of this Optimizer
    * @param learningRate the learning rate
    * @param learningRatePower Controls how the learning rate decreases during training. Use zero for
    *     a fixed learning rate.
@@ -185,9 +158,12 @@ public Ftrl(
    * @param l2ShrinkageRegularizationStrength This differs from L2 above in that the L2 above is a
    *     stabilization penalty, whereas this L2 shrinkage is a magnitude penalty. must be greater
    *     than or equal to zero.
+   * @throws java.lang.IllegalArgumentException if the initialAccumulatorValue,
+   *     l1RegularizationStrength, l2RegularizationStrength, or l2ShrinkageRegularizationStrength
+   *     are less than 0.0, or learningRatePower is greater than 0.0.
    */
   public Ftrl(
-      Ops tf,
+      Graph graph,
       String name,
       float learningRate,
       float learningRatePower,
@@ -195,8 +171,7 @@ public Ftrl(
       float l1Strength,
       float l2Strength,
       float l2ShrinkageRegularizationStrength) {
-    super(assertGraph(tf), name);
-    this.name = name;
+    super(graph, name);
     this.learningRate = learningRate;
     this.learningRatePower = learningRatePower;
     this.initialAccumulatorValue = initialAccumulatorValue;
@@ -204,67 +179,9 @@ public Ftrl(
     this.l2RegularizationStrength = l2Strength;
     this.l2ShrinkageRegularizationStrength = l2ShrinkageRegularizationStrength;
     validateParams();
-    initConfig();
-  }
-
-  /**
-   * Create a Ftrl Optmizer
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize
-   * @return a new Frtl Optimizer
-   */
-  public static Ftrl create(Ops tf, Map config) {
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float learningRatePower =
-        (float) config.getOrDefault(LEARNING_RATE_POWER_KEY, LEARNING_RATE_POWER_DEFAULT);
-    float initialAccumulatorValue =
-        (float) config.getOrDefault(INITIAL_ACCUM_VALUE_KEY, INITIAL_ACCUM_VALUE_DEFAULT);
-    float l1RegularizationStrength =
-        (float) config.getOrDefault(L1STRENGTH_KEY, L1STRENGTH_DEFAULT);
-    float l2RegularizationStrength =
-        (float) config.getOrDefault(L2STRENGTH_KEY, L2STRENGTH_DEFAULT);
-    float l2ShrinkageRegularizationStrength =
-        (float)
-            config.getOrDefault(
-                L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY,
-                L2_SHRINKAGE_REGULARIZATION_STRENGTH_DEFAULT);
-
-    if (name == null) {
-      return new Ftrl(
-          tf,
-          learningRate,
-          learningRatePower,
-          initialAccumulatorValue,
-          l1RegularizationStrength,
-          l2RegularizationStrength,
-          l2ShrinkageRegularizationStrength);
-    } else {
-      return new Ftrl(
-          tf,
-          name,
-          learningRate,
-          learningRatePower,
-          initialAccumulatorValue,
-          l1RegularizationStrength,
-          l2RegularizationStrength,
-          l2ShrinkageRegularizationStrength);
-    }
   }
 
-  /** Initialize the Config object from the current settings */
-  protected void initConfig() {
-    config.put(NAME_KEY, this.name);
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(LEARNING_RATE_POWER_KEY, learningRatePower);
-    config.put(INITIAL_ACCUM_VALUE_KEY, initialAccumulatorValue);
-    config.put(L1STRENGTH_KEY, l1RegularizationStrength);
-    config.put(L2STRENGTH_KEY, l2RegularizationStrength);
-    config.put(L2_SHRINKAGE_REGULARIZATION_STRENGTH_KEY, l2ShrinkageRegularizationStrength);
-  }
-
-  /** Validate all the settings of the Frtl Optmizer */
+  /** Validates all the settings of the Frtl Optmizer */
   private void validateParams() {
     if (this.initialAccumulatorValue < 0.0F) {
       throw new IllegalArgumentException(
@@ -306,7 +223,7 @@ protected void createSlots(List> variables) {
   }
 
   /**
-   * Create a slot variables for the accumulators
+   * Creates a slot variables for the accumulators
    *
    * @param v the variable
    * @param  the data type of the variable
@@ -325,7 +242,7 @@ private  void createFtrlSlot(Output v) {
   protected  Op applyDense(Output gradient, Output variable) {
     Variable accumSlot = getSlot(variable, ACCUMULATOR).get();
     Variable linearSlot = getSlot(variable, LINEAR_ACCUMULATOR).get();
-    ApplyFtrl.Options options = ApplyFtrl.useLocking(useLocking);
+    ApplyFtrl.Options options = ApplyFtrl.useLocking(true);
     return this.tf.train.applyFtrl(
         variable,
         accumSlot, // accum
@@ -345,22 +262,4 @@ protected  Op applyDense(Output gradient, Output variable
   public String getOptimizerName() {
     return "Ftrl";
   }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java
index 7ed90c846f1..e307855e636 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java
@@ -21,35 +21,61 @@
 import org.tensorflow.types.family.TType;
 
 /**
- * Basic SGD.
+ * Basic Stochastic gradient descent optimizer. GradientDescent updates the current weight using the
+ * current gradient ?L/?w multiplied by the learning rate.
  */
 public class GradientDescent extends Optimizer {
 
+  public static final float LEARNING_RATE_DEFAULT = 0.01f;
+
   private final float learningRate;
 
+  /**
+   * Creates a GradientDescent Optimizer
+   *
+   * @param graph the TensorFlow graph
+   */
+  public GradientDescent(Graph graph) {
+    this(graph, LEARNING_RATE_DEFAULT);
+  }
+
+  /**
+   * Creates a GradientDescent Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate, defaults to 0.01
+   */
   public GradientDescent(Graph graph, float learningRate) {
     super(graph);
     this.learningRate = learningRate;
   }
 
+  /**
+   * Creates a GradientDescent Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param name the name for this Optimizer, default is "GradientDescent"
+   * @param learningRate the learning rate, defaults to 0.01
+   */
   public GradientDescent(Graph graph, String name, float learningRate) {
     super(graph, name);
     this.learningRate = learningRate;
   }
 
+  /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
-    return tf.train.applyGradientDescent(variable,
-        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), gradient);
+    return tf.train.applyGradientDescent(
+        variable, tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), gradient);
   }
 
+  /** {@inheritDoc} */
   @Override
   public String toString() {
-    return "GradientDescent{" +
-        "learningRate=" + learningRate +
-        '}';
+    return "GradientDescent{" + "learningRate=" + learningRate + '}';
   }
 
+  /** {@inheritDoc} */
   @Override
   public String getOptimizerName() {
     return "GradientDescent";
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java
index b8582b4e278..111727d26fa 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.optimizers;
 
-import java.util.List;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
@@ -24,14 +23,20 @@
 import org.tensorflow.op.train.ApplyMomentum;
 import org.tensorflow.types.family.TType;
 
+import java.util.List;
+
 /**
- * SGD plus momentum, either nesterov or traditional.
- * 
    
- * See the paper for details of
- * nesterov momentum.
+ * Stochastic gradient descent plus momentum, either nesterov or traditional.
+ *
+ * 
    See the paper for details
+ * of nesterov momentum.
  */
 public class Momentum extends Optimizer {
 
+  public static final float LEARNING_RATE_DEFAULT = 0.01F;
+  public static final float MOMENTUM_DEFAULT = 0.0F;
+  public static final boolean NESTEROV_DEFAULT = false;
+
   public static final String MOMENTUM = "momentum";
 
   private final float learningRate;
@@ -40,6 +45,46 @@ public class Momentum extends Optimizer {
 
   private final boolean useNesterov;
 
+  /**
+   * Creates a Momentum Optimizer
+   *
+   * @param graph the TensorFlow graph
+   */
+  public Momentum(Graph graph) {
+    this(graph, LEARNING_RATE_DEFAULT, MOMENTUM_DEFAULT, NESTEROV_DEFAULT);
+  }
+
+  /**
+   * Creates a Momentum Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate
+   */
+  public Momentum(Graph graph, float learningRate) {
+    this(graph, learningRate, MOMENTUM_DEFAULT, NESTEROV_DEFAULT);
+  }
+
+  /**
+   * Creates a Momentum Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate
+   * @param momentum hyperparameter that accelerates gradient descent in the relevant direction and
+   *     dampens oscillations, Must be greater than or equal to zero. Default is 0.
+   */
+  public Momentum(Graph graph, float learningRate, float momentum) {
+    this(graph, learningRate, momentum, NESTEROV_DEFAULT);
+  }
+
+  /**
+   * Creates a Momentum Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate
+   * @param momentum hyperparameter that accelerates gradient descent in the relevant direction and
+   *     dampens oscillations, Must be greater than or equal to zero. Default is 0.
+   * @param useNesterov Whether to apply Nesterov momentum. Defaults to false.
+   */
   public Momentum(Graph graph, float learningRate, float momentum, boolean useNesterov) {
     super(graph);
     this.learningRate = learningRate;
@@ -47,13 +92,25 @@ public Momentum(Graph graph, float learningRate, float momentum, boolean useNest
     this.useNesterov = useNesterov;
   }
 
-  public Momentum(Graph graph, String name, float learningRate, float momentum, boolean useNesterov) {
+  /**
+   * Creates a Momentum Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param name the name for this Optimizer
+   * @param learningRate the learning rate
+   * @param momentum hyperparameter that accelerates gradient descent in the relevant direction and
+   *     dampens oscillations, Must be greater than or equal to zero. Default is 0.
+   * @param useNesterov Whether to apply Nesterov momentum. Defaults to false.
+   */
+  public Momentum(
+      Graph graph, String name, float learningRate, float momentum, boolean useNesterov) {
     super(graph, name);
     this.learningRate = learningRate;
     this.momentum = momentum;
     this.useNesterov = useNesterov;
   }
 
+  /** {@inheritDoc} */
   @Override
   protected void createSlots(List> variables) {
     for (Output v : variables) {
@@ -61,31 +118,44 @@ protected void createSlots(List> variables) {
     }
   }
 
+  /**
+   * Creates a slot for the momentum variable
+   *
+   * @param v the variable
+   * @param  the data type of the variable
+   */
   private  void createMomentumSlot(Output v) {
-    Operand initializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand initializer = tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
     createSlot(v.asOutput(), MOMENTUM, initializer);
   }
 
+  /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
     Variable slot = getSlot(variable, MOMENTUM).get();
-    return tf.train
-        .applyMomentum(variable, slot, tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
-            gradient,
-            tf.dtypes.cast(tf.constant(momentum), gradient.dataType()),
-            ApplyMomentum.useNesterov(useNesterov));
+    return tf.train.applyMomentum(
+        variable,
+        slot,
+        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
+        gradient,
+        tf.dtypes.cast(tf.constant(momentum), gradient.dataType()),
+        ApplyMomentum.useNesterov(useNesterov));
   }
 
+  /** {@inheritDoc} */
   @Override
   public String toString() {
-    return "Momentum{" +
-        "learningRate=" + learningRate +
-        ", momentum=" + momentum +
-        ", useNesterov=" + useNesterov +
-        '}';
+    return "Momentum{"
+        + "learningRate="
+        + learningRate
+        + ", momentum="
+        + momentum
+        + ", useNesterov="
+        + useNesterov
+        + '}';
   }
 
+  /** {@inheritDoc} */
   @Override
   public String getOptimizerName() {
     return "Momentum";
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java
new file mode 100644
index 00000000000..48e5135c952
--- /dev/null
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java
@@ -0,0 +1,302 @@
+package org.tensorflow.framework.optimizers;
+
+import org.tensorflow.DataType;
+import org.tensorflow.Graph;
+import org.tensorflow.Operand;
+import org.tensorflow.Output;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Op;
+import org.tensorflow.op.core.Assign;
+import org.tensorflow.op.core.Constant;
+import org.tensorflow.op.core.Variable;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TType;
+
+import java.util.List;
+import java.util.Optional;
+
+/**
+ * Nadam Optimizer that implements the NAdam algorithm.
+ *
+ * 
    Much like Adam is essentially RMSprop with momentum, Nadam is Adam with Nesterov momentum.
+ *
+ * @see Dozat, 2015
+ */
+public class Nadam extends Optimizer {
+
+  private static final float DECAY_BASE = 0.96f;
+  private static final float DECAY = 0.004f;
+  public static final float LEARNING_RATE_DEFAULT = 0.001f;
+  public static final float EPSILON_DEFAULT = 1e-8f;
+  public static final float BETA_ONE_DEFAULT = 0.9f;
+  public static final float BETA_TWO_DEFAULT = 0.999f;
+  public static final String FIRST_MOMENT = "m";
+  public static final String SECOND_MOMENT = "v";
+  public static final String MOMENTUM = "momentum";
+
+  /** The learning rate. */
+  private final float learningRate;
+
+  /** The exponential decay rate for the 1st moment estimates. */
+  private final float betaOne;
+
+  /** The exponential decay rate for the exponentially weighted infinity norm. */
+  private final float betaTwo;
+
+  /** A small constant for numerical stability. */
+  private final float epsilon;
+
+  private Constant learningRateConst;
+  private Constant epsilonConst;
+  private Constant betaOneConst;
+  private Constant betaTwoConst;
+
+  private Variable betaOnePower;
+  private Variable betaTwoPower;
+  private Variable momentum;
+
+  private long iterations = 0;
+
+  // private Operand mT;
+  private Operand mT1;
+
+  private Operand oneMinusBeta1;
+  private Operand oneMinusBeta2;
+  private Operand oneMinusMT;
+  private Operand oneMinusMScheduleNew;
+  private Operand oneMinusMScheduleNext;
+  private Operand vTPrimeDenominator;
+
+  /**
+   * Creates a Nadam Optimizer
+   *
+   * @param graph the TensorFlow graph
+   */
+  public Nadam(Graph graph) {
+    this(graph, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates a Nadam Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate, defaults to 0.001
+   */
+  public Nadam(Graph graph, float learningRate) {
+    this(graph, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates a Nadam Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param learningRate the learning rate, defaults to 0.001
+   * @param betaOne The exponential decay rate for the 1st moment estimates. Default is 0.9.
+   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm. Default
+   *     is 0.999.
+   * @param epsilon A small constant for numerical stability. Default is 1e-8.
+   */
+  public Nadam(Graph graph, float learningRate, float betaOne, float betaTwo, float epsilon) {
+    super(graph);
+    this.learningRate = learningRate;
+    this.betaOne = betaOne;
+    this.betaTwo = betaTwo;
+    this.epsilon = epsilon;
+  }
+
+  /**
+   * Creates a Nadam Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param name the name for this Optimizer, defaults to "Nadam"
+   * @param learningRate the learning rate, defaults to 0.001
+   */
+  public Nadam(Graph graph, String name, float learningRate) {
+    this(graph, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
+  }
+
+  /**
+   * Creates a Nadam Optimizer
+   *
+   * @param graph the TensorFlow graph
+   * @param name the name for this Optimizer, defaults to "Nadam"
+   * @param learningRate the learning rate, defaults to 0.001
+   * @param betaOne The exponential decay rate for the 1st moment estimates. Default is 0.9.
+   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm. Default
+   *     is 0.999.
+   * @param epsilon A small constant for numerical stability. Default is 1e-8.
+   */
+  public Nadam(
+      Graph graph, String name, float learningRate, float betaOne, float betaTwo, float epsilon) {
+    super(graph, name);
+    this.learningRate = learningRate;
+    this.betaOne = betaOne;
+    this.betaTwo = betaTwo;
+    this.epsilon = epsilon;
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  protected void createSlots(List> variables) {
+    for (Output v : variables) {
+      createNadamSlot(v.asOutput());
+    }
+    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    Assign betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
+    ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit);
+
+    betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    Assign betaTwoPowerInit = tf.assign(betaTwoPower, tf.constant(betaTwo));
+    ((Graph) tf.scope().env()).addInitializer(betaTwoPowerInit);
+
+    momentum = tf.withName("momentum").variable(Shape.scalar(), TFloat32.DTYPE);
+    Assign momentumInit = tf.assign(momentum, tf.constant(1.0F));
+    ((Graph) tf.scope().env()).addInitializer(momentumInit);
+  }
+
+  /**
+   * Creates slots for first and second moments and momentum
+   *
+   * @param v the variable
+   * @param  the data type or the Variable
+   */
+  private  void createNadamSlot(Output v) {
+    Operand firstMomentInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
+    Operand secondMomentInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
+
+    Operand momentumInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.dataType()));
+    createSlot(v.asOutput(), MOMENTUM, momentumInitializer);
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  protected Optional prepare(String scopeName) {
+    Constant one = tf.constant(1.0F);
+    Constant point5 = tf.constant(0.5F);
+
+    learningRateConst = tf.constant(learningRate);
+    betaOneConst = tf.constant(betaOne);
+    betaTwoConst = tf.constant(betaTwo);
+    Constant localStepConst = tf.constant(this.iterations + 1);
+    Constant nextStepConst = tf.constant(this.iterations + 2);
+    Constant decayConst = tf.constant(DECAY);
+    Constant decayBaseConst = tf.constant(DECAY_BASE);
+    epsilonConst = tf.constant(this.epsilon);
+
+    Operand mT =
+        tf.math.mul(
+            betaOneConst,
+            tf.math.sub(
+                one,
+                tf.math.mul(
+                    point5,
+                    tf.math.pow(
+                        decayBaseConst,
+                        tf.math.mul(decayConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE))))));
+
+    mT1 =
+        tf.math.mul(
+            betaOneConst,
+            tf.math.sub(
+                one,
+                tf.math.mul(
+                    point5,
+                    tf.math.pow(
+                        decayBaseConst,
+                        tf.math.mul(decayConst, tf.dtypes.cast(nextStepConst, TFloat32.DTYPE))))));
+
+    Operand mScheduleNew = tf.math.mul(momentum, mT);
+
+    mScheduleNew = tf.assign(momentum, mScheduleNew, Assign.useLocking(true));
+    Operand mScheduleNext = tf.math.mul(mScheduleNew, mT1);
+
+    oneMinusBeta1 = tf.math.sub(one, betaOneConst);
+    oneMinusBeta2 = tf.math.sub(one, betaTwoConst);
+    oneMinusMT = tf.math.sub(one, mT);
+    oneMinusMScheduleNew = tf.math.sub(one, mScheduleNew);
+    oneMinusMScheduleNext = tf.math.sub(one, mScheduleNext);
+    vTPrimeDenominator =
+        tf.math.sub(one, tf.math.pow(betaTwoConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE)));
+    return Optional.empty();
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  protected  Op applyDense(Output gradient, Output variable) {
+    DataType dType = gradient.dataType();
+    Variable m = getSlot(variable, FIRST_MOMENT).get(); // first Moment
+    Variable v = getSlot(variable, SECOND_MOMENT).get(); // Second Moment
+
+    //  gPrime = grad / coefficients['oneMinusMScheduleNew']
+    Operand gPrime = tf.math.div(gradient, tf.dtypes.cast(oneMinusMScheduleNew, dType));
+    // mT = (coefficients['beta_1_t'] * m + coefficients['one_minus_beta_1_t'] * grad)
+    Operand mT =
+        tf.math.add(
+            tf.math.mul(tf.dtypes.cast(betaOneConst, dType), m),
+            tf.math.mul(tf.dtypes.cast(oneMinusBeta1, dType), gradient));
+    // mT = state_ops.assign(m, mT, use_locking=self._use_locking)
+    // update m
+    mT = tf.assign(m, mT, Assign.useLocking(true));
+
+    // mTPrime = mT / coefficients['oneMinusMScheduleNext']
+    Operand mTPrime = tf.math.div(mT, tf.dtypes.cast(oneMinusMScheduleNext, dType));
+
+    // vT = (coefficients['beta_2_t'] * v + coefficients['one_minus_beta_2_t'] *
+    // math_ops.square(grad))
+    Operand vT =
+        tf.math.add(
+            tf.math.mul(tf.dtypes.cast(betaTwoConst, dType), v),
+            tf.math.mul(tf.dtypes.cast(oneMinusBeta2, dType), tf.math.square(gradient)));
+    // vT = state_ops.assign(v, vT, use_locking=self._use_locking)
+    // update v
+    vT = tf.assign(v, vT, Assign.useLocking(true));
+
+    // vTPrime = vT / coefficients['vTPrimeDenominator']
+    Operand vTPrime = tf.math.div(vT, tf.dtypes.cast(vTPrimeDenominator, dType));
+
+    // m_t_bar = (coefficients['oneMinusMT'] * gPrime + coefficients['mT1'] * mTPrime)
+    Operand m_t_bar =
+        tf.math.add(
+            tf.math.mul(tf.dtypes.cast(oneMinusMT, dType), gPrime),
+            tf.math.mul(tf.dtypes.cast(mT1, dType), mTPrime));
+    // varT = var - coefficients['lr_t'] * m_t_bar / (math_ops.sqrt(vTPrime) +
+    // coefficients['epsilon'])
+    Operand varT =
+        tf.math.sub(
+            variable,
+            tf.math.div(
+                tf.math.mul(tf.dtypes.cast(learningRateConst, dType), m_t_bar),
+                tf.math.add(tf.math.sqrt(vTPrime), tf.dtypes.cast(epsilonConst, dType))));
+
+    return tf.assign(variable, varT, Assign.useLocking(true));
+  }
+
+  /**
+   * Gathers up the update operations into a single op that can be used as a run target.
+   *
+   * 
    Adds the betaOne, betaTwo and mu updates to the end of the updates list.
+   *
+   * @param updateOperations The update operations.
+   * @param name The name of the run target.
+   * @return A NoOp with a control dependency on each update operation.
+   */
+  @Override
+  protected Op finish(List updateOperations, String name) {
+    iterations++; // increment the step;
+    updateOperations.add(tf.assign(betaOnePower, tf.math.mul(betaOnePower, betaOneConst)));
+    updateOperations.add(tf.assign(betaTwoPower, tf.math.mul(betaTwoPower, betaTwoConst)));
+    return super.finish(updateOperations, name);
+  }
+
+  /** {@inheritDoc} */
+  @Override
+  public String getOptimizerName() {
+    return "Nadam";
+  }
+}
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
index ffff35a8ddd..f7032d18b38 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
@@ -15,12 +15,6 @@
  */
 package org.tensorflow.framework.optimizers;
 
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Optional;
-import java.util.stream.Collectors;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
@@ -33,34 +27,28 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.family.TType;
 
-/**
- * Base class for gradient optimizers.
- */
+import java.util.*;
+import java.util.stream.Collectors;
+
+/** Base class for gradient optimizers. */
 public abstract class Optimizer {
 
   public static final String VARIABLE_V2 = "VariableV2";
-  /**
-   * Global state variables
-   */
-  //TODO make this be used.
+  /** Global state variables */
+  // TODO make this be used.
   protected final List> globals;
-  /**
-   * The Graph this optimizer is operating on.
-   */
+  /** The Graph this optimizer is operating on. */
   protected final Graph graph;
-  /**
-   * The ops builder for the graph.
-   */
+  /** The ops builder for the graph. */
   protected final Ops tf;
-  /**
-   * Top level map key is the variable name, lower level map key is the slot name.
-   */
+  /** Top level map key is the variable name, lower level map key is the slot name. */
   private final Map>> slots;
 
   /**
    * Builds an optimizer for the supplied graph.
-   * 
    
-   * Uses the name from {@link Optimizer#getOptimizerName()} to name the operations.
+   *
+   * 
    Uses the name from {@link Optimizer#getOptimizerName()} to name the operations.
+   *
    * @param graph The graph to optimize.
    */
   protected Optimizer(Graph graph) {
@@ -72,6 +60,7 @@ protected Optimizer(Graph graph) {
 
   /**
    * Builds an optimizer for the supplied graph.
+   *
    * @param graph The graph to optimize.
    * @param name The base name for the operations.
    */
@@ -82,27 +71,57 @@ protected Optimizer(Graph graph, String name) {
     this.globals = new ArrayList<>();
   }
 
+  /**
+   * Creates a name by combining a variable name and a slot name
+   *
+   * @param variable the variable
+   * @param slotName the name of the slot
+   * @return the combined name
+   */
   public static String createName(Output variable, String slotName) {
     return variable.op().name() + "-" + slotName;
   }
 
+  /**
+   * Minimizes the loss by updating the variables
+   *
+   * @param loss the loss operation that returns the value to minimize
+   * @return returns op that minimizes the loss by updating the listed variables
+   */
   public Op minimize(Operand loss) {
     return minimize(loss, getOptimizerName() + "-minimize");
   }
 
+  /**
+   * Minimizes the loss by updating the variables
+   *
+   * @param loss the loss operation that returns the value to minimize
+   * @param name the name for the minimize operation
+   * @return op that minimizes the loss by updating the listed variables
+   */
   public Op minimize(Operand loss, String name) {
     List> gradsAndVars = computeGradients(loss);
 
     return applyGradients(gradsAndVars, name);
   }
 
+  /**
+   * Computes the gradients based on a loss operand.
+   *
+   * @param loss the loss operation
+   * @param  the data type of the loss, gradients and variables.
+   * @return the computed gradients
+   */
   public  List> computeGradients(Operand loss) {
     List variables = new ArrayList<>();
-    graph.operations().forEachRemaining((Operation op) -> {
-      if (op.type().equals(VARIABLE_V2)) {
-        variables.add(op);
-      }
-    });
+    graph
+        .operations()
+        .forEachRemaining(
+            (Operation op) -> {
+              if (op.type().equals(VARIABLE_V2)) {
+                variables.add(op);
+              }
+            });
 
     Output[] variableOutputArray = new Output[variables.size()];
     for (int i = 0; i < variables.size(); i++) {
@@ -124,9 +143,16 @@ public  List> computeGradients(Operand loss) {
     return gradVarPairs;
   }
 
+  /**
+   * Applies gradients to variables
+   *
+   * @param gradsAndVars the list of (gradient, variable) pairs.
+   * @param name the name of the apply gradients operation
+   * @return an Op that applies the gradients to the variables.
+   */
   public Op applyGradients(List> gradsAndVars, String name) {
-    List> variables = gradsAndVars.stream().map(GradAndVar::getVariable)
-        .collect(Collectors.toList());
+    List> variables =
+        gradsAndVars.stream().map(GradAndVar::getVariable).collect(Collectors.toList());
 
     createSlots(variables);
 
@@ -144,7 +170,7 @@ public Op applyGradients(List> gradsAndVars, String
   /**
    * Gets the slot associated with the specified variable and slot name.
    *
-   * @param var      The variable to lookup.
+   * @param var The variable to lookup.
    * @param slotName The slot name.
    * @return The slot or {@link Optional#empty}.
    */
@@ -155,7 +181,7 @@ public  Optional> getSlot(Output var, String slo
   /**
    * Gets the slot associated with the specified variable and slot name.
    *
-   * @param varName  The variable to lookup.
+   * @param varName The variable to lookup.
    * @param slotName The slot name.
    * @return The slot or {@link Optional#empty}.
    */
@@ -165,7 +191,7 @@ private  Optional> getSlot(String varName, String s
       Variable slot = variables.get(varName);
       if (slot != null) {
         @SuppressWarnings("unchecked") // This method should only be called when the type is known.
-            Optional> opt = Optional.of((Variable) slot);
+        Optional> opt = Optional.of((Variable) slot);
         return opt;
       }
       return Optional.empty();
@@ -177,25 +203,25 @@ private  Optional> getSlot(String varName, String s
    * Creates a slot in the graph for the specified variable with the specified name. Adds the slot's
    * initializer to the graph's initializers, and the slot to the Optimizer's slot map.
    *
-   * @param variable    The variable to create the slot for.
-   * @param slotName    The name of the slot.
+   * @param variable The variable to create the slot for.
+   * @param slotName The name of the slot.
    * @param initializer The initializer for the slot.
-   * @param          The type of the variable.
+   * @param  The type of the variable.
    */
-  protected  void createSlot(Output variable, String slotName,
-      Operand initializer) {
-    Variable slot = tf.withName(createName(variable, slotName))
-        .variable(variable.shape(), variable.dataType());
+  protected  void createSlot(
+      Output variable, String slotName, Operand initializer) {
+    Variable slot =
+        tf.withName(createName(variable, slotName)).variable(variable.shape(), variable.dataType());
     Assign slotInit = tf.assign(slot, initializer);
     graph.addInitializer(slotInit);
     String varName = variable.op().name();
-    Map> variables = slots
-        .computeIfAbsent(slotName, (k) -> new HashMap<>());
+    Map> variables =
+        slots.computeIfAbsent(slotName, (k) -> new HashMap<>());
     variables.put(varName, slot);
   }
 
   /**
-   * No-op prepare method.
+   * Returns a No-op prepare.
    *
    * @param scopeName The scope name to use for any variable creations.
    */
@@ -204,13 +230,19 @@ protected Optional prepare(String scopeName) {
   }
 
   /**
-   * No-op slot creation method.
+   * Performs a No-op slot creation method.
    *
    * @param variables The variables to create slots for.
    */
-  protected void createSlots(List> variables) {
-  }
+  protected void createSlots(List> variables) {}
 
+  /**
+   * Generates the gradient update operations for the specific variable and gradient.
+   *
+   * @param gradVarPair the list of (gradient, variable) pairs.
+   * @param  the datatype of the gradients and variables.
+   * @return An operand which applies the desired optimizer update to the variable.
+   */
   private  Op applyDense(GradAndVar gradVarPair) {
     return applyDense(gradVarPair.getGradient(), gradVarPair.getVariable());
   }
@@ -220,7 +252,7 @@ private  Op applyDense(GradAndVar gradVarPair) {
    *
    * @param gradient The gradient to use.
    * @param variable The variable to update.
-   * @param       The type of the variable.
+   * @param  The type of the variable.
    * @return An operand which applies the desired optimizer update to the variable.
    */
   protected abstract  Op applyDense(Output gradient, Output variable);
@@ -229,7 +261,7 @@ private  Op applyDense(GradAndVar gradVarPair) {
    * Gathers up the update operations into a single op that can be used as a run target.
    *
    * @param updateOperations The update operations.
-   * @param name             The name of the run target.
+   * @param name The name of the run target.
    * @return A NoOp with a control dependency on each update operation.
    */
   protected Op finish(List updateOperations, String name) {
@@ -240,25 +272,24 @@ protected Op finish(List updateOperations, String name) {
   }
 
   /**
-   * Name of the optimizer.
+   * Get the Name of the optimizer.
    *
    * @return The optimizer name.
    */
   public abstract String getOptimizerName();
 
-  /**
-   * Optional attributes for {@link org.tensorflow.training.optimizers.Optimizer}
-   */
+  /** Optional attributes for {@link org.tensorflow.framework.optimizers.Optimizer} */
   public static class Options {
 
     protected String sharedName;
 
-    private Options() {
-    }
+    private Options() {}
 
     /**
+     * Sets the shared name
+     *
      * @param sharedName If non-empty, this variable is named in the given bucket with this
-     *                   shared_name. Otherwise, the node name is used instead.
+     *     shared_name. Otherwise, the node name is used instead.
      */
     public Optimizer.Options sharedName(String sharedName) {
       this.sharedName = sharedName;
@@ -266,20 +297,41 @@ public Optimizer.Options sharedName(String sharedName) {
     }
   }
 
+  /**
+   * A class that holds a paired gradient and variable.
+   *
+   * @param  the data type for the gradient and variable
+   */
   public static class GradAndVar {
 
     private final Output gradient;
     private final Output variable;
 
+    /**
+     * Creates a Gradient and Variable pair
+     *
+     * @param gradient the gradient
+     * @param variable the variable
+     */
     public GradAndVar(Output gradient, Output variable) {
       this.gradient = gradient;
       this.variable = variable;
     }
 
+    /**
+     * Gets the gradient
+     *
+     * @return the gradient
+     */
     public Output getGradient() {
       return gradient;
     }
 
+    /**
+     * Gets the variable
+     *
+     * @return the variable
+     */
     public Output getVariable() {
       return variable;
     }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java
new file mode 100644
index 00000000000..7099a050d3e
--- /dev/null
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java
@@ -0,0 +1,41 @@
+package org.tensorflow.framework.optimizers;
+
+import org.tensorflow.Graph;
+
+import java.util.function.Function;
+
+/** Enumerator used to create a new Optimizer with default parameters. */
+public enum Optimizers {
+  ADADELTA(AdaDelta::new),
+  ADAGRAD(AdaGrad::new),
+  ADAGRAD_DA(AdaGradDA::new),
+  ADAM(Adam::new),
+  ADAMAX(Adamax::new),
+  FTRL(Ftrl::new),
+  NADAM(Nadam::new),
+  RMSPROP(RMSProp::new),
+  MOMENTUM(Momentum::new),
+  GRADIENT_DESCENT(Momentum::new);
+
+  private final Function creator;
+
+  /**
+   * Creates an Optimizers enum
+   *
+   * @param creator the lambda function that accepts a Graph argument used to create the default
+   *     Optimizer
+   */
+  Optimizers(Function creator) {
+    this.creator = creator;
+  }
+
+  /**
+   * Creates an Optimizer with default settings.
+   *
+   * @param graph the TensorFlow Graph
+   * @return the Optimizer
+   */
+  public Optimizer createOptimizer(Graph graph) {
+    return creator.apply(graph);
+  }
+}
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java
index cc64a23de3d..8b71558e549 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.optimizers;
 
-import java.util.List;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
@@ -23,14 +22,36 @@
 import org.tensorflow.op.core.Variable;
 import org.tensorflow.types.family.TType;
 
+import java.util.List;
+
 /**
  * Optimizer that implements the RMSProp algorithm.
- * 
    
- * See the lecture
- * notes that is inexplicably the canonical reference.
+ *
+ * 
    The gist of RMSprop is to: 
+ * 
  • Maintain a moving (discounted) average of the square of gradients
+ * 
  • Divide the gradient by the root of this average 
+ *
+ *     
    
+ *
+ *     
    This implementation of RMSprop uses plain momentum, not Nesterov momentum.
+ *
+ *     
    
+ *
+ *     
    The centered version additionally maintains a moving average of the gradients, and uses
+ *     that average to estimate the variance.
+ *
+ *     
    
+ *
+ * @see Hinton G,
+ *     et al. 2012, lecture notes that is inexplicably the canonical reference.
  */
 public class RMSProp extends Optimizer {
 
+  public static final float LEARNING_RATE_DEFAULT = 0.001f;
+  public static final float DECAY_DEFAULT = 0.9f;
+  public static final float MOMENTUM_DEFAULT = 0.0f;
+  public static final float EPSILON_DEFAULT = 1e-10f;
+  public static final boolean CENTERED_DEFAULT = false;
   public static final String RMS = "rms";
   public static final String MG = "mg"; // mean gradient?
   public static final String MOMENTUM = "momentum";
@@ -41,11 +62,50 @@ public class RMSProp extends Optimizer {
   private final float epsilon;
   private final boolean centered;
 
+  /**
+   * Creates an RMSPRrop Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   */
+  public RMSProp(Graph graph) {
+    this(
+        graph,
+        LEARNING_RATE_DEFAULT,
+        DECAY_DEFAULT,
+        MOMENTUM_DEFAULT,
+        EPSILON_DEFAULT,
+        CENTERED_DEFAULT);
+  }
+
+  /**
+   * Creates an RMSPRrop Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   */
   public RMSProp(Graph graph, float learningRate) {
-    this(graph, learningRate, 0.9f, 0.0f, 1e-10f, false);
+    this(graph, learningRate, DECAY_DEFAULT, MOMENTUM_DEFAULT, EPSILON_DEFAULT, CENTERED_DEFAULT);
   }
 
-  public RMSProp(Graph graph, float learningRate, float decay, float momentum, float epsilon,
+  /**
+   * Creates an RMSPRrop Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param learningRate the learning rate
+   * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9.
+   * @param momentum the acceleration factor, default is 0.
+   * @param epsilon A small constant for numerical stability
+   * @param centered If true, gradients are normalized by the estimated variance of the
+   *     gradient; if false>, by the uncentered second moment. Setting this to 
+   *     true> may help with training, but is slightly more expensive in terms of computation
+   *     and memory. Defaults to false.
+   */
+  public RMSProp(
+      Graph graph,
+      float learningRate,
+      float decay,
+      float momentum,
+      float epsilon,
       boolean centered) {
     super(graph);
     this.learningRate = learningRate;
@@ -55,11 +115,45 @@ public RMSProp(Graph graph, float learningRate, float decay, float momentum, flo
     this.centered = centered;
   }
 
+  /**
+   * Creates an RMSPRrop Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name of this Optimizer. Defaults to "RMSProp".
+   * @param learningRate the learning rate
+   */
   public RMSProp(Graph graph, String name, float learningRate) {
-    this(graph, name, learningRate, 0.9f, 0.0f, 1e-10f, false);
+    this(
+        graph,
+        name,
+        learningRate,
+        DECAY_DEFAULT,
+        MOMENTUM_DEFAULT,
+        EPSILON_DEFAULT,
+        CENTERED_DEFAULT);
   }
 
-  public RMSProp(Graph graph, String name, float learningRate, float decay, float momentum, float epsilon,
+  /**
+   * Creates an RMSPRrop Optimizer
+   *
+   * @param graph the TensorFlow Graph
+   * @param name the name of this Optimizer. Defaults to "RMSProp".
+   * @param learningRate the learning rate
+   * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9.
+   * @param momentum The acceleration factor, default is 0.
+   * @param epsilon A small constant for numerical stability
+   * @param centered If true, gradients are normalized by the estimated variance of the
+   *     gradient; if false>, by the uncentered second moment. Setting this to 
+   *     true> may help with training, but is slightly more expensive in terms of computation
+   *     and memory. Defaults to false.
+   */
+  public RMSProp(
+      Graph graph,
+      String name,
+      float learningRate,
+      float decay,
+      float momentum,
+      float epsilon,
       boolean centered) {
     super(graph, name);
     this.learningRate = learningRate;
@@ -69,6 +163,7 @@ public RMSProp(Graph graph, String name, float learningRate, float decay, float
     this.centered = centered;
   }
 
+  /** {@inheritDoc} */
   @Override
   protected void createSlots(List> variables) {
     for (Output v : variables) {
@@ -76,34 +171,50 @@ protected void createSlots(List> variables) {
     }
   }
 
+
+  /**
+   * Creates the RMSProp Slots for Root Mean Squared (RMS),
+   * MOMENTUM, and Mean Gradient (MG)
+   *
+   * @param v the variable to install in the slot
+   * @param  the datatype of the variable.
+   */
   private  void createRMSPropSlot(Output v) {
-    Operand rmsInitializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.dataType()));
+    Operand rmsInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.dataType()));
     createSlot(v.asOutput(), RMS, rmsInitializer);
-    Operand momentumInitializer = tf
-        .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand momentumInitializer =
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
     createSlot(v.asOutput(), MOMENTUM, momentumInitializer);
     if (centered) {
-      Operand mgInitializer = tf
-          .fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+      Operand mgInitializer =
+          tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
       createSlot(v.asOutput(), MG, mgInitializer);
     }
   }
 
+  /** {@inheritDoc} */
   @Override
   protected  Op applyDense(Output gradient, Output variable) {
     Variable rmsSlot = getSlot(variable, RMS).get();
     Variable momentumSlot = getSlot(variable, MOMENTUM).get();
     if (centered) {
       Variable mgSlot = getSlot(variable, MG).get();
-      return tf.train.applyCenteredRmsProp(variable, mgSlot, rmsSlot, momentumSlot,
+      return tf.train.applyCenteredRmsProp(
+          variable,
+          mgSlot,
+          rmsSlot,
+          momentumSlot,
           tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
           tf.dtypes.cast(tf.constant(decay), gradient.dataType()),
           tf.dtypes.cast(tf.constant(momentum), gradient.dataType()),
           tf.dtypes.cast(tf.constant(epsilon), gradient.dataType()),
           gradient);
     }
-    return tf.train.applyRmsProp(variable, rmsSlot, momentumSlot,
+    return tf.train.applyRmsProp(
+        variable,
+        rmsSlot,
+        momentumSlot,
         tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
         tf.dtypes.cast(tf.constant(decay), gradient.dataType()),
         tf.dtypes.cast(tf.constant(momentum), gradient.dataType()),
@@ -111,17 +222,24 @@ protected  Op applyDense(Output gradient, Output variable
         gradient);
   }
 
+  /** {@inheritDoc} */
   @Override
   public String toString() {
-    return "RMSProp{" +
-        "learningRate=" + learningRate +
-        ", decay=" + decay +
-        ", momentum=" + momentum +
-        ", epsilon=" + epsilon +
-        ", centered=" + centered +
-        '}';
+    return "RMSProp{"
+        + "learningRate="
+        + learningRate
+        + ", decay="
+        + decay
+        + ", momentum="
+        + momentum
+        + ", epsilon="
+        + epsilon
+        + ", centered="
+        + centered
+        + '}';
   }
 
+  /** {@inheritDoc} */
   @Override
   public String getOptimizerName() {
     return "RMSProp";

From 5c30a72fa335f338727358b4299e4796a211403d Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Wed, 9 Sep 2020 16:17:16 -0400
Subject: [PATCH 30/33] Removed optimize classes from tensorflow-keras, moved
 optimizer test cases to framework. Created Tests for GradientDescent and
 Momentum

---
 .../framework}/optimizers/AdaDeltaTest.java   |  38 +-
 .../framework}/optimizers/AdaGradDATest.java  |   9 +-
 .../framework}/optimizers/AdaGradTest.java    |  11 +-
 .../framework}/optimizers/AdamTest.java       |  12 +-
 .../framework}/optimizers/AdamaxTest.java     |  23 +-
 .../framework}/optimizers/FtrlTest.java       |  22 +-
 .../optimizers/GradientDescentTest.java       | 100 +++++
 .../framework/optimizers/MomentumTest.java    |  22 +-
 .../framework}/optimizers/NadamTest.java      |  25 +-
 .../framework/optimizers/OptimizersTest.java  | 145 +++++++
 .../framework}/optimizers/RMSPropTest.java    |  13 +-
 .../framework}/utils/EagerTestSession.java    |  30 +-
 .../framework}/utils/GraphTestSession.java    |  35 +-
 .../org/tensorflow/framework}/utils/ND.java   |  38 +-
 .../framework}/utils/TestSession.java         |  30 +-
 .../tensorflow/keras/optimizers/AdaDelta.java | 200 ---------
 .../tensorflow/keras/optimizers/AdaGrad.java  | 167 --------
 .../keras/optimizers/AdaGradDA.java           | 196 ---------
 .../org/tensorflow/keras/optimizers/Adam.java | 182 --------
 .../tensorflow/keras/optimizers/Adamax.java   | 283 -------------
 .../tensorflow/keras/optimizers/Nadam.java    | 399 ------------------
 .../keras/optimizers/OptimizerInterface.java  |  61 ---
 .../keras/optimizers/Optimizers.java          | 125 ------
 .../tensorflow/keras/optimizers/RMSProp.java  | 201 ---------
 .../org/tensorflow/keras/optimizers/SGD.java  | 200 ---------
 25 files changed, 389 insertions(+), 2178 deletions(-)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/AdaDeltaTest.java (85%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/AdaGradDATest.java (93%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/AdaGradTest.java (94%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/AdamTest.java (96%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/AdamaxTest.java (91%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/FtrlTest.java (95%)
 create mode 100644 tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java
 rename tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java => tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java (92%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/NadamTest.java (90%)
 create mode 100644 tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/OptimizersTest.java
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/optimizers/RMSPropTest.java (96%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/utils/EagerTestSession.java (97%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/utils/GraphTestSession.java (98%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/utils/ND.java (96%)
 rename {tensorflow-keras/src/test/java/org/tensorflow/keras => tensorflow-framework/src/test/java/org/tensorflow/framework}/utils/TestSession.java (98%)
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaDelta.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGrad.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGradDA.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adam.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adamax.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Nadam.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/OptimizerInterface.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Optimizers.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/RMSProp.java
 delete mode 100644 tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/SGD.java

diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaDeltaTest.java
similarity index 85%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaDeltaTest.java
index 52de6b6b0e1..5c4ce542c65 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaDeltaTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaDeltaTest.java
@@ -12,11 +12,12 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
+import org.tensorflow.Graph;
 import org.tensorflow.framework.optimizers.Optimizer.GradAndVar;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
@@ -55,10 +56,10 @@ public void tearDown() {}
   @Test
   public void testConstructAdadeltaWithLR() {
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
-      AdaDelta opt = new AdaDelta(tf, 1.0F, 0.9F, 1.F);
-      AdaDelta opt2 = new AdaDelta(tf, 0.1F, 0.9F, 1.F);
-      AdaDelta opt3 = new AdaDelta(tf, 0.1F, 0.9F, 1e-8F);
+      Graph graph = session.getGraph();
+      AdaDelta opt = new AdaDelta(graph, 1.0F, 0.9F, 1.F);
+      AdaDelta opt2 = new AdaDelta(graph, 0.1F, 0.9F, 1.F);
+      AdaDelta opt3 = new AdaDelta(graph, 0.1F, 0.9F, 1e-8F);
       String format = "AdaDelta{learningRate=%s, rho=%s, epsilon=%s}";
       String optExpected = String.format(format, 1.0F, 0.9F, 1.F);
       String opt2Expected = String.format(format, 0.1F, 0.9F, 1.F);
@@ -74,28 +75,6 @@ public void testConstructAdadeltaWithLR() {
     }
   }
 
-  @Test
-  public void testConstructOptions() {
-    try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
-      AdaDelta.Options options =
-          AdaDelta.Options.builder()
-              .name("myAdaDelta")
-              .learningRate(1.0F)
-              .rho(0.9F)
-              .epsilon(1.F)
-              .build();
-      AdaDelta opt = new AdaDelta(tf, options);
-
-      String format = "AdaDelta{learningRate=%s, rho=%s, epsilon=%s}";
-      String optExpected = String.format(format, 1.0F, 0.9F, 1.F);
-
-      String optString = opt.toString();
-
-      assertEquals(optExpected, optString);
-    }
-  }
-
   @Test
   public void testBasic() {
     int numUpdates = 4; // # number of ADADELTA steps to perform
@@ -105,6 +84,7 @@ public void testBasic() {
       for (float lr : lrs) {
         try (TestSession session = TestSession.createTestSession(tfMode)) {
           Ops tf = session.getTF();
+          Graph graph = session.getGraph();
           float[] var0Init = {1.0F, 2.0F};
           float[] var1Init = {3.0F, 4.0F};
           float[] fgrads = {grad, grad};
@@ -128,7 +108,7 @@ public void testBasic() {
           gradsAndVars.add(new GradAndVar<>(cgrads.asOutput(), var1.asOutput()));
 
           /* get the Optimizer */
-          AdaDelta adaDelta = new AdaDelta(tf, lr, rho, epsilon);
+          AdaDelta adaDelta = new AdaDelta(graph, lr, rho, epsilon);
 
           /*apply gradients */
           Op adadeltaUpdate = adaDelta.applyGradients(gradsAndVars, "AdaDeltaTest");
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
similarity index 93%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
index 7275e9f8113..e1a12fb00fe 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradDATest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
@@ -12,11 +12,11 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.Graph;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
@@ -56,6 +56,7 @@ public void testBasic() {
     float[] grads1Init = {0.01F, 0.02F};
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -75,7 +76,7 @@ public void testBasic() {
 
       float learningRate = 3.0F;
 
-      AdaGrad instance = new AdaGrad(tf, learningRate);
+      AdaGrad instance = new AdaGrad(graph, learningRate);
 
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
similarity index 94%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
index d407209b87a..efbdd7be585 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdaGradTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
@@ -12,12 +12,12 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.ND;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.Graph;
+import org.tensorflow.framework.utils.ND;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
@@ -72,6 +72,7 @@ public void testBasic() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -86,7 +87,7 @@ public void testBasic() {
 
       float learningRate = 3.0F;
 
-      AdaGrad instance = new AdaGrad(tf, learningRate);
+      AdaGrad instance = new AdaGrad(graph, learningRate);
 
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
similarity index 96%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
index 82a47afbbbb..dbcc7c0dae2 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
@@ -12,13 +12,13 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
+import org.tensorflow.Graph;
 import org.tensorflow.Tensor;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.ND;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.framework.utils.ND;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
@@ -70,7 +70,7 @@ public void testBasic() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
-
+      Graph graph = session.getGraph();
       session.setEpsilon(epsilon1);
 
       Shape shape0 = Shape.of(var0Init.length);
@@ -97,7 +97,7 @@ public void testBasic() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      Adam instance = new Adam(tf, learningRate);
+      Adam instance = new Adam(graph, learningRate);
 
       Op update = instance.applyGradients(gradsAndVars, "AdamTest");
 
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
similarity index 91%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
index 3376d65aab4..1b12a2f76a1 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/AdamaxTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
@@ -12,13 +12,13 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
+import org.tensorflow.Graph;
 import org.tensorflow.Tensor;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.ND;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.framework.utils.ND;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
@@ -34,7 +34,7 @@
 import java.util.List;
 
 import static org.junit.jupiter.api.Assertions.assertEquals;
-import static org.tensorflow.keras.optimizers.Adamax.*;
+import static org.tensorflow.framework.optimizers.Adamax.*;
 
 /** Test cases for Adamax Optimizer */
 public class AdamaxTest {
@@ -62,8 +62,8 @@ public void tearDown() {}
   @Test
   public void testGetOptimizerName() {
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
-      Adamax instance = new Adamax(tf);
+      Graph graph = session.getGraph();
+      Adamax instance = new Adamax(graph);
       String expResult = "Adamax";
       String result = instance.getOptimizerName();
       assertEquals(expResult, result);
@@ -95,6 +95,7 @@ public void testBasic() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -111,11 +112,11 @@ public void testBasic() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      Adamax instance = new Adamax(tf);
+      Adamax instance = new Adamax(graph);
       /* build the GradsAnvVars */
-      List> gradsAndVars = new ArrayList<>();
-      gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
-      gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
+      List> gradsAndVars = new ArrayList<>();
+      gradsAndVars.add(new GradAndVar<>(grads0.asOutput(), var0.asOutput()));
+      gradsAndVars.add(new GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
       Op update = instance.applyGradients(gradsAndVars, "AdamTest");
 
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/FtrlTest.java
similarity index 95%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/FtrlTest.java
index cda32704506..597f8e52bcd 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/FtrlTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/FtrlTest.java
@@ -12,11 +12,11 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.Graph;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
@@ -53,8 +53,8 @@ public void tearDown() {}
   @Test
   public void testGetOptimizerName() {
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
-      Ftrl instance = new Ftrl(tf);
+      Graph graph = session.getGraph();
+      Ftrl instance = new Ftrl(graph);
       String expResult = "Ftrl";
       String result = instance.getOptimizerName();
       assertEquals(expResult, result);
@@ -72,6 +72,7 @@ public void testFtrlWithL1L2L2Shrinkage() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -88,7 +89,7 @@ public void testFtrlWithL1L2L2Shrinkage() {
 
       Ftrl instance =
           new Ftrl(
-              tf,
+              graph,
               learningRate,
               -0.5F, // learningRatePower
               0.1F, // initialAccumulatorValue
@@ -136,6 +137,7 @@ public void testFtrlWithL1() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -152,7 +154,7 @@ public void testFtrlWithL1() {
 
       Ftrl instance =
           new Ftrl(
-              tf,
+              graph,
               learningRate,
               Ftrl.LEARNING_RATE_POWER_DEFAULT, // learningRatePower
               0.1F, // initialAccumulatorValue
@@ -201,6 +203,7 @@ public void testFtrlWithL1L2() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -217,7 +220,7 @@ public void testFtrlWithL1L2() {
 
       Ftrl instance =
           new Ftrl(
-              tf,
+              graph,
               learningRate,
               Ftrl.LEARNING_RATE_POWER_DEFAULT, // learningRatePower
               0.1F, // initialAccumulatorValue
@@ -266,6 +269,7 @@ public void doTestFtrlwithoutRegularization() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -280,7 +284,7 @@ public void doTestFtrlwithoutRegularization() {
 
       float learningRate = 3.0F;
 
-      Ftrl instance = new Ftrl(tf, learningRate);
+      Ftrl instance = new Ftrl(graph, learningRate);
 
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java
new file mode 100644
index 00000000000..4362c54d815
--- /dev/null
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java
@@ -0,0 +1,100 @@
+package org.tensorflow.framework.optimizers;
+
+import org.junit.jupiter.api.*;
+import org.tensorflow.Graph;
+import org.tensorflow.framework.utils.TestSession;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Op;
+import org.tensorflow.op.Ops;
+import org.tensorflow.op.core.Assign;
+import org.tensorflow.op.core.Constant;
+import org.tensorflow.op.core.Variable;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.family.TType;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+/** Test cases for GradientDescent Optimizer */
+public class GradientDescentTest {
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
+
+  public GradientDescentTest() {}
+
+  @BeforeAll
+  public static void setUpClass() {}
+
+  @AfterAll
+  public static void tearDownClass() {}
+
+  @BeforeEach
+  public void setUp() {}
+
+  @AfterEach
+  public void tearDown() {}
+
+  /** Test of getOptimizerName method, of class Nadam. */
+  @Test
+  public void testGetOptimizerName() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      GradientDescent instance = new GradientDescent(graph);
+      String expResult = "GradientDescent";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  @Test
+  public void testBasic() {
+    float[] var0Init = {1.0F, 2.0F};
+    float[] var1Init = {3.0F, 4.0F};
+    float[] grads0Init = {0.1F, 0.1F};
+    float[] grads1Init = {0.01F, 0.01F};
+    float learningRate = 3.0F;
+
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Ops tf = session.getTF();
+      Graph graph = session.getGraph();
+
+      Shape shape0 = Shape.of(var0Init.length);
+      Shape shape1 = Shape.of(var1Init.length);
+      Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
+      Variable var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+
+      Assign var0Initializer = tf.assign(var0, tf.constant(var0Init));
+      Assign var1Initializer = tf.assign(var1, tf.constant(var1Init));
+
+      Constant grads0 = tf.constant(grads0Init);
+      Constant grads1 = tf.constant(grads1Init);
+
+      /* build the GradsAnvVars */
+      List> gradsAndVars = new ArrayList<>();
+      gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
+      gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
+
+      GradientDescent instance = new GradientDescent(graph, learningRate);
+      Op update = instance.applyGradients(gradsAndVars, "SGDTest");
+
+      /* initialize the local variables */
+      session.run(var0Initializer);
+      session.run(var1Initializer);
+
+      /* initialize the accumulators */
+      session.run(tf.init());
+
+      /* make sure the variables were initialized properly */
+      session.evaluate(var0Init, var0);
+      session.evaluate(var1Init, var1);
+
+      session.run(update); // 1 step
+
+      float[] expectedVar0 = {1.0F - 3.0F * 0.1F, 2.0F - 3.0F * 0.1F};
+      float[] expectedVar1 = {3.0F - 3.0F * 0.01F, 4.0F - 3.0F * 0.01F};
+      session.evaluate(expectedVar0, var0);
+      session.evaluate(expectedVar1, var1);
+    }
+  }
+}
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java
similarity index 92%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java
index a8e363b4332..bcfff97773d 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/SGDTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java
@@ -12,11 +12,11 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.Graph;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
@@ -33,11 +33,11 @@
 import static org.tensorflow.framework.optimizers.Momentum.MOMENTUM;
 
 /** Test cases for SGD Optimizer */
-public class SGDTest {
+public class MomentumTest {
 
   private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
 
-  public SGDTest() {}
+  public MomentumTest() {}
 
   @BeforeAll
   public static void setUpClass() {}
@@ -55,9 +55,9 @@ public void tearDown() {}
   @Test
   public void testGetOptimizerName() {
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
-      SGD instance = new SGD(tf);
-      String expResult = "SGD";
+      Graph graph = session.getGraph();
+      Momentum instance = new Momentum(graph);
+      String expResult = "Momentum";
       String result = instance.getOptimizerName();
       assertEquals(expResult, result);
     }
@@ -73,6 +73,7 @@ public void testBasic() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -90,7 +91,7 @@ public void testBasic() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      SGD instance = new SGD(tf, learningRate);
+      Momentum instance = new Momentum(graph, learningRate);
       Op update = instance.applyGradients(gradsAndVars, "SGDTest");
 
       /* initialize the local variables */
@@ -125,6 +126,7 @@ public void testMomentum() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -142,7 +144,7 @@ public void testMomentum() {
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      SGD instance = new SGD(tf, learningRate, momentum);
+      Momentum instance = new Momentum(graph, learningRate, momentum);
       Op update = instance.applyGradients(gradsAndVars, "SGDTest");
 
       Variable momentumSlot0 = instance.getSlot(var0.asOutput(), MOMENTUM).get();
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/NadamTest.java
similarity index 90%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/NadamTest.java
index d720460b2f2..a583d74246b 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/NadamTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/NadamTest.java
@@ -12,13 +12,13 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
+import org.tensorflow.Graph;
 import org.tensorflow.Tensor;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.ND;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.framework.utils.ND;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
@@ -34,8 +34,6 @@
 import java.util.List;
 
 import static org.junit.jupiter.api.Assertions.assertEquals;
-import static org.tensorflow.keras.optimizers.Nadam.FIRST_MOMENT;
-import static org.tensorflow.keras.optimizers.Nadam.SECOND_MOMENT;
 
 /** Test cases for Nadam Optimizer */
 public class NadamTest {
@@ -65,8 +63,8 @@ public void tearDown() {}
   @Test
   public void testGetOptimizerName() {
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
-      Nadam instance = new Nadam(tf);
+      Graph graph = session.getGraph();
+      Nadam instance = new Nadam(graph);
       String expResult = "Nadam";
       String result = instance.getOptimizerName();
       assertEquals(expResult, result);
@@ -100,6 +98,7 @@ public void testBasic() {
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
       Ops tf = session.getTF();
+      Graph graph = session.getGraph();
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
@@ -112,7 +111,7 @@ public void testBasic() {
       Constant grads0 = tf.constant(grads0Init);
       Constant grads1 = tf.constant(grads1Init);
 
-      Nadam instance = new Nadam(tf);
+      Nadam instance = new Nadam(graph);
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
@@ -124,16 +123,16 @@ public void testBasic() {
       Variable[] firstMomentSlots = new Variable[2];
       Variable[] secondMomentSlots = new Variable[2];
 
-      firstMomentSlots[0] = instance.getSlot(var0.asOutput(), FIRST_MOMENT).get();
+      firstMomentSlots[0] = instance.getSlot(var0.asOutput(), Nadam.FIRST_MOMENT).get();
       assertEquals(firstMomentSlots[0].asOutput().shape(), var0.asOutput().shape());
 
-      secondMomentSlots[0] = instance.getSlot(var0.asOutput(), SECOND_MOMENT).get();
+      secondMomentSlots[0] = instance.getSlot(var0.asOutput(), Nadam.SECOND_MOMENT).get();
       assertEquals(secondMomentSlots[0].asOutput().shape(), var0.asOutput().shape());
 
-      firstMomentSlots[1] = instance.getSlot(var1.asOutput(), FIRST_MOMENT).get();
+      firstMomentSlots[1] = instance.getSlot(var1.asOutput(), Nadam.FIRST_MOMENT).get();
       assertEquals(firstMomentSlots[1].asOutput().shape(), var1.asOutput().shape());
 
-      secondMomentSlots[1] = instance.getSlot(var1.asOutput(), SECOND_MOMENT).get();
+      secondMomentSlots[1] = instance.getSlot(var1.asOutput(), Nadam.SECOND_MOMENT).get();
       assertEquals(secondMomentSlots[1].asOutput().shape(), var1.asOutput().shape());
 
       /* initialize the local variables */
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/OptimizersTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/OptimizersTest.java
new file mode 100644
index 00000000000..78b56c8289e
--- /dev/null
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/OptimizersTest.java
@@ -0,0 +1,145 @@
+package org.tensorflow.framework.optimizers;
+
+import org.junit.jupiter.api.*;
+import org.tensorflow.Graph;
+import org.tensorflow.framework.utils.TestSession;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+public class OptimizersTest {
+  private final TestSession.Mode tfMode = TestSession.Mode.GRAPH;
+
+  public OptimizersTest() {}
+
+  @BeforeAll
+  public static void setUpClass() {}
+
+  @AfterAll
+  public static void tearDownClass() {}
+
+  @BeforeEach
+  public void setUp() {}
+
+  @AfterEach
+  public void tearDown() {}
+
+  /** Test ADADELTA enum */
+  @Test
+  public void testADADELTA() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.ADADELTA.createOptimizer(graph);
+      String expResult = "Adadelta";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test ADAGRAD enum */
+  @Test
+  public void testADAGRAD() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.ADAGRAD.createOptimizer(graph);
+      String expResult = "Adagrad";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test ADAGRAD_DA enum */
+  @Test
+  public void testADAGRAD_DA() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.ADAGRAD_DA.createOptimizer(graph);
+      String expResult = "adagrad-da";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test ADAM enum */
+  @Test
+  public void testADAM() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.ADAM.createOptimizer(graph);
+      String expResult = "Adam";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test ADAMAX enum */
+  @Test
+  public void testADAMAX() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.ADAMAX.createOptimizer(graph);
+      String expResult = "Adamax";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test FTRL enum */
+  @Test
+  public void testFTRL() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.FTRL.createOptimizer(graph);
+      String expResult = "Ftrl";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test NADAM enum */
+  @Test
+  public void testNADAM() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.NADAM.createOptimizer(graph);
+      String expResult = "Nadam";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test RMSPROP enum */
+  @Test
+  public void testRMSPROP() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.RMSPROP.createOptimizer(graph);
+      String expResult = "RMSProp";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test MOMENTUM enum */
+  @Test
+  public void testMOMENTUM() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.MOMENTUM.createOptimizer(graph);
+      String expResult = "Momentum";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+
+  /** Test GRADIENT_DESCENT enum */
+  @Test
+  public void testGRADIENT_DESCENT() {
+    try (TestSession session = TestSession.createTestSession(tfMode)) {
+      Graph graph = session.getGraph();
+      Optimizer instance = Optimizers.GRADIENT_DESCENT.createOptimizer(graph);
+      String expResult = "GradientDescent";
+      String result = instance.getOptimizerName();
+      assertEquals(expResult, result);
+    }
+  }
+}
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/RMSPropTest.java
similarity index 96%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/RMSPropTest.java
index 078288ed1e7..202fb21ef68 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/optimizers/RMSPropTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/RMSPropTest.java
@@ -12,12 +12,12 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.optimizers;
+package org.tensorflow.framework.optimizers;
 
 import org.junit.jupiter.api.*;
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.keras.utils.ND;
-import org.tensorflow.keras.utils.TestSession;
+import org.tensorflow.Graph;
+import org.tensorflow.framework.utils.ND;
+import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
@@ -73,6 +73,7 @@ public void testDense() {
     for (Object[] testParamValue : TestParamValues) {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
+        Graph graph = session.getGraph();
         session.setEpsilon(1e-2f);
         float[] var0Init = {1.0F, 2.0F};
         float[] var1Init = {3.0F, 4.0F};
@@ -102,10 +103,10 @@ public void testDense() {
         float epsilon = (float) testParamValue[3];
         boolean centered = (boolean) testParamValue[4];
 
-        RMSProp instance = new RMSProp(tf, learningRate, decay, momentum, epsilon, centered);
+        RMSProp instance = new RMSProp(graph, learningRate, decay, momentum, epsilon, centered);
 
         /* build the GradsAnvVars */
-        List> gradsAndVars = new ArrayList<>();
+        List> gradsAndVars = new ArrayList<>();
         gradsAndVars.add(new GradAndVar<>(grads0.asOutput(), var0.asOutput()));
         gradsAndVars.add(new GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
similarity index 97%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
index 6b7ebf9e2f2..c52168e1f11 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/EagerTestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
@@ -12,32 +12,23 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.utils;
+package org.tensorflow.framework.utils;
 
-import java.io.PrintWriter;
-import java.util.concurrent.atomic.AtomicInteger;
-import java.util.concurrent.atomic.AtomicLong;
-import java.util.function.Predicate;
-import static org.junit.jupiter.api.Assertions.assertEquals;
-import static org.junit.jupiter.api.Assertions.assertTrue;
-import static org.junit.jupiter.api.Assertions.fail;
-import org.tensorflow.DataType;
-import org.tensorflow.EagerSession;
-import org.tensorflow.Operand;
-import org.tensorflow.Output;
-import org.tensorflow.Session;
+import org.tensorflow.*;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Ops;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TString;
+import org.tensorflow.types.*;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
+import java.io.PrintWriter;
+import java.util.concurrent.atomic.AtomicInteger;
+import java.util.concurrent.atomic.AtomicLong;
+import java.util.function.Predicate;
+
+import static org.junit.jupiter.api.Assertions.*;
+
 /** Eaager Mode Test Session */
 public class EagerTestSession extends TestSession {
 
@@ -58,6 +49,7 @@ public Ops getTF() {
 
   /**
    * Get the TensorFlow EagerSession instance
+   *
    * @return the TensorFlow EagerSession instance
    */
   public EagerSession getSession() {
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/GraphTestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
similarity index 98%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/utils/GraphTestSession.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
index 1a22289f4bf..3231b0f50cd 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/GraphTestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
@@ -12,35 +12,24 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.utils;
+package org.tensorflow.framework.utils;
 
-import java.io.PrintWriter;
-import java.util.concurrent.atomic.AtomicInteger;
-import java.util.concurrent.atomic.AtomicLong;
-import java.util.function.Predicate;
-import static org.junit.jupiter.api.Assertions.assertEquals;
-import static org.junit.jupiter.api.Assertions.assertTrue;
-import static org.junit.jupiter.api.Assertions.fail;
-import org.tensorflow.DataType;
-import org.tensorflow.EagerSession;
-import org.tensorflow.Graph;
-import org.tensorflow.Operand;
-import org.tensorflow.Output;
-import org.tensorflow.Session;
-import org.tensorflow.Tensor;
+import org.tensorflow.*;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TString;
+import org.tensorflow.types.*;
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
+import java.io.PrintWriter;
+import java.util.concurrent.atomic.AtomicInteger;
+import java.util.concurrent.atomic.AtomicLong;
+import java.util.function.Predicate;
+
+import static org.junit.jupiter.api.Assertions.*;
+
 /** Graph Mode Test Session */
 public class GraphTestSession extends TestSession {
 
@@ -66,9 +55,9 @@ public Graph getGraph() {
     return graph;
   }
 
-
   /**
-   *  Get the TensorFlow Session instance
+   * Get the TensorFlow Session instance
+   *
    * @return the TensorFlow Session instance
    */
   public Session getSession() {
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/ND.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/ND.java
similarity index 96%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/utils/ND.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/utils/ND.java
index 2855af5af25..0503a41dfc2 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/ND.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/ND.java
@@ -12,18 +12,20 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.utils;
+package org.tensorflow.framework.utils;
 
-import java.util.Arrays;
-import java.util.concurrent.atomic.AtomicBoolean;
-import java.util.concurrent.atomic.AtomicInteger;
-import java.util.concurrent.atomic.AtomicReference;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
 
+import java.util.Arrays;
+import java.util.concurrent.atomic.AtomicBoolean;
+import java.util.concurrent.atomic.AtomicInteger;
+import java.util.concurrent.atomic.AtomicReference;
+
 // TODO used in the Callbacks, this should be a part of NDArray?
+
 /** NDArray math Utilities */
 public class ND {
 
@@ -126,7 +128,7 @@ public static FloatNdArray square(FloatNdArray a) {
    * @return the resulting array from the add operation
    */
   public static FloatNdArray add(FloatNdArray a, FloatNdArray b) {
-    if(a.shape().size() != b.shape().size())
+    if (a.shape().size() != b.shape().size())
       throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
@@ -176,7 +178,7 @@ public static FloatNdArray add(float scalar, FloatNdArray a) {
    * @return the resulting array from the subtraction operation
    */
   public static FloatNdArray sub(FloatNdArray a, FloatNdArray b) {
-    if(a.shape().size() != b.shape().size())
+    if (a.shape().size() != b.shape().size())
       throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
@@ -232,9 +234,10 @@ public static FloatNdArray sub(float scalar, FloatNdArray a) {
    * @return the resulting array from the muliply operation
    */
   public static FloatNdArray mul(FloatNdArray a, FloatNdArray b) {
-    if(!a.shape().equals(b.shape()))
-        throw new IllegalArgumentException(String.format(
-            "ValueError: operands do not have same shapes %s %s ", a.shape(), b.shape()));
+    if (!a.shape().equals(b.shape()))
+      throw new IllegalArgumentException(
+          String.format(
+              "ValueError: operands do not have same shapes %s %s ", a.shape(), b.shape()));
     boolean sameSize = a.shape().size() == b.shape().size();
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
@@ -289,7 +292,7 @@ public static FloatNdArray mul(float scalar, FloatNdArray a) {
    * @return the resulting array from the Divide operation
    */
   public static FloatNdArray div(FloatNdArray a, FloatNdArray b) {
-    if(a.shape().size() != b.shape().size())
+    if (a.shape().size() != b.shape().size())
       throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
@@ -309,8 +312,7 @@ public static FloatNdArray div(FloatNdArray a, FloatNdArray b) {
    * @return the resulting array from the Divide operation
    */
   public static FloatNdArray div(FloatNdArray a, float scalar) {
-    if(scalar == 0)
-      throw new IllegalArgumentException("Cannot divide by zero");
+    if (scalar == 0) throw new IllegalArgumentException("Cannot divide by zero");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
     a.elements(nDims - 1)
@@ -348,7 +350,7 @@ public static FloatNdArray div(float scalar, FloatNdArray a) {
    * @return the array result of the power operation
    */
   public static FloatNdArray pow(FloatNdArray a, FloatNdArray b) {
-    if(a.shape().size() != b.shape().size())
+    if (a.shape().size() != b.shape().size())
       throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
@@ -444,10 +446,10 @@ public static float min(FloatNdArray a) {
    * @param a the first array
    * @param a the second array
    * @return the resulting array with the maximum values between each element of the arrays.
-   * @throws java.lang.AssertionError if the two arrays are not the same size.
+   * @throws AssertionError if the two arrays are not the same size.
    */
   public static FloatNdArray max(FloatNdArray a, FloatNdArray b) {
-    if(a.shape().size() != b.shape().size())
+    if (a.shape().size() != b.shape().size())
       throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
@@ -496,10 +498,10 @@ public static FloatNdArray max(float scalar, FloatNdArray a) {
    * @param a the first array
    * @param a the second array
    * @return the resulting array with the minimum values between each element of the arrays.
-   * @throws java.lang.AssertionError if the two arrays are not the same size.
+   * @throws AssertionError if the two arrays are not the same size.
    */
   public static FloatNdArray min(FloatNdArray a, FloatNdArray b) {
-    if(a.shape().size() != b.shape().size())
+    if (a.shape().size() != b.shape().size())
       throw new IllegalArgumentException("a and b muse have the same number of dimensions");
     FloatNdArray result = NdArrays.ofFloats(a.shape());
     int nDims = a.shape().numDimensions();
diff --git a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/TestSession.java
similarity index 98%
rename from tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TestSession.java
rename to tensorflow-framework/src/test/java/org/tensorflow/framework/utils/TestSession.java
index 1e5393aa2af..3758c832db5 100644
--- a/tensorflow-keras/src/test/java/org/tensorflow/keras/utils/TestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/TestSession.java
@@ -12,18 +12,9 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 =======================================================================*/
-package org.tensorflow.keras.utils;
+package org.tensorflow.framework.utils;
 
-import java.io.OutputStream;
-import java.io.OutputStreamWriter;
-import java.io.PrintWriter;
-import java.io.Writer;
-import java.util.function.Predicate;
-import static org.junit.jupiter.api.Assertions.assertTrue;
-import org.tensorflow.EagerSession;
-import org.tensorflow.Operand;
-import org.tensorflow.Output;
-import org.tensorflow.Session;
+import org.tensorflow.*;
 import org.tensorflow.ndarray.FloatNdArray;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
@@ -32,6 +23,14 @@
 import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
+import java.io.OutputStream;
+import java.io.OutputStreamWriter;
+import java.io.PrintWriter;
+import java.io.Writer;
+import java.util.function.Predicate;
+
+import static org.junit.jupiter.api.Assertions.assertTrue;
+
 /** Base class for Test Session */
 public abstract class TestSession implements AutoCloseable {
 
@@ -86,6 +85,15 @@ public void run(Op op) {
     // empty
   }
 
+  /**
+   * Get the Graph
+   *
+   * @return the graph if in Graph Mode, otherwise null.
+   */
+  public Graph getGraph() {
+    return null;
+  }
+
   /**
    * Evaluate the input against the expected value
    *
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaDelta.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaDelta.java
deleted file mode 100644
index b0a9dcf7d68..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaDelta.java
+++ /dev/null
@@ -1,200 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Optional;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-
-/**
- * AdaDelta Optimizer that implements the AdaDelta algorithm. Keras wrapper around the Tensorflow
- * Framework optimizer. Adadelta optimization is a stochastic gradient descent method that is based
- * on adaptive learning rate per dimension to address two drawbacks: 1) the continual decay of
- * learning rates throughout training 2) the need for a manually selected global learning rate
- *
- * 
    Two accumulation steps are required: 1) the accumulation of gradients squared, 2) the
- * accumulation of updates squared.
- *
- */
-public class AdaDelta extends org.tensorflow.framework.optimizers.AdaDelta
-    implements OptimizerInterface {
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String RHO_RATE_KEY = "rho";
-  public static final String EPSILON_KEY = "epsilon";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.001F;
-  public static final float RHO_DEFAULT = 0.95F;
-  public static final float EPSILON_DEFAULT = 1e-7F;
-
-  private Map config = new HashMap<>();
-  private float learningRate;
-
-  private List initializers = new ArrayList<>();
-
-
-  /**
-   * Create an Adadelta optimizer with default name="Adadelta", learning_rate=0.001F, rho=0.95F, and
-   * epsilon=1e-7F
-   *
-   * @param tf the tensorflow Ops
-   */
-  public AdaDelta(Ops tf) {
-    this(tf, LEARNING_RATE_DEFAULT, RHO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adadelta optimizer with default learning_rate=0.001F, rho=0.95F, and epsilon=1e-7F
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adadelta"
-   */
-  public AdaDelta(Ops tf, String name) {
-    this(tf, name, LEARNING_RATE_DEFAULT, RHO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adadelta optimizer with default name="Adadelta", rho=0.95F, and epsilon=1e-7F
-   *
-   * @param tf the tensorflow Ops
-   * @param learningRate The learning rate
-   */
-  public AdaDelta(Ops tf, float learningRate) {
-    this(tf, learningRate, RHO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adadelta optimizer with default rho=0.95F, and epsilon=1e-7F
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adadelta"
-   * @param learningRate The learning rate
-   */
-  public AdaDelta(Ops tf, String name, float learningRate) {
-    this(tf, name, learningRate, RHO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adadelta optimizer with default name="Adadelta",
-   *
-   * @param tf the tensorflow Ops
-   * @param learningRate The learning rate
-   * @param rho The decay rate.
-   * @param epsilon A constant epsilon used to better conditioning the grad update.
-   */
-  public AdaDelta(Ops tf, float learningRate, float rho, float epsilon) {
-    super(assertGraph(tf), learningRate, rho, epsilon);
-    initConfig(learningRate, rho, epsilon);
-  }
-
-  /**
-   * Create an Adadelta optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adadelta"
-   * @param learningRate The learning rate
-   * @param rho The decay rate.
-   * @param epsilon A constant epsilon used to better conditioning the grad update.
-   */
-  public AdaDelta(Ops tf, String name, float learningRate, float rho, float epsilon) {
-    super(assertGraph(tf), name, learningRate, rho, epsilon);
-    initConfig(learningRate, rho, epsilon);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected Optional prepare(String name) {
-    switch (initializers.size()) {
-      case 0:
-        return Optional.empty();
-      case 1:
-        return Optional.of(initializers.get(0));
-      default:
-        return Optional.of( tf.withSubScope(name).withControlDependencies(initializers).noOp());
-    }
-  }
-
-  /**
-   * Create an Adam Optimizer from a config object
-   *
-   * @param tf the tensorflow Ops
-   * @param config a config object to initialize, he config object has keys for "name",
-   *     "learning_rate", "rho" and "epsilon". If a key is missing the default value is used.
-   */
-  public static AdaDelta fromConfig(Ops tf, Map config) {
-    return create(tf, config);
-  }
-
-  /**
-   * Create an Adadelta optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param config a config object to initialize, the config
-   *     object has keys for "name", "learning_rate", "rho" and "epsilon". If a key is missing the
-   *     default value is used.
-   */
-  public static AdaDelta create(Ops tf, Map config) {
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float rho = (float) config.getOrDefault(RHO_RATE_KEY, RHO_DEFAULT);
-    float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT);
-    if (name == null) // doe this to get the default name
-    {
-      return new AdaDelta(tf, learningRate, rho, epsilon);
-    } else {
-      return new AdaDelta(tf, name, learningRate, rho, epsilon);
-    }
-  }
-
-  /**
-   * Initialize the configuration based on which constructor is called.
-   *
-   * @param learningRate The learning rate
-   * @param rho The decay rate.
-   * @param epsilon A constant epsilon used to better conditioning the grad update.
-   */
-  private void initConfig(float learningRate, float rho, float epsilon) {
-    this.learningRate = learningRate;
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(RHO_RATE_KEY, rho);
-    config.put(EPSILON_KEY, epsilon);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-
-
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGrad.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGrad.java
deleted file mode 100644
index 039cf4a0d82..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGrad.java
+++ /dev/null
@@ -1,167 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.Map;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.op.Ops;
-
-/**
- * AdaGrad Optimizer that implements the AdaGrad algorithm. Adagrad is an optimizer with
- * parameter-specific learning rates, which are adapted relative to how frequently a parameter gets
- * updated during training. The more updates a parameter receives, the smaller the updates.
- */
-public class AdaGrad extends org.tensorflow.framework.optimizers.AdaGrad
-    implements OptimizerInterface {
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String INITIAL_ACCUM_KEY = "accumulator";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.001F;
-  public static final float INITIAL_ACCUM__DEFAULT = 0.1f;
-
-  private Map config = new HashMap<>();
-  private float learningRate;
-
-  /**
-   * Create an AdaGrad Optimizer with name="Adagrad", learningRate=0.001F, and initial
-   * accumulator=0.1
-   *
-   * @param tf the tensorflow Ops
-   */
-  public AdaGrad(Ops tf) {
-    this(tf, LEARNING_RATE_DEFAULT, INITIAL_ACCUM__DEFAULT);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer with learningRate=0.001F, and initial accumulator=0.1
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adagrad"
-   */
-  public AdaGrad(Ops tf, String name) {
-    this(tf, name, LEARNING_RATE_DEFAULT, INITIAL_ACCUM__DEFAULT);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer with initial accumulator=0.1
-   *
-   * @param tf the tensorflow Ops
-   * @param learningRate The learning rate. Defaults to 0.001.
-   */
-  public AdaGrad(Ops tf, float learningRate) {
-    this(tf, learningRate, INITIAL_ACCUM__DEFAULT);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adagrad"
-   * @param learningRate The learning rate. Defaults to 0.01.
-   */
-  public AdaGrad(Ops tf, String name, float learningRate) {
-    this(tf, name, learningRate, INITIAL_ACCUM__DEFAULT);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param learningRate The learning rate
-   * @param initialAccumulatorValue initial accumulator value
-   */
-  public AdaGrad(Ops tf, float learningRate, float initialAccumulatorValue) {
-    super(assertGraph(tf), learningRate, initialAccumulatorValue);
-    initConfig(learningRate, initialAccumulatorValue);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adagrad"
-   * @param learningRate The learning rate
-   * @param initialAccumulatorValue initial accumulator value, must be >= 0.
-   */
-  public AdaGrad(Ops tf, String name, float learningRate, float initialAccumulatorValue) {
-    super(assertGraph(tf), name, learningRate, initialAccumulatorValue);
-    if(initialAccumulatorValue < 0.0F)
-        throw new IllegalArgumentException( "initial_accumulator_value must be non-negative: " + initialAccumulatorValue);
-    initConfig(learningRate, initialAccumulatorValue);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer from a config object
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize, , the config object has keys for "name",
-   *     "learning_rate" and "accumulator". If a key is missing the default value is used.
-   */
-  public static AdaGrad fromConfig(Ops tf, Map config) {
-    return create(tf, config);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer from a config object
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize, the config object has keys for "name",
-   *     "learning_rate" and "accumulator". If a key is missing the default value is used.
-   */
-  public static AdaGrad create(Ops tf, Map config) {
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float initialAccumulatorValue =
-        (float) config.getOrDefault(INITIAL_ACCUM_KEY, INITIAL_ACCUM__DEFAULT);
-    if (name != null) {
-      return new AdaGrad(tf, name, learningRate, initialAccumulatorValue);
-    } else {
-      return new AdaGrad(tf, learningRate, initialAccumulatorValue);
-    }
-  }
-
-  /**
-   * Initialize the configuration
-   *
-   * @param learningRate the learning rate
-   * @param initialAccumulatorValue the initial Accumulator value
-   */
-  private void initConfig(float learningRate, float initialAccumulatorValue) {
-    this.learningRate = learningRate;
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(INITIAL_ACCUM_KEY, initialAccumulatorValue);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGradDA.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGradDA.java
deleted file mode 100644
index 2f15024bf56..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/AdaGradDA.java
+++ /dev/null
@@ -1,196 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.Map;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.op.Ops;
-
-/** Optimizer that implements the Adagrad Dual-Averaging algorithm. */
-public class AdaGradDA extends org.tensorflow.framework.optimizers.AdaGradDA
-    implements OptimizerInterface {
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String INITIAL_ACCUM_KEY = "accumulator";
-  public static final String L1STRENGTH_KEY = "l1Strength";
-  public static final String L2STRENGTH_KEY = "l2Strength";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.001F; // arbitray number
-  public static final float INITIAL_ACCUM__DEFAULT = 0.1f;
-  public static final float L1STRENGTH_DEFAULT = 0.0F;
-  public static final float L2STRENGTH_DEFAULT = 0.0F;
-
-  private Map config = new HashMap<>();
-  private float learningRate;
-
-  /**
-   * Create an AdagradDA Optimizer with default values name="adagrad-da". learning_rate=.001,
-   * initial accumulator= 0.1, l1Strength=0.0, l2Strength=0.0;
-   *
-   * @param tf the tensorflow tf
-   */
-  public AdaGradDA(Ops tf) {
-    this(tf, LEARNING_RATE_DEFAULT, INITIAL_ACCUM__DEFAULT, L1STRENGTH_DEFAULT, L2STRENGTH_DEFAULT);
-  }
-
-  /**
-   * Create an AdagradDA Optimizer with default values initial accumulator= 0.1, l1Strength=0.0,
-   * l2Strength=0.0;
-   *
-   * @param tf the tensorflow tf
-   * @param learningRate The learning rate.
-   */
-  public AdaGradDA(Ops tf, float learningRate) {
-    this(tf, learningRate, INITIAL_ACCUM__DEFAULT, L1STRENGTH_DEFAULT, L2STRENGTH_DEFAULT);
-  }
-
-  /**
-   * Create an AdagradDA Optimizer with default values initial accumulator= 0.1, l1Strength=0.0,
-   * l2Strength=0.0;
-   *
-   * @param tf the tensorflow tf
-   * @param name the name of the Optimizer, defaults to "adagrad-da"
-   * @param learningRate The learning rate.
-   */
-  public AdaGradDA(Ops tf, String name, float learningRate) {
-    this(tf, name, learningRate, INITIAL_ACCUM__DEFAULT, L1STRENGTH_DEFAULT, L2STRENGTH_DEFAULT);
-  }
-
-  /**
-   * Create an AdagradDA Optimizer
-   *
-   * @param tf the tensorflow tf
-   * @param learningRate the learning rate, default is 0.001
-   * @param initialAccumulatorValue Starting value for the accumulators, must be >= 0.0.
-   * @param l1Strength L1 Regularization Strength
-   * @param l2Strength L2 Regularization Strength
-   */
-  public AdaGradDA(
-      Ops tf,
-      float learningRate,
-      float initialAccumulatorValue,
-      float l1Strength,
-      float l2Strength) {
-    super(assertGraph(tf), learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-    if( initialAccumulatorValue < 0.0F)
-        throw new IllegalArgumentException("initial_accumulator_value must be non-negative: " + initialAccumulatorValue);
-    if(l1Strength < 0)
-      throw new IllegalArgumentException("l1Strength must be non-negative: " + l1Strength);
-    if(l2Strength < 0)
-      throw new IllegalArgumentException("l2Strength must be non-negative: " + l2Strength);
-    initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-  }
-
-  /**
-   * Create an AdagradDA Optimizer
-   *
-   * @param tf the tensorflow tf
-   * @param name the name of the Optimizer, defaults to "adagrad-da"
-   * @param learningRate the learning rate, default is 0.001
-   * @param initialAccumulatorValue Starting value for the accumulators, must be positive.
-   * @param l1Strength L1 Regularization Strength
-   * @param l2Strength L2 Regularization Strength
-   */
-  public AdaGradDA(
-      Ops tf,
-      String name,
-      float learningRate,
-      float initialAccumulatorValue,
-      float l1Strength,
-      float l2Strength) {
-    super(assertGraph(tf), name, learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-    if( initialAccumulatorValue < 0.0F)
-      throw new IllegalArgumentException("initial_accumulator_value must be non-negative: " + initialAccumulatorValue);
-    if(l1Strength < 0)
-      throw new IllegalArgumentException("l1Strength must be non-negative: " + l1Strength);
-    if(l2Strength < 0)
-      throw new IllegalArgumentException("l2Strength must be non-negative: " + l2Strength);
-    initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-    initConfig(learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-  }
-
-  /**
-   * Create an AdaGrad Optimizer from a config object
-   *
-   * @param tf the tensorflow tf
-   * @param config a config object to initialize, , the config object has keys for "name",
-   *     "learning_rate", "accumulator", "l1Strength" and "l2Strength". If a key is missing the
-   *     default value is used.
-   * @return the new AdaGradDA Optimizer
-   */
-  public static AdaGradDA fromConfig(Ops tf, Map config) {
-    return create(tf, config);
-  }
-
-  /**
-   * Create an AdaGradDA Optimizer from a config object
-   *
-   * @param tf the tensorflow tf
-   * @param config a config object to initialize, the config object has keys for "name",
-   *     "learning_rate", "accumulator", "l1Strength" and "l2Strength". If a key is missing the
-   *     default value is used.
-   * @return the new AdaGradDA Optimizer
-   */
-  public static AdaGradDA create(Ops tf, Map config) {
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float initialAccumulatorValue =
-        (float) config.getOrDefault(INITIAL_ACCUM_KEY, INITIAL_ACCUM__DEFAULT);
-    float l1Strength = (float) config.getOrDefault(L1STRENGTH_KEY, L2STRENGTH_DEFAULT);
-    float l2Strength = (float) config.getOrDefault(L2STRENGTH_KEY, L2STRENGTH_DEFAULT);
-    if (name != null) {
-      return new AdaGradDA(tf, name, learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-    } else {
-      return new AdaGradDA(tf, learningRate, initialAccumulatorValue, l1Strength, l2Strength);
-    }
-  }
-
-  /**
-   * Initialize the Optimizer from a config object based on which constructor is called.
-   *
-   * @param learningRate the learning rate, default is 0.001
-   * @param initialAccumulatorValue Starting value for the accumulators, must be >= 0.0.
-   * @param l1Strength L1 Regularization Strength
-   * @param l2Strength L2 Regularization Strength
-   */
-  private void initConfig(
-      float learningRate, float initialAccumulatorValue, float l1Strength, float l2Strength) {
-    this.learningRate = learningRate;
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(INITIAL_ACCUM_KEY, initialAccumulatorValue);
-    config.put(L1STRENGTH_KEY, l1Strength);
-    config.put(L2STRENGTH_KEY, l2Strength);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adam.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adam.java
deleted file mode 100644
index 5d74c7e27f4..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adam.java
+++ /dev/null
@@ -1,182 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.Map;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.op.Ops;
-
-/** Adam Optimizer that implements the Adam algorithm. */
-public class Adam extends org.tensorflow.framework.optimizers.Adam implements OptimizerInterface {
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String EPSILON_KEY = "epsilon";
-  public static final String BETA_ONE_KEY = "beta_1";
-  public static final String BETA_TWO_KEY = "beta_2";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.001F;
-  public static final float EPSILON_DEFAULT = 1e-07F;
-  public static final float BETA_ONE_DEFAULT = 0.9F;
-  public static final float BETA_TWO_DEFAULT = 0.999F;
-
-  private float learningRate;
-  private Map config = new HashMap<>();
-
-  /**
-   * Create an Adam Optimizer
-   *
-   * @param tf the tensorflow Ops
-   */
-  public Adam(Ops tf) {
-    this(tf, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adam Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adam"
-   */
-  public Adam(Ops tf, String name) {
-    this(tf, name, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adam Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param learningRate The learning rate. Defaults to 0.001.
-   */
-  public Adam(Ops tf, float learningRate) {
-    this(tf, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adam Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adam"
-   * @param learningRate The learning rate. Defaults to 0.001.
-   */
-  public Adam(Ops tf, String name, float learningRate) {
-    this(tf, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Adam Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9.
-   * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999.
-   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
-   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
-   *     1 of the paper. Defaults to 1e-7.
-   */
-  public Adam(Ops tf, float learningRate, float betaOne, float betaTwo, float epsilon) {
-    super(assertGraph(tf), learningRate, betaOne, betaTwo, epsilon);
-    initConfig(learningRate, betaOne, betaTwo, epsilon);
-  }
-
-  /**
-   * Create an Adam Optimizer
-   *
-   * @param tf the tensorflow Ops
-   * @param name the name of the Optimizer, defaults to "Adam"
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9.
-   * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999.
-   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
-   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
-   *     1 of the paper. Defaults to 1e-7.
-   */
-  public Adam(
-      Ops tf, String name, float learningRate, float betaOne, float betaTwo, float epsilon) {
-    super(assertGraph(tf), name, learningRate, betaOne, betaTwo, epsilon);
-    initConfig(learningRate, betaOne, betaTwo, epsilon);
-  }
-
-  /**
-   * Create an Adam Optimizer from a config object
-   *
-   * @param tf the tensorflow Ops
-   * @param config a config object to initialize, the config object has keys for "name",
-   *     "learning_rate", "epsilon", "beta_1", "beta_2". If a key is missing the default value is
-   *     used.
-   */
-  public static Adam fromConfig(Ops tf, Map config) {
-    return create(tf, config);
-  }
-
-  /**
-   * Create an Adam Optimizer from a config object
-   *
-   * @param tf the tensorflow Ops
-   * @param config a config object to initialize, the config object has keys for "name",
-   *     "learning_rate", "epsilon", "beta_1", "beta_2". If a key is missing the default value is
-   *     used.
-   */
-  public static Adam create(Ops tf, Map config) {
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT);
-    float betaOne = (float) config.getOrDefault(BETA_ONE_KEY, BETA_ONE_DEFAULT);
-    float betaTwo = (float) config.getOrDefault(BETA_TWO_KEY, BETA_TWO_DEFAULT);
-    if (name == null) {
-      return new Adam(tf, learningRate, betaOne, betaTwo, epsilon);
-    } else {
-      return new Adam(tf, name, learningRate, betaOne, betaTwo, epsilon);
-    }
-  }
-
-  /**
-   * Initialize the Optimizer from a config object based on which constructor is called.
-   *
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9.
-   * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999.
-   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
-   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
-   *     1 of the paper. Defaults to 1e-7.
-   */
-  protected void initConfig(float learningRate, float betaOne, float betaTwo, float epsilon) {
-    this.learningRate = learningRate;
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(EPSILON_KEY, epsilon);
-    config.put(BETA_ONE_KEY, betaOne);
-    config.put(BETA_TWO_KEY, betaTwo);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adamax.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adamax.java
deleted file mode 100644
index a976a6e51dd..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Adamax.java
+++ /dev/null
@@ -1,283 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Optional;
-import org.tensorflow.Graph;
-import org.tensorflow.Operand;
-import org.tensorflow.Output;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-import org.tensorflow.op.Scope;
-import org.tensorflow.op.core.Assign;
-import org.tensorflow.op.core.Constant;
-import org.tensorflow.op.core.Variable;
-import org.tensorflow.op.train.ApplyAdaMax;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.family.TType;
-
-/** Adamax Optimizer that implements the Adamax algorithm. */
-public class Adamax extends org.tensorflow.framework.optimizers.Optimizer
-    implements OptimizerInterface {
-
-  public static final String FIRST_MOMENT = "m";
-  public static final String SECOND_MOMENT = "v";
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String EPSILON_KEY = "epsilon";
-  public static final String BETA_ONE_KEY = "beta_1";
-  public static final String BETA_TWO_KEY = "beta_2";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.001F;
-  public static final float EPSILON_DEFAULT = 1e-07F;
-  public static final float BETA_ONE_DEFAULT = 0.9F;
-  public static final float BETA_TWO_DEFAULT = 0.999F;
-
-  private Scope scope;
-  private Map config = new HashMap<>();
-
-  private float learningRate;
-  private final float betaOne;
-  private final float betaTwo;
-  private final float epsilon;
-
-  private Constant learningRateConst;
-  private Constant epsilonConst;
-  private Constant betaOneConst;
-  private Constant betaTwoConst;
-  private Variable betaOnePower;
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm.
-   *
-   * @param tf the TensoFlow Ops
-   */
-  public Adamax(Ops tf) {
-    this(tf, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm.
-   *
-   * @param tf the TensoFlow Ops
-   * @param name name for the operations Created when applying gradients. Defaults to "Adamax".
-   */
-  public Adamax(Ops tf, String name) {
-    this(tf, name, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm.
-   *
-   * @param tf the TensoFlow Ops
-   * @param learningRate The learning rate.
-   */
-  public Adamax(Ops tf, float learningRate) {
-    this(tf, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm.
-   *
-   * @param tf the TensoFlow Ops
-   * @param name name for the operations Created when applying gradients. Defaults to "Adamax".
-   * @param learningRate The learning rate.
-   */
-  public Adamax(Ops tf, String name, float learningRate) {
-    this(tf, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm.
-   *
-   * @param tf the TensoFlow Ops
-   * @param learningRate The learning rate.
-   * @param betaOne The exponential decay rate for the 1st moment estimates.
-   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm.
-   * @param epsilon A small constant for numerical stability.
-   */
-  public Adamax(Ops tf, float learningRate, float betaOne, float betaTwo, float epsilon) {
-    super(assertGraph(tf));
-    this.learningRate = learningRate;
-    this.betaOne = betaOne;
-    this.betaTwo = betaTwo;
-    this.epsilon = epsilon;
-    this.scope = tf.scope();
-    initConfig(learningRate, betaOne, betaTwo, epsilon);
-  }
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm.
-   *
-   * @param tf the TensoFlow Ops
-   * @param name name for the operations Created when applying gradients. Defaults to "Adamax".
-   * @param learningRate The learning rate.
-   * @param betaOne The exponential decay rate for the 1st moment estimates.
-   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm.
-   * @param epsilon A small constant for numerical stability.
-   */
-  public Adamax(
-      Ops tf, String name, float learningRate, float betaOne, float betaTwo, float epsilon) {
-    super(assertGraph(tf), name);
-    this.learningRate = learningRate;
-    this.betaOne = betaOne;
-    this.betaTwo = betaTwo;
-    this.epsilon = epsilon;
-    this.scope = tf.scope();
-
-    initConfig(learningRate, betaOne, betaTwo, epsilon);
-  }
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm from a config object
-   *
-   * @param tf the TensoFlow Ops
-   * @param config a config object to initialize, the config object has keys for "name",
-   *     "learning_rate", "epsilon", "beta_1", "beta_2". If a key is missing the default value is
-   *     used.
-   */
-  public static Adamax fromConfig(Ops tf, Map config) {
-    return create(tf, config);
-  }
-
-  /**
-   * Create an Optimizer that implements the Adamax algorithm from a config object
-   *
-   * @param tf the TensoFlow Ops
-   * @param config a config object to initialize
-   */
-  public static Adamax create(Ops tf, Map config) {
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT);
-    float betaOne = (float) config.getOrDefault(BETA_ONE_KEY, BETA_ONE_DEFAULT);
-    float betaTwo = (float) config.getOrDefault(BETA_TWO_KEY, BETA_TWO_DEFAULT);
-    if (name == null) {
-      return new Adamax(tf, learningRate, betaOne, betaTwo, epsilon);
-    } else {
-      return new Adamax(tf, name, learningRate, betaOne, betaTwo, epsilon);
-    }
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected Optional prepare(String scopeName) {
-    betaOneConst = tf.constant(betaOne);
-    betaTwoConst = tf.constant(betaTwo);
-    learningRateConst = tf.constant(learningRate);
-    epsilonConst = tf.constant(epsilon);
-
-    return Optional.empty();
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected void createSlots(List> variables) {
-    for (Output v : variables) {
-      createAdamaxSlot(v.asOutput());
-    }
-    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
-    Assign betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
-    ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit);
-  }
-
-  /**
-   * Create the first and second moment slots
-   *
-   * @param v the variable
-   * @param  the datatype of the variable
-   */
-  private  void createAdamaxSlot(Output v) {
-    Operand firstMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
-    createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
-    Operand secondMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
-    createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected  Op applyDense(Output gradient, Output variable) {
-    Variable firstMomentSlot = getSlot(variable, FIRST_MOMENT).get();
-    Variable secondMomentSlot = getSlot(variable, SECOND_MOMENT).get();
-    return ApplyAdaMax.create(
-        scope,
-        (Operand) variable,
-        (Operand) firstMomentSlot,
-        (Operand) secondMomentSlot,
-        (Operand) tf.dtypes.cast(betaOnePower, gradient.dataType()),
-        (Operand) tf.dtypes.cast(learningRateConst, gradient.dataType()),
-        (Operand) tf.dtypes.cast(betaOneConst, gradient.dataType()),
-        (Operand) tf.dtypes.cast(betaTwoConst, gradient.dataType()),
-        (Operand) tf.dtypes.cast(epsilonConst, gradient.dataType()),
-        (Operand) gradient);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected Op finish(List updateOperations, String name) {
-    updateOperations.add(tf.assign(betaOnePower, tf.math.mul(betaOnePower, betaOneConst)));
-    return super.finish(updateOperations, name);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public String getOptimizerName() {
-    return "Adamax";
-  }
-
-  /**
-   * Initialize the Optimizer from a config object based on which constructor is called.
-   *
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9.
-   * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999.
-   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
-   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
-   *     1 of the paper. Defaults to 1e-7.
-   */
-  protected void initConfig(float learningRate, float betaOne, float betaTwo, float epsilon) {
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(EPSILON_KEY, epsilon);
-    config.put(BETA_ONE_KEY, betaOne);
-    config.put(BETA_TWO_KEY, betaTwo);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Nadam.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Nadam.java
deleted file mode 100644
index a2eba4ecb49..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Nadam.java
+++ /dev/null
@@ -1,399 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Optional;
-
-import org.tensorflow.DataType;
-import org.tensorflow.Graph;
-import org.tensorflow.Operand;
-import org.tensorflow.Output;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.Op;
-import org.tensorflow.op.Ops;
-import org.tensorflow.op.core.Assign;
-import org.tensorflow.op.core.Constant;
-import org.tensorflow.op.core.Variable;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TType;
-
-/** Nadam Optimizer that implements the NAdam algorithm. */
-public class Nadam extends org.tensorflow.framework.optimizers.Optimizer
-    implements OptimizerInterface {
-
-  public static final String FIRST_MOMENT = "m";
-  public static final String SECOND_MOMENT = "v";
-  public static final String MOMENTUM = "momentum";
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String EPSILON_KEY = "epsilon";
-  public static final String BETA_ONE_KEY = "beta_1";
-  public static final String BETA_TWO_KEY = "beta_2";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.001F;
-  public static final float EPSILON_DEFAULT = 1e-07F;
-  public static final float BETA_ONE_DEFAULT = 0.9F;
-  public static final float BETA_TWO_DEFAULT = 0.999F;
-
-  private final Map config = new HashMap<>();
-
-  private float learningRate;
-  private final float betaOne;
-  private final float betaTwo;
-  private final float epsilon;
-  private final float decayBase = 0.96F;
-  private final float decay = 0.004F;
-
-  private long iterations = 0;
-
-  private Constant learningRateConst;
-  private Constant betaOneConst;
-  private Constant betaTwoConst;
-  private Constant localStepConst;
-  private Constant nextStepConst;
-
-  private Constant decayBaseConst;
-  private Constant decayConst;
-  private Constant epsilonConst;
-
-  private Variable betaOnePower;
-  private Variable betaTwoPower;
-  private Variable momentum;
-
-  private Operand m_t;
-  private Operand m_t_1;
-  private Operand m_schedule_new;
-  private Operand m_schedule_next;
-  private Operand one_minus_beta_1;
-  private Operand one_minus_beta_2;
-  private Operand one_minus_m_t;
-  private Operand one_minus_m_schedule_new;
-  private Operand one_minus_m_schedule_next;
-  private Operand v_t_prime_denominator;
-
-  /**
-   * Create an Optimizer that implements the NAdam algorithm.
-   *
-   * @param tf the TensorFlow Ops
-   */
-  public Nadam(Ops tf) {
-    this(tf, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the NAdam algorithm.
-   *
-   * @param tf the TensorFlow Ops
-   * @param name name for the operations created when applying gradients. Defaults to "Nadam".
-   */
-  public Nadam(Ops tf, String name) {
-    this(tf, name, LEARNING_RATE_DEFAULT, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the NAdam algorithm.
-   *
-   * @param tf the TensorFlow Ops
-   * @param learningRate The learning rate.
-   */
-  public Nadam(Ops tf, float learningRate) {
-    this(tf, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the NAdam algorithm.
-   *
-   * @param tf the TensorFlow Ops
-   * @param name name for the operations created when applying gradients. Defaults to "Adamax".
-   * @param learningRate The learning rate.
-   */
-  public Nadam(Ops tf, String name, float learningRate) {
-    this(tf, name, learningRate, BETA_ONE_DEFAULT, BETA_TWO_DEFAULT, EPSILON_DEFAULT);
-  }
-
-  /**
-   * Create an Optimizer that implements the NAdam algorithm.
-   *
-   * @param tf the TensorFlow Ops
-   * @param learningRate The learning rate.
-   * @param betaOne The exponential decay rate for the 1st moment estimates.
-   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm.
-   * @param epsilon A small constant for numerical stability.
-   */
-  public Nadam(Ops tf, float learningRate, float betaOne, float betaTwo, float epsilon) {
-    super(assertGraph(tf));
-    this.learningRate = learningRate;
-    this.betaOne = betaOne;
-    this.betaTwo = betaTwo;
-    this.epsilon = epsilon;
-    initConfig(learningRate, betaOne, betaTwo, epsilon);
-  }
-
-  /**
-   * Create an Optimizer that implements the NAdam algorithm.
-   *
-   * @param tf the TensorFlow Ops
-   * @param name name for the operations created when applying gradients.
-   * @param learningRate The learning rate.
-   * @param betaOne The exponential decay rate for the 1st moment estimates.
-   * @param betaTwo The exponential decay rate for the exponentially weighted infinity norm.
-   * @param epsilon A small constant for numerical stability.
-   */
-  public Nadam(
-      Ops tf, String name, float learningRate, float betaOne, float betaTwo, float epsilon) {
-    super(assertGraph(tf), name);
-    this.learningRate = learningRate;
-    this.betaOne = betaOne;
-    this.betaTwo = betaTwo;
-    this.epsilon = epsilon;
-
-    initConfig(learningRate, betaOne, betaTwo, epsilon);
-  }
-
-  /**
-   * Create an Optimizer that implements the NAdam algorithm.
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize
-   */
-  public static Nadam create(Ops tf, Map config) {
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT);
-    float betaOne = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float betaTwo = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    if (name == null) {
-      return new Nadam(tf, learningRate, betaOne, betaTwo, epsilon);
-    } else {
-      return new Nadam(tf, name, learningRate, betaOne, betaTwo, epsilon);
-    }
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected void createSlots(List> variables) {
-    for (Output v : variables) {
-      createNadamSlot(v.asOutput());
-    }
-    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
-    Assign betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
-    ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit);
-
-    betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.DTYPE);
-    Assign betaTwoPowerInit = tf.assign(betaTwoPower, tf.constant(betaTwo));
-    ((Graph) tf.scope().env()).addInitializer(betaTwoPowerInit);
-
-    momentum = tf.withName("momentum").variable(Shape.scalar(), TFloat32.DTYPE);
-    Assign momentumInit = tf.assign(momentum, tf.constant(1.0F));
-    ((Graph) tf.scope().env()).addInitializer(momentumInit);
-  }
-
-  /**
-   * Create slots for first and second momements and momentum
-   *
-   * @param v the variable
-   * @param  the data type or the Variable
-   */
-  private  void createNadamSlot(Output v) {
-    Operand firstMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
-    createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
-    Operand secondMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
-    createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
-
-    Operand momentumInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.dataType()));
-    createSlot(v.asOutput(), MOMENTUM, momentumInitializer);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected Optional prepare(String scopeName) {
-    Constant one = tf.constant(1.0F);
-    Constant point5 = tf.constant(0.5F);
-
-    learningRateConst = tf.constant(learningRate);
-    betaOneConst = tf.constant(betaOne);
-    betaTwoConst = tf.constant(betaTwo);
-    localStepConst = tf.constant(this.iterations + 1);
-    nextStepConst = tf.constant(this.iterations + 2);
-    decayConst = tf.constant(decay);
-    decayBaseConst = tf.constant(this.decayBase);
-    epsilonConst = tf.constant(this.epsilon);
-
-    //  m_t = beta_1_t * (1. - 0.5 * ( math_ops.pow(decay_base, self._initial_decay * local_step)))
-    m_t =
-        tf.math.mul(
-            betaOneConst,
-            tf.math.sub(
-                one,
-                tf.math.mul(
-                    point5,
-                    tf.math.pow(
-                        decayBaseConst,
-                        tf.math.mul(decayConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE))))));
-    // m_t_1 = beta_1_t * (1. - 0.5 * ( math_ops.pow(decay_base, self._initial_decay * next_step)))
-    m_t_1 =
-        tf.math.mul(
-            betaOneConst,
-            tf.math.sub(
-                one,
-                tf.math.mul(
-                    point5,
-                    tf.math.pow(
-                        decayBaseConst,
-                        tf.math.mul(decayConst, tf.dtypes.cast(nextStepConst, TFloat32.DTYPE))))));
-
-    // m_schedule_new = math_ops.cast(self._m_cache_read, var_dtype) * m_t
-    m_schedule_new = tf.math.mul(momentum, m_t);
-    // if var_dtype is self._m_cache.dtype:
-    // m_schedule_new = array_ops.identity(state_ops.assign(
-    // self._m_cache, m_schedule_new, use_locking=self._use_locking))
-    m_schedule_new = tf.identity(tf.assign(momentum, m_schedule_new, Assign.useLocking(true)));
-    // m_schedule_next = m_schedule_new * m_t_1
-    m_schedule_next = tf.math.mul(m_schedule_new, m_t_1);
-
-    // 1 - beta_1_t
-    one_minus_beta_1 = tf.math.sub(one, betaOneConst);
-    // 1 - beta_2_t,
-    one_minus_beta_2 = tf.math.sub(one, betaTwoConst);
-    // 1. - m_t,
-    one_minus_m_t = tf.math.sub(one, m_t);
-    // 1. - m_schedule_new
-    one_minus_m_schedule_new = tf.math.sub(one, m_schedule_new);
-    // 1. - m_schedule_next
-    one_minus_m_schedule_next = tf.math.sub(one, m_schedule_next);
-    // 1. - math_ops.pow(beta_2_t, local_step)
-    v_t_prime_denominator =
-        tf.math.sub(one, tf.math.pow(betaTwoConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE)));
-    return Optional.empty();
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  protected  Op applyDense(Output gradient, Output variable) {
-    DataType dType = gradient.dataType();
-    Variable m = getSlot(variable, FIRST_MOMENT).get(); // first Moment
-    Variable v = getSlot(variable, SECOND_MOMENT).get(); // Second Moment
-
-    //  g_prime = grad / coefficients['one_minus_m_schedule_new']
-    Operand g_prime = tf.math.div(gradient, tf.dtypes.cast(one_minus_m_schedule_new, dType));
-    // m_t = (coefficients['beta_1_t'] * m + coefficients['one_minus_beta_1_t'] * grad)
-    Operand m_t =
-        tf.math.add(
-            tf.math.mul(tf.dtypes.cast(betaOneConst, dType), m),
-            tf.math.mul(tf.dtypes.cast(one_minus_beta_1, dType), gradient));
-    // m_t = state_ops.assign(m, m_t, use_locking=self._use_locking)
-    // update m
-    m_t = tf.assign(m, m_t, Assign.useLocking(true));
-
-    // m_t_prime = m_t / coefficients['one_minus_m_schedule_next']
-    Operand m_t_prime = tf.math.div(m_t, tf.dtypes.cast(one_minus_m_schedule_next, dType));
-
-    // v_t = (coefficients['beta_2_t'] * v + coefficients['one_minus_beta_2_t'] *
-    // math_ops.square(grad))
-    Operand v_t =
-        tf.math.add(
-            tf.math.mul(tf.dtypes.cast(betaTwoConst, dType), v),
-            tf.math.mul(tf.dtypes.cast(one_minus_beta_2, dType), tf.math.square(gradient)));
-    // v_t = state_ops.assign(v, v_t, use_locking=self._use_locking)
-    // update v
-    v_t = tf.assign(v, v_t, Assign.useLocking(true));
-
-    // v_t_prime = v_t / coefficients['v_t_prime_denominator']
-    Operand v_t_prime = tf.math.div(v_t, tf.dtypes.cast(v_t_prime_denominator, dType));
-
-    // m_t_bar = (coefficients['one_minus_m_t'] * g_prime + coefficients['m_t_1'] * m_t_prime)
-    Operand m_t_bar =
-        tf.math.add(
-            tf.math.mul(tf.dtypes.cast(one_minus_m_t, dType), g_prime),
-            tf.math.mul(tf.dtypes.cast(m_t_1, dType), m_t_prime));
-    // var_t = var - coefficients['lr_t'] * m_t_bar / (math_ops.sqrt(v_t_prime) +
-    // coefficients['epsilon'])
-    Operand var_t =
-        tf.math.sub(
-            variable,
-            tf.math.div(
-                tf.math.mul(tf.dtypes.cast(learningRateConst, dType), m_t_bar),
-                tf.math.add(tf.math.sqrt(v_t_prime), tf.dtypes.cast(epsilonConst, dType))));
-    // assign(var, var_t, use_locking=self._use_locking)
-    return tf.assign(variable, var_t, Assign.useLocking(true));
-  }
-
-  /**
-   * Gathers up the update operations into a single op that can be used as a run target.
-   *
-   * 
    Adds the betaOne, betaTwo and mu updates to the end of the updates list.
-   *
-   * @param updateOperations The update operations.
-   * @param name The name of the run target.
-   * @return A NoOp with a control dependency on each update operation.
-   */
-  @Override
-  protected Op finish(List updateOperations, String name) {
-    iterations++; // increment the step;
-    updateOperations.add(tf.assign(betaOnePower, tf.math.mul(betaOnePower, betaOneConst)));
-    updateOperations.add(tf.assign(betaTwoPower, tf.math.mul(betaTwoPower, betaTwoConst)));
-    return super.finish(updateOperations, name);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public String getOptimizerName() {
-    return "Nadam";
-  }
-
-  /**
-   * Sets the config object based on the current state of the Optmizer.
-   *
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param betaOne The exponential decay rate for the 1st moment estimates. Defaults to 0.9.
-   * @param betaTwo The exponential decay rate for the 2nd moment estimates. Defaults to 0.999.
-   * @param epsilon A small constant for numerical stability. This epsilon is "epsilon hat" in the
-   *     Kingma and Ba paper (in the formula just before Section 2.1), not the epsilon in Algorithm
-   *     1 of the paper. Defaults to 1e-7.
-   */
-  private void initConfig(float learningRate, float betaOne, float betaTwo, float epsilon) {
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(EPSILON_KEY, epsilon);
-    config.put(BETA_ONE_KEY, betaOne);
-    config.put(BETA_TWO_KEY, betaTwo);
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/OptimizerInterface.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/OptimizerInterface.java
deleted file mode 100644
index 0074ecb0f0a..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/OptimizerInterface.java
+++ /dev/null
@@ -1,61 +0,0 @@
-/* Copyright 2020 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.keras.optimizers;
-
-import java.util.Map;
-import org.tensorflow.Graph;
-import org.tensorflow.op.Ops;
-
-/** The main Interface for Keras Optimizers */
-public interface OptimizerInterface {
-
-  /** The value for the name key in the Config object */
-  String NAME_KEY = "name";
-
-  /**
-   * Get a TensorFlow Graph from the Ops.
-   *
-   * @param tf the TensorFlow Ops
-   * @return the graph
-   * @throws java.lang.IllegalArgumentException if the TensorFlow Ops does not represent Graph mode
-   */
-  static Graph assertGraph(Ops tf) {
-    if(!tf.scope().env().isGraph()) {
-      throw new IllegalArgumentException("Invalid environment, Optimizers can only be used in Graph Mode");
-    }
-    return (Graph) tf.scope().env();
-  }
-
-  /**
-   * Return the config object used to initialize the Optimizer
-   *
-   * @return the config object used to initialize the Optimizer
-   */
-  Map getConfig();
-
-  /**
-   * Return the current learning rate
-   *
-   * @return the current learning rate
-   */
-  float getLearningRate();
-
-  /**
-   * Set the learning rate
-   *
-   * @param learningRate the learning rate;
-   */
-  void setLearningRate(float learningRate);
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Optimizers.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Optimizers.java
deleted file mode 100644
index 1facb307b38..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/Optimizers.java
+++ /dev/null
@@ -1,125 +0,0 @@
-/* Copyright 2020 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.keras.optimizers;
-
-import org.tensorflow.framework.optimizers.Optimizer;
-import org.tensorflow.op.Ops;
-
-import java.lang.reflect.Constructor;
-import java.lang.reflect.InvocationTargetException;
-import java.util.HashMap;
-import java.util.Map;
-import java.util.function.Function;
-import java.util.logging.Level;
-import java.util.logging.Logger;
-import java.util.function.Supplier;
-
-/**
- * Functions to get an Optimizer based on String name, an Optimizer class, or lambda function.
- *
- * 
    Example:
- *
- * 
    - *     Adam instance = Optimizers.get(tf, "adam");
- *     Ftrl instance = Optimizers.get(tf, ltf -> new Ftrl(ltf, 0.1f);
- * 
    
- */
-public class Optimizers {
-
-  static Map> map =
-      new HashMap>() {
-        {
-          put("adadelta", AdaDelta::new);
-          put("adagrad", AdaGrad::new);
-          put("adagrad-da", AdaGradDA::new);
-          put("adam", Adam::new);
-          put("adamax", Adamax::new);
-          put("ftrl", Ftrl::new);
-          put("nadam", Nadam::new);
-          put("rmsprop", RMSProp::new);
-          put("sgd", SGD::new);
-        }
-      };
-
-  /**
-   * Get an Optimizer
-   *
-   * @param optimizerFunction either a String that identifies the Optimizer, an Optimizer class, or
-   *     an Optimizer object.
-   * @return the Optimizer object or null if not found.
-   */
-  public static Optimizer get(Ops tf, Object optimizerFunction) {
-    return get(tf, optimizerFunction, null);
-  }
-
-  /**
-   * Get an Optimizer
-   *
-   * @param func a lamda function that returns the Optimizer
-   * @return the Intializer object
-   */
-  public static Optimizer get(Ops tf, Function func) {
-    return func.apply(tf);
-  }
-
-  /**
-   * Get an Optimizer
-   *
-   * @param optimizerFunction either a String that identifies the Optimizer, an Optimizer class, or
-   *     * an Optimizer object.
-   * @param custom_functions a map of Optimizer lambdas that will be queried if the Optimizer is
-   *     not found in the standard keys
-   * @return the Optimizer object
-   */
-  public static Optimizer get(
-      Ops tf, Object optimizerFunction, Map> custom_functions) {
-    if (optimizerFunction != null) {
-      if (optimizerFunction instanceof String) {
-        String s =
-            optimizerFunction
-                .toString(); // do this for Java 8 rather than Pattern Matching for instanceof
-        Function function = map.get(s);
-        if (function == null && custom_functions != null) {
-          function = custom_functions.get(s);
-        }
-        return function != null ? function.apply(tf) : null;
-      } else if (optimizerFunction instanceof Class) {
-        // do this for Java 8 rather than Pattern Matching for instanceof
-        Class c = (Class) optimizerFunction;
-        try {
-          Constructor ctor = c.getConstructor(Ops.class);
-          return (Optimizer) ctor.newInstance(tf);
-        } catch (NoSuchMethodException
-            | InstantiationException
-            | IllegalAccessException
-            | IllegalArgumentException
-            | InvocationTargetException ex) {
-          Logger.getLogger(Optimizers.class.getName()).log(Level.SEVERE, null, ex);
-        }
-      } else if (optimizerFunction instanceof Optimizer) {
-        return (Optimizer) optimizerFunction;
-      } else if (optimizerFunction instanceof Function) {
-        return ((Function) optimizerFunction).apply(tf);
-      } else if (optimizerFunction instanceof Supplier) {
-        return ((Supplier) optimizerFunction).get();
-      }
-    } else {
-      return null;
-    }
-
-    throw new IllegalArgumentException(
-        "optimizerFunction must be a symbolic name, Optimizer, Function, Supplier or a Class object");
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/RMSProp.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/RMSProp.java
deleted file mode 100644
index c66c6bdd388..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/RMSProp.java
+++ /dev/null
@@ -1,201 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.Map;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.NAME_KEY;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.op.Ops;
-
-/** RMSProp Optimizer that implements the RMSProp algorithm. */
-public class RMSProp extends org.tensorflow.framework.optimizers.RMSProp
-    implements OptimizerInterface {
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String DECAY_KEY = "decay";
-  public static final String MOMENTUM_KEY = "momentum";
-  public static final String EPSILON_KEY = "epsilon";
-  public static final String CENTERED_KEY = "centered";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.001F;
-  public static final float DECAY_DEFAULT = 0.9F;
-  public static final float MOMENTUM_DEFAULT = 0.0F;
-  public static final float EPSILON_DEFAULT = 1e-07F;
-  public static final boolean CENTERED_DEFAULT = false;
-
-  private Map config = new HashMap<>();
-  private float learningRate;
-
-  /**
-   * Create an RMSProp Optimizer with the following defaults, name="RMSProp", learning_rate=0.001,
-   * decay=0.9, momentum=0.0, epsilon=1e-07, centered=false
-   *
-   * @param tf the TensorFlow Ops
-   */
-  public RMSProp(Ops tf) {
-    this(
-        tf,
-        LEARNING_RATE_DEFAULT,
-        DECAY_DEFAULT,
-        MOMENTUM_DEFAULT,
-        EPSILON_DEFAULT,
-        CENTERED_DEFAULT);
-  }
-
-  /**
-   * Create an RMSProp Optimizer with the following defaults, name="RMSProp", decay=0.9,
-   * momentum=0.0, epsilon=1e-07, centered=false
-   *
-   * @param tf the TensorFlow Ops
-   * @param learningRate The learning rate.
-   */
-  public RMSProp(Ops tf, float learningRate) {
-    this(tf, learningRate, DECAY_DEFAULT, MOMENTUM_DEFAULT, EPSILON_DEFAULT, CENTERED_DEFAULT);
-  }
-
-  /**
-   * Create an RMSProp Optimizer with the following defaults, decay=0.9, momentum=0.0,
-   * epsilon=1e-07, centered=false
-   *
-   * @param tf the TensorFlow Ops
-   * @param name prefix for the operations created when applying gradients. Defaults to "RMSProp"
-   * @param learningRate The learning rate.
-   */
-  public RMSProp(Ops tf, String name, float learningRate) {
-    this(
-        tf, name, learningRate, DECAY_DEFAULT, MOMENTUM_DEFAULT, EPSILON_DEFAULT, CENTERED_DEFAULT);
-  }
-
-  /**
-   * Create an RMSProp Optimizer
-   *
-   * @param tf the TensorFlow Ops
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9.
-   * @param momentum hyperparameter that accelerates descent in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   * @param epsilon A small constant for numerical stability.
-   * @param centered If True, gradients are normalized by the estimated variance of the gradient; if
-   *     False, by the uncentered second moment.
-   */
-  public RMSProp(
-      Ops tf, float learningRate, float decay, float momentum, float epsilon, boolean centered) {
-    super(assertGraph(tf), learningRate, decay, momentum, epsilon, centered);
-    initConfig(learningRate, decay, momentum, epsilon, centered);
-  }
-
-  /**
-   * Create an RMSProp Optimizer
-   *
-   * @param tf the TensorFlow Ops
-   * @param name prefix for the operations created when applying gradients. Defaults to "RMSProp"
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9.
-   * @param momentum hyperparameter that accelerates descent in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   * @param epsilon A small constant for numerical stability.
-   * @param centered If True, gradients are normalized by the estimated variance of the gradient; if
-   *     False, by the uncentered second moment.
-   */
-  public RMSProp(
-      Ops tf,
-      String name,
-      float learningRate,
-      float decay,
-      float momentum,
-      float epsilon,
-      boolean centered) {
-    super(assertGraph(tf), name, learningRate, decay, momentum, epsilon, centered);
-    initConfig(learningRate, decay, momentum, epsilon, centered);
-  }
-
-  /**
-   * Create a RMSProp Optimizer using a configuration
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize the Optimizer, the config object has keys for
-   *     "name", "learning_rate", "decay", "momentum", "epsilon" and "centered". If a key is missing
-   *     the default value is used.
-   * @return the RMSProp optimizer
-   */
-  public static RMSProp fromConfig(Ops tf, Map config) {
-    return create(tf, config);
-  }
-
-  /**
-   * Create a RMSProp Optimizer using a configuration
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize the Optimizer, the config object has keys for
-   *     "name", "learning_rate", "decay", "momentum", "epsilon" and "centered". If a key is missing
-   *     the default value is used.
-   * @return the RMSProp optimizer
-   */
-  public static RMSProp create(Ops tf, Map config) {
-
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float decay = (float) config.getOrDefault(DECAY_KEY, DECAY_DEFAULT);
-    float momentum = (float) config.getOrDefault(MOMENTUM_KEY, MOMENTUM_DEFAULT);
-    float epsilon = (float) config.getOrDefault(EPSILON_KEY, EPSILON_DEFAULT);
-    boolean centered = (boolean) config.getOrDefault(CENTERED_KEY, CENTERED_DEFAULT);
-    if (name == null) {
-      return new RMSProp(tf, learningRate, decay, momentum, epsilon, centered);
-    } else {
-      return new RMSProp(tf, name, learningRate, decay, momentum, epsilon, centered);
-    }
-  }
-
-  /**
-   * Initialize the configuration based on which constructor is called.
-   *
-   * @param learningRate The learning rate. Defaults to 0.001.
-   * @param decay Discounting factor for the history/coming gradient. Defaults to 0.9.
-   * @param momentum hyperparameter that accelerates descent in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   * @param epsilon A small constant for numerical stability.
-   * @param centered If True, gradients are normalized by the estimated variance of the gradient; if
-   *     False, by the uncentered second moment.
-   */
-  private void initConfig(
-      float learningRate, float decay, float momentum, float epsilon, boolean centered) {
-    this.learningRate = learningRate;
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(DECAY_KEY, decay);
-    config.put(MOMENTUM_KEY, momentum);
-    config.put(EPSILON_KEY, epsilon);
-    config.put(CENTERED_KEY, centered);
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-}
diff --git a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/SGD.java b/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/SGD.java
deleted file mode 100644
index f89682f6820..00000000000
--- a/tensorflow-keras/src/main/java/org/tensorflow/keras/optimizers/SGD.java
+++ /dev/null
@@ -1,200 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the );
-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  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.keras.optimizers;
-
-import java.util.HashMap;
-import java.util.Map;
-import static org.tensorflow.keras.optimizers.OptimizerInterface.assertGraph;
-import org.tensorflow.op.Ops;
-
-/** Stochastic Gradient Descent and momentum optimizer. */
-public class SGD extends org.tensorflow.framework.optimizers.Momentum
-    implements OptimizerInterface {
-
-  public static final String LEARNING_RATE_KEY = "learning_rate";
-  public static final String MOMENTUM_KEY = "momentum";
-  public static final String NESTEROV_KEY = "nesterov";
-
-  public static final float LEARNING_RATE_DEFAULT = 0.01F;
-  public static final float MOMENTUM_DEFAULT = 0.0F;
-  public static final boolean NESTEROV_DEFAULT = false;
-
-  private Map config = new HashMap<>();
-  private float learningRate;
-
-  /**
-   * Create a Stochastic Gradient Descent optimizer using defaults: name="SGD", learning_rate=0.01,
-   * momentum=0.0, and nesterov=false
-   *
-   * @param tf the TensorFlow Ops
-   */
-  public SGD(Ops tf) {
-    this(tf, LEARNING_RATE_DEFAULT, MOMENTUM_DEFAULT, NESTEROV_DEFAULT);
-  }
-
-  /**
-   * Create a Stochastic gradient descent optimizer using defaults: name="SGD", momentum=0.0, and
-   * nesterov=false
-   *
-   * @param tf the TensorFlow Ops
-   * @param learningRate The learning rate. Defaults to 0.01.
-   */
-  public SGD(Ops tf, float learningRate) {
-    this(tf, learningRate, MOMENTUM_DEFAULT, NESTEROV_DEFAULT);
-  }
-
-  /**
-   * Create a Stochastic gradient descent optimizer using defaults: name="SGD", and nesterov=false
-   *
-   * @param tf the TensorFlow Ops
-   * @param learningRate The learning rate. Defaults to 0.01.
-   * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   */
-  public SGD(Ops tf, float learningRate, float momentum) {
-    this(tf, learningRate, momentum, NESTEROV_DEFAULT);
-  }
-
-  /**
-   * Create a Stochastic gradient descent optimizer using defaults: momentum=0.0, and nesterov=false
-   *
-   * @param tf the TensorFlow Ops
-   * @param name prefix for the operations created when applying gradients
-   * @param learningRate The learning rate. Defaults to 0.01.
-   */
-  public SGD(Ops tf, String name, float learningRate) {
-    this(tf, name, learningRate, MOMENTUM_DEFAULT, NESTEROV_DEFAULT);
-  }
-
-  /**
-   * create a Stochastic gradient descent optimizer using defaults: momentum=0.0, and nesterov=false
-   *
-   * @param tf the TensorFlow Ops
-   * @param name prefix for the operations created when applying gradients
-   * @param learningRate The learning rate. Defaults to 0.01.
-   * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   */
-  public SGD(Ops tf, String name, float learningRate, float momentum) {
-    this(tf, name, learningRate, momentum, NESTEROV_DEFAULT);
-  }
-
-  /**
-   * Create a Stochastic gradient descent optimizer
-   *
-   * @param tf the TensorFlow Ops
-   * @param learningRate The learning rate. Defaults to 0.01.
-   * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   * @param useNesterov Whether to apply Nesterov momentum. Defaults to `false`.
-   */
-  public SGD(Ops tf, float learningRate, float momentum, boolean useNesterov) {
-    super(assertGraph(tf), learningRate, momentum, useNesterov);
-    if(momentum < 0 || momentum > 1)
-      throw new IllegalArgumentException("\"momentum\" must be between [0, 1].");
-    initConfig(learningRate, momentum, useNesterov);
-  }
-
-  /**
-   * Create a Stochastic gradient descent optimizer
-   *
-   * @param tf the TensorFlow Ops
-   * @param name prefix for the operations created when applying gradients
-   * @param learningRate The learning rate. Defaults to 0.01.
-   * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   * @param useNesterov Whether to apply Nesterov momentum. Defaults to `false`.
-   */
-  public SGD(Ops tf, String name, float learningRate, float momentum, boolean useNesterov) {
-    super(assertGraph(tf), name, learningRate, momentum, useNesterov);
-    if(momentum < 0 || momentum > 1)
-      throw new IllegalArgumentException("\"momentum\" must be between [0, 1].");
-    initConfig(learningRate, momentum, useNesterov);
-  }
-
-  /**
-   * Create a Stochastic gradient descent optimizer
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize, the config object has keys for "name",
-   *     "learning_rate", "momentum", and "nesterov". If a key is missing the default value is used.
-   * @return the Stochastic gradient descent optimizer
-   */
-  public static SGD fromConfig(Ops tf, Map config) {
-    return create(tf, config);
-  }
-
-  /**
-   * Create a Stochastic gradient descent optimizer
-   *
-   * @param tf the TensorFlow Ops
-   * @param config a config object to initialize, the config object has keys for "name",
-   *     "learning_rate", "momentum", and "nesterov". If a key is missing the default value is used.
-   * @return the Stochastic gradient descent optimizer
-   */
-  public static SGD create(Ops tf, Map config) {
-
-    String name = (String) config.get(NAME_KEY);
-    float learningRate = (float) config.getOrDefault(LEARNING_RATE_KEY, LEARNING_RATE_DEFAULT);
-    float momentum = (float) config.getOrDefault(MOMENTUM_KEY, MOMENTUM_DEFAULT);
-    boolean nesterov = (boolean) config.getOrDefault(NESTEROV_KEY, NESTEROV_DEFAULT);
-    if (name == null) {
-      return new SGD(tf, learningRate, momentum, nesterov);
-    } else {
-      return new SGD(tf, name, learningRate, momentum, nesterov);
-    }
-  }
-
-  /**
-   * Initialize the configuration ased on which constructor is called.
-   *
-   * @param learningRate learningRate The learning rate. Defaults to 0.01.
-   * @param momentum hyperparameter that accelerates SGD in the relevant direction and dampens
-   *     oscillations. Must be between [0, 1].
-   * @param useNesterov Whether to apply Nesterov momentum. Defaults to `false`.
-   */
-  private void initConfig(float learningRate, float momentum, boolean useNesterov) {
-    this.learningRate = learningRate;
-    config.put(NAME_KEY, this.getOptimizerName());
-    config.put(LEARNING_RATE_KEY, learningRate);
-    config.put(MOMENTUM_KEY, momentum);
-    config.put(NESTEROV_KEY, useNesterov);
-  }
-
-  /** { @inheritDoc } */
-  @Override
-  public Map getConfig() {
-    return config;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public float getLearningRate() {
-    return this.learningRate;
-  }
-
-  /** {@inheritDoc} */
-  @Override
-  public void setLearningRate(float learningRate) {
-    this.learningRate = learningRate;
-  }
-
-  // overide the momentum name to return "SGD"
-  /** {@inheritDoc} */
-  @Override
-  public String getOptimizerName() {
-    return "SGD";
-  }
-}

From ebefc2ea54b2f3d53b8b8f92912175eac50330d0 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Wed, 9 Sep 2020 16:17:37 -0400
Subject: [PATCH 31/33] Fixed generics

---
 .../op/nn/SoftmaxCrossEntropyWithLogits.java  | 48 +++++++++----------
 1 file changed, 24 insertions(+), 24 deletions(-)

diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
index 8447b985bb0..0c8bac697ed 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
@@ -64,52 +64,55 @@ public class SoftmaxCrossEntropyWithLogits {
    * @param logits Per-label activations, typically a linear output. These activation energies are
    *     interpreted as unnormalized log probabilities.
    * @param axis The class dimension. -1 is the last dimension.
-   * @param  the data type of the logits
    * @param  the number type of the operands
    * @return the softmax cross entropy loss. Its type is the same as logits and its
    *     shape is the same as labels except that it does not have the last dimension of
    *     labels.
    */
   @Endpoint(name = "softmaxCrossEntropyWithLogits")
-  public static  Operand softmaxCrossEntropyWithLogits(
-      Scope scope, Operand labels, Operand logits, int axis) {
+  public static  Operand softmaxCrossEntropyWithLogits(
+      Scope scope, Operand labels, Operand logits, int axis) {
     scope = scope.withSubScope("SoftmaxCrossEntropyWithLogits");
     axis = axis % logits.asOutput().shape().numDimensions();
     if (axis < 0) {
       axis += logits.asOutput().shape().numDimensions();
     }
 
-    Operand preciseLogits =
-        (Operand)
-            logits; // cannot use generics cause logits of bool gets cast to TFloat32
 
     boolean convertToFloat32 =
         logits.asOutput().dataType() == TFloat16.DTYPE
             || logits.asOutput().dataType() == TBfloat16.DTYPE;
     if (convertToFloat32) {
-      preciseLogits = Cast.create(scope, logits, TFloat32.DTYPE);
+      Operand result =  softmaxCrossEntropyWithLogits(scope,
+              Cast.create(scope, labels, TFloat32.DTYPE),
+              Cast.create(scope, logits, TFloat32.DTYPE),
+              axis);
+      return Cast.create(scope, result, logits.asOutput().dataType());
+    } else if(!logits.asOutput().dataType().equals(labels.asOutput().dataType())) {
+      return softmaxCrossEntropyWithLogits(scope,
+              Cast.create(scope, labels, logits.asOutput().dataType()),
+              logits,
+              axis);
     }
-    /* cannot use generics on DataType because preciseLogits may have been cast. */
-    DataType dtype = preciseLogits.asOutput().dataType();
-    Operand castLabels = Cast.create(scope, labels, dtype);
-    Operand inputRank = Cast.create(scope, Rank.create(scope, preciseLogits), TInt64.DTYPE);
+
+    Operand inputRank = Cast.create(scope, Rank.create(scope, logits), TInt64.DTYPE);
     Shape shape = logits.asOutput().shape();
 
     // Move the dim to the end if dim is not the last dimension.
-    if (axis != -1 && axis != preciseLogits.asOutput().shape().numDimensions() - 1) {
-      preciseLogits = moveDimToEnd(scope, preciseLogits, axis, inputRank);
-      castLabels = moveDimToEnd(scope, castLabels, axis, inputRank);
+    if (axis != -1 && axis != logits.asOutput().shape().numDimensions() - 1) {
+      logits = moveDimToEnd(scope, logits, axis, inputRank);
+      labels = moveDimToEnd(scope, labels, axis, inputRank);
     }
 
-    Shape inputShape = preciseLogits.asOutput().shape();
-    preciseLogits = flattenOuterDims(scope, preciseLogits);
-    castLabels = flattenOuterDims(scope, castLabels);
+    Shape inputShape = logits.asOutput().shape();
+    logits = flattenOuterDims(scope, logits);
+    labels = flattenOuterDims(scope, labels);
 
-    org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits smax =
+    org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits smax =
         org.tensorflow.op.nn.raw.SoftmaxCrossEntropyWithLogits.create(
-            scope, preciseLogits, castLabels);
+            scope, logits, (Operand)labels);
     /* cannot use generic on cost, because cost may be recast later. */
-    Operand cost = smax.loss();
+    Operand cost = smax.loss();
     Operand outputShape =
         Slice.create(
             scope,
@@ -132,9 +135,6 @@ public static  Operand softmaxCrossEntrop
       cost = Reshape.create(scope, cost, Constant.vectorOf(scope, newArray));
     }
 
-    if (convertToFloat32) {
-      cost = Cast.create(scope, cost, logits.asOutput().dataType());
-    }
     return cost;
   }
 
@@ -195,7 +195,7 @@ private static  Operand flattenOuterDims(Scope scope, Oper
    * @param  the data type of the rank
    * @return the reshaped input
    */
-  private static  Operand moveDimToEnd(
+  private static  Operand moveDimToEnd(
       Scope scope, Operand input, int dimIndex, Operand rank) {
     DataType rankDType = rank.asOutput().dataType();
     Operand one = Cast.create(scope, Constant.scalarOf(scope, 1), rankDType);

From 7915e6309e9db7a536cda24eac8264578cdbfe31 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Wed, 9 Sep 2020 19:03:09 -0400
Subject: [PATCH 32/33] Fixed from Unit test results

---
 .../annotations/org/tensorflow/op/NnOps.java  |   5 +-
 .../framework/optimizers/Optimizer.java       |   8 +
 .../framework/optimizers/Optimizers.java      |   2 +-
 .../framework/optimizers/AdaGradDATest.java   |  11 +-
 .../framework/optimizers/AdaGradTest.java     |  19 +-
 .../framework/optimizers/AdamTest.java        |  17 +-
 .../framework/optimizers/AdamaxTest.java      |   8 +-
 .../framework/utils/EagerTestSession.java     | 311 +++++---------
 .../framework/utils/GraphTestSession.java     | 382 ++++++------------
 .../framework/utils/TestSession.java          | 209 +++++-----
 10 files changed, 363 insertions(+), 609 deletions(-)

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 e15cccdd339..33caf02d890 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
@@ -1863,14 +1863,13 @@ public  Softmax softmax(Operand logits) {
    * @param logits Per-label activations, typically a linear output. These activation energies are
    *      interpreted as unnormalized log probabilities.
    * @param axis The class dimension. -1 is the last dimension.
-   * @param  the data type of the logits
    * @param  the number type of the operands
    * @return the softmax cross entropy loss. Its type is the same as logits and its
    *      shape is the same as labels except that it does not have the last dimension of
    *      labels.
    */
-  public  Operand softmaxCrossEntropyWithLogits(
-      Operand labels, Operand logits, int axis) {
+  public  Operand softmaxCrossEntropyWithLogits(
+      Operand labels, Operand logits, int axis) {
     return SoftmaxCrossEntropyWithLogits.softmaxCrossEntropyWithLogits(scope, labels, logits, axis);
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
index f7032d18b38..933a54c7670 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
@@ -71,6 +71,14 @@ protected Optimizer(Graph graph, String name) {
     this.globals = new ArrayList<>();
   }
 
+  /**
+   * Gets the Optimizer's Ops instance
+   * @return the Optimizer's Ops instance
+   */
+  public final Ops getTF() {
+    return tf;
+  }
+
   /**
    * Creates a name by combining a variable name and a slot name
    *
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java
index 7099a050d3e..8d7f9620984 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizers.java
@@ -15,7 +15,7 @@ public enum Optimizers {
   NADAM(Nadam::new),
   RMSPROP(RMSProp::new),
   MOMENTUM(Momentum::new),
-  GRADIENT_DESCENT(Momentum::new);
+  GRADIENT_DESCENT(GradientDescent::new);
 
   private final Function creator;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
index e1a12fb00fe..ef9053ff1eb 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
@@ -55,9 +55,13 @@ public void testBasic() {
     float[] grads0Init = {0.1F, 0.2F};
     float[] grads1Init = {0.01F, 0.02F};
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
       Graph graph = session.getGraph();
 
+      float learningRate = 3.0F;
+
+      AdaGradDA instance = new AdaGradDA(graph, learningRate);
+      Ops tf = instance.getTF();
+
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
@@ -70,13 +74,10 @@ public void testBasic() {
       Constant grads1 = tf.constant(grads1Init);
 
       /* initialize the local variables */
-      /* initialize the local variables */
+
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      float learningRate = 3.0F;
-
-      AdaGrad instance = new AdaGrad(graph, learningRate);
 
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
index efbdd7be585..c5ae178b84c 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
@@ -71,9 +71,12 @@ public void testBasic() {
     FloatNdArray accum1Np = NdArrays.vectorOf(accum1);
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
       Graph graph = session.getGraph();
 
+      float learningRate = 3.0F;
+      AdaGrad instance = new AdaGrad(graph, learningRate, 0.1f);
+      Ops tf = instance.getTF();
+
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
@@ -85,9 +88,7 @@ public void testBasic() {
       Constant grads0 = tf.constant(grads0Init);
       Constant grads1 = tf.constant(grads1Init);
 
-      float learningRate = 3.0F;
 
-      AdaGrad instance = new AdaGrad(graph, learningRate);
 
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
@@ -116,15 +117,11 @@ public void testBasic() {
 
       for (int step = 0; step < numSteps; step++) {
         session.run(adaUpdate);
-
-        accum0Np = caclulateAccum(accum0Np, grads0Np);
-        var0Np = calculate(var0Np, accum0Np, grads0Np, learningRate);
-        session.evaluate(var0Np, var0);
-
-        accum1Np = caclulateAccum(accum1Np, grads1Np);
-        var1Np = calculate(var1Np, accum1Np, grads1Np, learningRate);
-        session.evaluate(var1Np, var1);
       }
+      float[] expected0 = {-1.6026098728179932f, -0.6026098728179932f};
+      session.evaluate(expected0, var0);
+      float[] expected1 = {2.715679168701172f, 3.715679168701172f};
+      session.evaluate(expected1, var1);
     }
   }
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
index dbcc7c0dae2..1aeed5a9772 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
@@ -69,10 +69,15 @@ public void testBasic() {
     float epsilon1 = 1e-3F;
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
+      float learningRate = 0.001F;
+      float beta1 = 0.9F;
+      float beta2 = 0.999F;
       Graph graph = session.getGraph();
+
       session.setEpsilon(epsilon1);
 
+      Adam instance = new Adam(graph, learningRate);
+      Ops tf = instance.getTF();
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
@@ -88,16 +93,14 @@ public void testBasic() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      float learningRate = 0.001F;
-      float beta1 = 0.9F;
-      float beta2 = 0.999F;
+
 
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads0.asOutput(), var0.asOutput()));
       gradsAndVars.add(new Optimizer.GradAndVar<>(grads1.asOutput(), var1.asOutput()));
 
-      Adam instance = new Adam(graph, learningRate);
+
 
       Op update = instance.applyGradients(gradsAndVars, "AdamTest");
 
@@ -139,7 +142,7 @@ public void testBasic() {
             session
                 .getGraphSession()
                 .runner()
-                .fetch("beta1Power")
+                .fetch("beta1_power")
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
@@ -149,7 +152,7 @@ public void testBasic() {
             session
                 .getGraphSession()
                 .runner()
-                .fetch("beta2Power")
+                .fetch("beta2_power")
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
index 1b12a2f76a1..de17395f76a 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
@@ -94,9 +94,11 @@ public void testBasic() {
     float epsilon1 = 1e-3F;
 
     try (TestSession session = TestSession.createTestSession(tfMode)) {
-      Ops tf = session.getTF();
       Graph graph = session.getGraph();
 
+      Adamax instance = new Adamax(graph);
+      Ops tf = instance.getTF();
+
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
       Variable var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
@@ -112,7 +114,7 @@ public void testBasic() {
       session.run(var0Initializer);
       session.run(var1Initializer);
 
-      Adamax instance = new Adamax(graph);
+
       /* build the GradsAnvVars */
       List> gradsAndVars = new ArrayList<>();
       gradsAndVars.add(new GradAndVar<>(grads0.asOutput(), var0.asOutput()));
@@ -151,7 +153,7 @@ public void testBasic() {
             session
                 .getGraphSession()
                 .runner()
-                .fetch("beta1Power")
+                .fetch("beta1_power")
                 .run()
                 .get(0)
                 .expect(TFloat32.DTYPE)) {
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
index c52168e1f11..9fb9885505c 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
@@ -16,6 +16,7 @@
 
 import org.tensorflow.*;
 import org.tensorflow.ndarray.FloatNdArray;
+import org.tensorflow.ndarray.IntNdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.*;
@@ -29,7 +30,7 @@
 
 import static org.junit.jupiter.api.Assertions.*;
 
-/** Eaager Mode Test Session */
+/** Eager Mode Test Session */
 public class EagerTestSession extends TestSession {
 
   private final EagerSession session;
@@ -83,79 +84,47 @@ public EagerSession getEagerSession() {
   /** {@inheritDoc} */
   @Override
   public  void evaluate(double expected, Operand input) {
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     if (dtype == TFloat32.DTYPE) {
       Operand o = (Operand) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-                });
+            .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
       }
       index.set(0);
-      o.data()
-          .scalars()
-          .forEach(
-              f -> {
-                assertEquals(expected, f.getFloat(), epsilon);
-              });
+      o.data().scalars().forEach(f -> assertEquals(expected, f.getFloat(), epsilon));
     } else if (dtype == TFloat64.DTYPE) {
       Operand o = (Operand) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-                });
+            .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
       }
       index.set(0);
-      o.data()
-          .scalars()
-          .forEach(
-              f -> {
-                assertEquals((double) expected, f.getDouble(), epsilon);
-              });
+      o.data().scalars().forEach(f -> assertEquals(expected, f.getDouble(), epsilon));
     } else if (dtype == TInt32.DTYPE) {
       Operand o = (Operand) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-                });
+            .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
       }
       index.set(0);
-      o.data()
-          .scalars()
-          .forEach(
-              f -> {
-                assertEquals((int) expected, f.getInt());
-              });
+      o.data().scalars().forEach(f -> assertEquals((int) expected, f.getInt()));
     } else if (dtype == TInt64.DTYPE) {
       Operand o = (Operand) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-                });
+            .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
       }
       index.set(0);
-      o.data()
-          .scalars()
-          .forEach(
-              f -> {
-                assertEquals((long) expected, f.getLong());
-              });
+      o.data().scalars().forEach(f -> assertEquals((long) expected, f.getLong()));
     }
   }
 
@@ -167,160 +136,120 @@ public  void evaluate(Number[] expected, Output input) {
         expected.length,
         size,
         () -> String.format("expected length (%d) != to input length (%d)", expected.length, size));
-    DataType dtype = input.dataType();
+    DataType dtype = input.dataType();
     if (dtype == TFloat32.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-                });
+            .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
       }
       index.set(0);
       o.data()
           .scalars()
           .forEach(
-              f -> {
-                assertEquals(expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon);
-              });
+              f ->
+                  assertEquals(
+                      expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon));
     } else if (dtype == TFloat64.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-                });
+            .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
       }
       index.set(0);
       o.data()
           .scalars()
           .forEach(
-              f -> {
-                assertEquals(
-                    expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon);
-              });
+              f ->
+                  assertEquals(
+                      expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon));
     } else if (dtype == TInt32.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-                });
+            .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
       }
       index.set(0);
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt());
-              });
+          .forEach(f -> assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt()));
     } else if (dtype == TInt64.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-                });
+            .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
       }
       index.set(0);
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong());
-              });
+          .forEach(f -> assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong()));
     }
   }
 
   /** {@inheritDoc} */
   @Override
   public  void evaluate(FloatNdArray expected, Output input) {
-    DataType dtype = input.dataType();
+    DataType dtype = input.dataType();
     if (dtype == TFloat32.DTYPE) {
       Output o = (Output) input;
       AtomicLong index = new AtomicLong();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-                });
+            .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
       }
       index.set(0);
       o.data()
           .scalars()
           .forEach(
-              f -> {
-                assertEquals(expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon);
-              });
+              f -> assertEquals(expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon));
     } else if (dtype == TFloat64.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-                });
+            .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
       }
       index.set(0);
       o.data()
           .scalars()
           .forEach(
-              f -> {
-                assertEquals(
-                    (double) expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon);
-              });
+              f ->
+                  assertEquals(expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon));
     } else if (dtype == TInt32.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-                });
+            .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
       }
       index.set(0);
-      o.data()
-          .scalars()
-          .forEach(
-              f -> {
-                assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt());
-              });
+      for (IntNdArray f : o.data().scalars()) {
+        assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt());
+      }
     } else if (dtype == TInt64.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         o.data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-                });
+            .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
       }
       index.set(0);
       o.data()
           .scalars()
           .forEach(
-              f -> {
-                assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong());
-              });
+              f -> assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong()));
     }
   }
 
@@ -328,7 +257,7 @@ public  void evaluate(FloatNdArray expected, Output input) {
   @Override
   public  void evaluate(Output input, Predicate predicate) {
     AtomicInteger index = new AtomicInteger();
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     boolean isScalar = input.shape().equals(Shape.scalar());
     if (dtype == TFloat32.DTYPE) {
       Output o = (Output) input;
@@ -340,11 +269,10 @@ public  void evaluate(Output input, Predicate predic
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %b <==> %f\n",
-                        index.getAndIncrement(), predicate.test(f.getFloat()), f.getFloat());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %b <==> %f\n",
+                          index.getAndIncrement(), predicate.test(f.getFloat()), f.getFloat()));
         }
       }
       index.set(0);
@@ -353,10 +281,7 @@ public  void evaluate(Output input, Predicate predic
       } else {
         o.data()
             .scalars()
-            .forEachIndexed(
-                (idx, f) -> {
-                  assertTrue(predicate.test(o.data().getFloat()));
-                });
+            .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.data().getFloat())));
       }
     } else if (dtype == TFloat64.DTYPE) {
       Output o = (Output) input;
@@ -368,11 +293,10 @@ public  void evaluate(Output input, Predicate predic
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %b <==> %f\n",
-                        index.getAndIncrement(), predicate.test(f.getDouble()), f.getDouble());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %b <==> %f\n",
+                          index.getAndIncrement(), predicate.test(f.getDouble()), f.getDouble()));
         }
       }
       index.set(0);
@@ -381,10 +305,7 @@ public  void evaluate(Output input, Predicate predic
       } else {
         o.data()
             .scalars()
-            .forEachIndexed(
-                (idx, f) -> {
-                  assertTrue(predicate.test(o.data().getDouble()));
-                });
+            .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.data().getDouble())));
       }
     } else if (dtype == TInt32.DTYPE) {
       Output o = (Output) input;
@@ -396,11 +317,10 @@ public  void evaluate(Output input, Predicate predic
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %b <==> %d\n",
-                        index.getAndIncrement(), predicate.test(f.getInt()), f.getInt());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %b <==> %d\n",
+                          index.getAndIncrement(), predicate.test(f.getInt()), f.getInt()));
         }
       }
       index.set(0);
@@ -409,10 +329,7 @@ public  void evaluate(Output input, Predicate predic
       } else {
         o.data()
             .scalars()
-            .forEachIndexed(
-                (idx, f) -> {
-                  assertTrue(predicate.test(o.data().getInt()));
-                });
+            .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.data().getInt())));
       }
     } else if (dtype == TInt64.DTYPE) {
       Output o = (Output) input;
@@ -424,11 +341,10 @@ public  void evaluate(Output input, Predicate predic
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %b <==> %d\n",
-                        index.getAndIncrement(), predicate.test(f.getLong()), f.getLong());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %b <==> %d\n",
+                          index.getAndIncrement(), predicate.test(f.getLong()), f.getLong()));
         }
       }
       index.set(0);
@@ -437,10 +353,7 @@ public  void evaluate(Output input, Predicate predic
       } else {
         o.data()
             .scalars()
-            .forEachIndexed(
-                (idx, f) -> {
-                  assertTrue(predicate.test(o.data().getLong()));
-                });
+            .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.data().getLong())));
       }
     } else {
       fail("Unexpected DataType: " + dtype);
@@ -460,19 +373,13 @@ public void evaluate(String[] expected, Output input) {
       input
           .data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject());
-              });
+          .forEach(f -> System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject()));
     }
     index.set(0);
     input
         .data()
         .scalars()
-        .forEach(
-            f -> {
-              assertEquals(expected[index.getAndIncrement()], f.getObject());
-            });
+        .forEach(f -> assertEquals(expected[index.getAndIncrement()], f.getObject()));
   }
 
   /** {@inheritDoc} */
@@ -488,19 +395,13 @@ public void evaluate(Boolean[] expected, Output input) {
       input
           .data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean());
-              });
+          .forEach(f -> System.out.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()));
     }
     index.set(0);
     input
         .data()
         .scalars()
-        .forEach(
-            f -> {
-              assertEquals(expected[index.getAndIncrement()], f.getBoolean());
-            });
+        .forEach(f -> assertEquals(expected[index.getAndIncrement()], f.getBoolean()));
   }
 
   /** {@inheritDoc} */
@@ -508,9 +409,9 @@ public void evaluate(Boolean[] expected, Output input) {
   public  void evaluate(Output expected, Output input) {
     assert input.shape().equals(expected.shape())
         : String.format(
-            "expected shape (%s) != to input shape (%ds)",
+            "expected shape (%s) != to input shape (%s)",
             expected.shape().toString(), input.shape().toString());
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     boolean isScalar = input.shape().equals(Shape.scalar());
     if (dtype == TFloat32.DTYPE) {
       Output x = (Output) expected;
@@ -523,11 +424,10 @@ public  void evaluate(Output expected, Output input) {
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %f <==> %f\n",
-                        index.getAndIncrement(), x.data().getFloat(idx), f.getFloat());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %f <==> %f\n",
+                          index.getAndIncrement(), x.data().getFloat(idx), f.getFloat()));
         }
       }
       index.set(0);
@@ -550,11 +450,10 @@ public  void evaluate(Output expected, Output input) {
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %f <==> %f\n",
-                        index.getAndIncrement(), x.data().getDouble(idx), f.getDouble());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %f <==> %f\n",
+                          index.getAndIncrement(), x.data().getDouble(idx), f.getDouble()));
         }
       }
       index.set(0);
@@ -577,11 +476,10 @@ public  void evaluate(Output expected, Output input) {
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %d <==> %d\n",
-                        index.getAndIncrement(), x.data().getInt(idx), f.getInt());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %d <==> %d\n",
+                          index.getAndIncrement(), x.data().getInt(idx), f.getInt()));
         }
       }
       index.set(0);
@@ -603,11 +501,10 @@ public  void evaluate(Output expected, Output input) {
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %d  <==> %d\n",
-                        index.getAndIncrement(), x.data().getLong(idx), f.getLong());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %d  <==> %d\n",
+                          index.getAndIncrement(), x.data().getLong(idx), f.getLong()));
         }
       }
       index.set(0);
@@ -629,11 +526,10 @@ public  void evaluate(Output expected, Output input) {
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %s  <==> %s\n",
-                        index.getAndIncrement(), x.data().getObject(idx), f.getObject());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %s  <==> %s\n",
+                          index.getAndIncrement(), x.data().getObject(idx), f.getObject()));
         }
       }
       index.set(0);
@@ -655,11 +551,10 @@ public  void evaluate(Output expected, Output input) {
           o.data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    System.out.printf(
-                        "%d). %b  <==> %b\n",
-                        index.getAndIncrement(), x.data().getBoolean(idx), f.getBoolean());
-                  });
+                  (idx, f) ->
+                      System.out.printf(
+                          "%d). %b  <==> %b\n",
+                          index.getAndIncrement(), x.data().getBoolean(idx), f.getBoolean()));
         }
       }
       index.set(0);
@@ -676,61 +571,43 @@ public  void evaluate(Output expected, Output input) {
   /** {@inheritDoc} */
   @Override
   public  void print(PrintWriter writer, Output input) {
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     if (dtype == TFloat32.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-              });
+          .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
     } else if (dtype == TFloat64.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-              });
+          .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
     } else if (dtype == TInt32.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-              });
+          .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
     } else if (dtype == TInt64.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-              });
+          .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
     } else if (dtype == TString.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject());
-              });
+          .forEach(f -> System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject()));
     } else if (dtype == TBool.DTYPE) {
       Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       o.data()
           .scalars()
-          .forEach(
-              f -> {
-                System.out.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean());
-              });
+          .forEach(f -> System.out.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()));
     } else {
       writer.println("Unexpected DataType: " + dtype);
     }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
index 3231b0f50cd..0416267ae59 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
@@ -92,12 +92,7 @@ public EagerSession getEagerSession() {
   /** {@inheritDoc} */
   @Override
   public void initialize() {
-    graph
-        .initializers()
-        .forEach(
-            initializer -> {
-              session.runner().addTarget(initializer).run();
-            });
+    graph.initializers().forEach(initializer -> session.runner().addTarget(initializer).run());
   }
 
   /** {@inheritDoc} */
@@ -109,7 +104,7 @@ public void run(Op op) {
   /** {@inheritDoc} */
   @Override
   public  void evaluate(double expected, Operand input) {
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     if (dtype == TFloat32.DTYPE) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -118,22 +113,13 @@ public  void evaluate(double expected, Operand input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-                  });
+              .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
         }
       }
       index.set(0);
       try (Tensor result =
           this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat32.DTYPE)) {
-        result
-            .data()
-            .scalars()
-            .forEach(
-                f -> {
-                  assertEquals((float) expected, f.getFloat(), epsilon);
-                });
+        result.data().scalars().forEach(f -> assertEquals((float) expected, f.getFloat(), epsilon));
       }
     } else if (dtype == TFloat64.DTYPE) {
       AtomicInteger index = new AtomicInteger();
@@ -143,22 +129,13 @@ public  void evaluate(double expected, Operand input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-                  });
+              .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
         }
       }
       index.set(0);
       try (Tensor result =
           this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) {
-        result
-            .data()
-            .scalars()
-            .forEach(
-                f -> {
-                  assertEquals(expected, f.getDouble(), epsilon);
-                });
+        result.data().scalars().forEach(f -> assertEquals(expected, f.getDouble(), epsilon));
       }
     } else if (dtype == TInt32.DTYPE) {
       AtomicInteger index = new AtomicInteger();
@@ -168,25 +145,15 @@ public  void evaluate(double expected, Operand input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-                  });
+              .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
         }
       }
       index.set(0);
       try (Tensor result =
           this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) {
-        result
-            .data()
-            .scalars()
-            .forEach(
-                f -> {
-                  assertEquals((int) expected, f.getInt());
-                });
+        result.data().scalars().forEach(f -> assertEquals((int) expected, f.getInt()));
       }
     } else if (dtype == TInt64.DTYPE) {
-      Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (Tensor result =
@@ -194,22 +161,13 @@ public  void evaluate(double expected, Operand input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-                  });
+              .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
         }
       }
       index.set(0);
       try (Tensor result =
           this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) {
-        result
-            .data()
-            .scalars()
-            .forEach(
-                f -> {
-                  assertEquals((long) expected, f.getLong());
-                });
+        result.data().scalars().forEach(f -> assertEquals((long) expected, f.getLong()));
       }
     } else {
       fail("Unexpected DataType: " + dtype);
@@ -224,7 +182,7 @@ public  void evaluate(Number[] expected, Output input) {
         expected.length,
         size,
         () -> String.format("expected length (%d) != to input length (%d)", expected.length, size));
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     if (dtype == TFloat32.DTYPE) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -233,10 +191,7 @@ public  void evaluate(Number[] expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-                  });
+              .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
         }
       }
       index.set(0);
@@ -246,10 +201,9 @@ public  void evaluate(Number[] expected, Output input) {
             .data()
             .scalars()
             .forEach(
-                f -> {
-                  assertEquals(
-                      expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon);
-                });
+                f ->
+                    assertEquals(
+                        expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon));
       }
     } else if (dtype == TFloat64.DTYPE) {
       AtomicInteger index = new AtomicInteger();
@@ -259,10 +213,7 @@ public  void evaluate(Number[] expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-                  });
+              .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
         }
       }
       index.set(0);
@@ -272,10 +223,9 @@ public  void evaluate(Number[] expected, Output input) {
             .data()
             .scalars()
             .forEach(
-                f -> {
-                  assertEquals(
-                      expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon);
-                });
+                f ->
+                    assertEquals(
+                        expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon));
       }
     } else if (dtype == TInt32.DTYPE) {
       AtomicInteger index = new AtomicInteger();
@@ -285,10 +235,7 @@ public  void evaluate(Number[] expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-                  });
+              .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
         }
       }
       index.set(0);
@@ -297,13 +244,9 @@ public  void evaluate(Number[] expected, Output input) {
         result
             .data()
             .scalars()
-            .forEach(
-                f -> {
-                  assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt());
-                });
+            .forEach(f -> assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt()));
       }
     } else if (dtype == TInt64.DTYPE) {
-      Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (Tensor result =
@@ -311,10 +254,7 @@ public  void evaluate(Number[] expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-                  });
+              .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
         }
       }
       index.set(0);
@@ -323,10 +263,7 @@ public  void evaluate(Number[] expected, Output input) {
         result
             .data()
             .scalars()
-            .forEach(
-                f -> {
-                  assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong());
-                });
+            .forEach(f -> assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong()));
       }
     } else {
       fail("Unexpected DataType: " + dtype);
@@ -336,7 +273,7 @@ public  void evaluate(Number[] expected, Output input) {
   /** {@inheritDoc} */
   @Override
   public  void evaluate(FloatNdArray expected, Output input) {
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     if (dtype == TFloat32.DTYPE) {
       AtomicLong index = new AtomicLong();
       if (debug) {
@@ -345,10 +282,7 @@ public  void evaluate(FloatNdArray expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-                  });
+              .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
         }
       }
       index.set(0);
@@ -358,9 +292,9 @@ public  void evaluate(FloatNdArray expected, Output input) {
             .data()
             .scalars()
             .forEach(
-                f -> {
-                  assertEquals(expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon);
-                });
+                f ->
+                    assertEquals(
+                        expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon));
       }
     } else if (dtype == TFloat64.DTYPE) {
       AtomicInteger index = new AtomicInteger();
@@ -370,10 +304,7 @@ public  void evaluate(FloatNdArray expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-                  });
+              .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
         }
       }
       index.set(0);
@@ -383,10 +314,9 @@ public  void evaluate(FloatNdArray expected, Output input) {
             .data()
             .scalars()
             .forEach(
-                f -> {
-                  assertEquals(
-                      (double) expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon);
-                });
+                f ->
+                    assertEquals(
+                        expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon));
       }
     } else if (dtype == TInt32.DTYPE) {
       AtomicInteger index = new AtomicInteger();
@@ -396,10 +326,7 @@ public  void evaluate(FloatNdArray expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-                  });
+              .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
         }
       }
       index.set(0);
@@ -409,12 +336,9 @@ public  void evaluate(FloatNdArray expected, Output input) {
             .data()
             .scalars()
             .forEach(
-                f -> {
-                  assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt());
-                });
+                f -> assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt()));
       }
     } else if (dtype == TInt64.DTYPE) {
-      Output o = (Output) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (Tensor result =
@@ -422,10 +346,7 @@ public  void evaluate(FloatNdArray expected, Output input) {
           result
               .data()
               .scalars()
-              .forEach(
-                  f -> {
-                    System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-                  });
+              .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
         }
       }
       index.set(0);
@@ -435,9 +356,7 @@ public  void evaluate(FloatNdArray expected, Output input) {
             .data()
             .scalars()
             .forEach(
-                f -> {
-                  assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong());
-                });
+                f -> assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong()));
       }
     } else {
       fail("Unexpected DataType: " + dtype);
@@ -459,10 +378,7 @@ public void evaluate(String[] expected, Output input) {
         result
             .data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject());
-                });
+            .forEach(f -> System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject()));
       }
     }
     index.set(0);
@@ -471,10 +387,7 @@ public void evaluate(String[] expected, Output input) {
       result
           .data()
           .scalars()
-          .forEach(
-              f -> {
-                assertEquals(expected[index.getAndIncrement()], f.getObject());
-              });
+          .forEach(f -> assertEquals(expected[index.getAndIncrement()], f.getObject()));
     }
   }
 
@@ -493,10 +406,7 @@ public void evaluate(Boolean[] expected, Output input) {
         result
             .data()
             .scalars()
-            .forEach(
-                f -> {
-                  System.out.printf("%d). %b\n", index.getAndIncrement(), f.getObject());
-                });
+            .forEach(f -> System.out.printf("%d). %b\n", index.getAndIncrement(), f.getObject()));
       }
     }
     index.set(0);
@@ -505,10 +415,7 @@ public void evaluate(Boolean[] expected, Output input) {
       result
           .data()
           .scalars()
-          .forEach(
-              f -> {
-                assertEquals(expected[index.getAndIncrement()], f.getObject());
-              });
+          .forEach(f -> assertEquals(expected[index.getAndIncrement()], f.getObject()));
     }
   }
 
@@ -517,10 +424,16 @@ public void evaluate(Boolean[] expected, Output input) {
   public  void evaluate(Output expected, Output input) {
     assert input.shape().equals(expected.shape())
         : String.format(
-            "expected shape (%s) != to input shape (%ds)",
+            "expected shape (%s) != to input shape (%s)",
             expected.shape().toString(), input.shape().toString());
     AtomicInteger index = new AtomicInteger();
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
+    if (!dtype.equals(expected.dataType())) {
+      throw new IllegalArgumentException(
+          String.format(
+              "Both data type must be equal, inout = %s, expected = %s",
+              dtype, expected.dataType()));
+    }
     boolean isScalar = input.shape().equals(Shape.scalar());
     if (dtype == TFloat32.DTYPE) {
       final Output finalExpected = (Output) expected;
@@ -537,13 +450,12 @@ public  void evaluate(Output expected, Output input) {
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %f <==> %f\n",
-                          index.getAndIncrement(),
-                          finalExpected.data().getFloat(idx),
-                          f.getFloat());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %f <==> %f\n",
+                            index.getAndIncrement(),
+                            finalExpected.data().getFloat(idx),
+                            f.getFloat()));
           }
         }
       }
@@ -559,9 +471,8 @@ public  void evaluate(Output expected, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    assertEquals(expectedResult.data().getFloat(idx), f.getFloat(), epsilon);
-                  });
+                  (idx, f) ->
+                      assertEquals(expectedResult.data().getFloat(idx), f.getFloat(), epsilon));
         }
       }
     } else if (dtype == TFloat64.DTYPE) {
@@ -579,13 +490,12 @@ public  void evaluate(Output expected, Output input) {
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %f <==> %f\n",
-                          index.getAndIncrement(),
-                          finalExpected.data().getDouble(idx),
-                          f.getDouble());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %f <==> %f\n",
+                            index.getAndIncrement(),
+                            finalExpected.data().getDouble(idx),
+                            f.getDouble()));
           }
         }
       }
@@ -601,9 +511,8 @@ public  void evaluate(Output expected, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    assertEquals(expectedResult.data().getDouble(idx), f.getDouble(), epsilon);
-                  });
+                  (idx, f) ->
+                      assertEquals(expectedResult.data().getDouble(idx), f.getDouble(), epsilon));
         }
       }
     } else if (dtype == TInt32.DTYPE) {
@@ -621,11 +530,10 @@ public  void evaluate(Output expected, Output input) {
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %d <==> %d\n",
-                          index.getAndIncrement(), finalExpected.data().getInt(idx), f.getInt());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %d <==> %d\n",
+                            index.getAndIncrement(), finalExpected.data().getInt(idx), f.getInt()));
           }
         }
       }
@@ -641,9 +549,7 @@ public  void evaluate(Output expected, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    assertEquals(expectedResult.data().getInt(idx), f.getInt(), epsilon);
-                  });
+                  (idx, f) -> assertEquals(expectedResult.data().getInt(idx), f.getInt(), epsilon));
         }
       }
     } else if (dtype == TInt64.DTYPE) {
@@ -661,11 +567,12 @@ public  void evaluate(Output expected, Output input) {
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %d <==> %d\n",
-                          index.getAndIncrement(), finalExpected.data().getLong(idx), f.getLong());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %d <==> %d\n",
+                            index.getAndIncrement(),
+                            finalExpected.data().getLong(idx),
+                            f.getLong()));
           }
         }
       }
@@ -681,9 +588,8 @@ public  void evaluate(Output expected, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    assertEquals(expectedResult.data().getLong(idx), f.getLong(), epsilon);
-                  });
+                  (idx, f) ->
+                      assertEquals(expectedResult.data().getLong(idx), f.getLong(), epsilon));
         }
       }
     } else if (dtype == TBool.DTYPE) {
@@ -701,13 +607,12 @@ public  void evaluate(Output expected, Output input) {
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %b <==> %b\n",
-                          index.getAndIncrement(),
-                          finalExpected.data().getBoolean(idx),
-                          f.getBoolean());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %b <==> %b\n",
+                            index.getAndIncrement(),
+                            finalExpected.data().getBoolean(idx),
+                            f.getBoolean()));
           }
         }
       }
@@ -723,9 +628,7 @@ public  void evaluate(Output expected, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    assertEquals(expectedResult.data().getBoolean(idx), f.getBoolean());
-                  });
+                  (idx, f) -> assertEquals(expectedResult.data().getBoolean(idx), f.getBoolean()));
         }
       }
     } else if (dtype == TString.DTYPE) {
@@ -743,13 +646,12 @@ public  void evaluate(Output expected, Output input) {
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %s <==> %s\n",
-                          index.getAndIncrement(),
-                          finalExpected.data().getObject(idx),
-                          f.getObject());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %s <==> %s\n",
+                            index.getAndIncrement(),
+                            finalExpected.data().getObject(idx),
+                            f.getObject()));
           }
         }
       }
@@ -765,9 +667,7 @@ public  void evaluate(Output expected, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    assertEquals(expectedResult.data().getObject(idx), f.getObject());
-                  });
+                  (idx, f) -> assertEquals(expectedResult.data().getObject(idx), f.getObject()));
         }
       }
     } else {
@@ -779,7 +679,7 @@ public  void evaluate(Output expected, Output input) {
   @Override
   public  void evaluate(Output input, Predicate predicate) {
     AtomicInteger index = new AtomicInteger();
-    DataType dtype = input.asOutput().dataType();
+    DataType dtype = input.asOutput().dataType();
     boolean isScalar = input.shape().equals(Shape.scalar());
     if (dtype == TFloat32.DTYPE) {
       if (debug) {
@@ -794,11 +694,10 @@ public  void evaluate(Output input, Predicate predic
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %b <==> %f\n",
-                          index.getAndIncrement(), predicate.test(f.getFloat()), f.getFloat());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %b <==> %f\n",
+                            index.getAndIncrement(), predicate.test(f.getFloat()), f.getFloat()));
           }
         }
       }
@@ -811,10 +710,7 @@ public  void evaluate(Output input, Predicate predic
           result
               .data()
               .scalars()
-              .forEachIndexed(
-                  (idx, f) -> {
-                    assertTrue(predicate.test(result.data().getFloat()));
-                  });
+              .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.data().getFloat())));
         }
       }
     } else if (dtype == TFloat64.DTYPE) {
@@ -830,29 +726,23 @@ public  void evaluate(Output input, Predicate predic
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %b <==> %f\n",
-                          index.getAndIncrement(), predicate.test(f.getDouble()), f.getDouble());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %b <==> %f\n",
+                            index.getAndIncrement(), predicate.test(f.getDouble()), f.getDouble()));
           }
         }
       }
       index.set(0);
       try (Tensor result =
-              this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE);
-          Tensor expectedResult =
-              this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) {
+          this.getGraphSession().runner().fetch(input).run().get(0).expect(TFloat64.DTYPE)) {
         if (isScalar) {
           assertTrue(predicate.test(result.data().getDouble()));
         } else {
           result
               .data()
               .scalars()
-              .forEachIndexed(
-                  (idx, f) -> {
-                    assertTrue(predicate.test(result.data().getDouble()));
-                  });
+              .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.data().getDouble())));
         }
       }
     } else if (dtype == TInt32.DTYPE) {
@@ -867,29 +757,23 @@ public  void evaluate(Output input, Predicate predic
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %b <==> %d\n",
-                          index.getAndIncrement(), predicate.test(f.getInt()), f.getInt());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %b <==> %d\n",
+                            index.getAndIncrement(), predicate.test(f.getInt()), f.getInt()));
           }
         }
       }
       index.set(0);
       try (Tensor result =
-              this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE);
-          Tensor expectedResult =
-              this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) {
+          this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) {
         if (isScalar) {
           assertTrue(predicate.test(result.data().getInt()));
         } else {
           result
               .data()
               .scalars()
-              .forEachIndexed(
-                  (idx, f) -> {
-                    assertTrue(predicate.test(result.data().getInt()));
-                  });
+              .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.data().getInt())));
         }
       }
     } else if (dtype == TInt64.DTYPE) {
@@ -905,29 +789,23 @@ public  void evaluate(Output input, Predicate predic
                 .data()
                 .scalars()
                 .forEachIndexed(
-                    (idx, f) -> {
-                      System.out.printf(
-                          "%d). %b <==> %d\n",
-                          index.getAndIncrement(), predicate.test(f.getLong()), f.getLong());
-                    });
+                    (idx, f) ->
+                        System.out.printf(
+                            "%d). %b <==> %d\n",
+                            index.getAndIncrement(), predicate.test(f.getLong()), f.getLong()));
           }
         }
       }
       index.set(0);
       try (Tensor result =
-              this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE);
-          Tensor expectedResult =
-              this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) {
+          this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) {
         if (isScalar) {
           assertTrue(predicate.test(result.data().getLong()));
         } else {
           result
               .data()
               .scalars()
-              .forEachIndexed(
-                  (idx, f) -> {
-                    assertTrue(predicate.test(result.data().getLong()));
-                  });
+              .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.data().getLong())));
         }
       }
     } else {
@@ -940,7 +818,7 @@ public  void evaluate(Output input, Predicate predic
   public  void print(PrintWriter writer, Output input) {
     boolean isScalar = input.asOutput().shape().size() == 1;
 
-    DataType dtype = input.dataType();
+    DataType dtype = input.dataType();
     if (dtype == TFloat32.DTYPE) {
       AtomicInteger index = new AtomicInteger();
       try (Tensor result =
@@ -952,9 +830,7 @@ public  void print(PrintWriter writer, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    writer.printf("%d). %f\n", index.getAndIncrement(), f.getFloat());
-                  });
+                  (idx, f) -> writer.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
         }
       }
     } else if (dtype == TFloat64.DTYPE) {
@@ -970,9 +846,7 @@ public  void print(PrintWriter writer, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    writer.printf("%d). %f\n", index.getAndIncrement(), f.getDouble());
-                  });
+                  (idx, f) -> writer.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
         }
       }
     } else if (dtype == TInt32.DTYPE) {
@@ -982,15 +856,13 @@ public  void print(PrintWriter writer, Output input) {
           this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt32.DTYPE)) {
         if (isScalar) {
           writer.printf(
-              "%d). %f\n", index.getAndIncrement(), ((Output) input).data().getInt());
+              "%d). %d\n", index.getAndIncrement(), ((Output) input).data().getInt());
         } else {
           result
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    writer.printf("%d). %d\n", index.getAndIncrement(), f.getInt());
-                  });
+                  (idx, f) -> writer.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
         }
       }
     } else if (dtype == TInt64.DTYPE) {
@@ -1000,15 +872,13 @@ public  void print(PrintWriter writer, Output input) {
           this.getGraphSession().runner().fetch(input).run().get(0).expect(TInt64.DTYPE)) {
         if (isScalar) {
           writer.printf(
-              "%d). %f\n", index.getAndIncrement(), ((Output) input).data().getLong());
+              "%d). %d\n", index.getAndIncrement(), ((Output) input).data().getLong());
         } else {
           result
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    writer.printf("%d). %d\n", index.getAndIncrement(), f.getLong());
-                  });
+                  (idx, f) -> writer.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
         }
       }
     } else if (dtype == TBool.DTYPE) {
@@ -1024,9 +894,7 @@ public  void print(PrintWriter writer, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    writer.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean());
-                  });
+                  (idx, f) -> writer.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()));
         }
       }
     } else if (dtype == TString.DTYPE) {
@@ -1042,9 +910,7 @@ public  void print(PrintWriter writer, Output input) {
               .data()
               .scalars()
               .forEachIndexed(
-                  (idx, f) -> {
-                    writer.printf("%d). %s\n", index.getAndIncrement(), f.getObject());
-                  });
+                  (idx, f) -> writer.printf("%d). %s\n", index.getAndIncrement(), f.getObject()));
         }
       }
     } else {
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/TestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/TestSession.java
index 3758c832db5..a0855eb6260 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/TestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/TestSession.java
@@ -40,11 +40,11 @@ public abstract class TestSession implements AutoCloseable {
   /** The Test Session mode, either Eager or Graph */
   public enum Mode {
     EAGER,
-    GRAPH;
+    GRAPH
   }
 
   /**
-   * Create an Eager Test Session
+   * Creates an Eager Test Session
    *
    * @return the Eager Test Session
    */
@@ -53,7 +53,7 @@ public static TestSession createEagerSession() {
   }
 
   /**
-   * Create a Graph Test Session
+   * Creates a Graph Test Session
    *
    * @return the Graph Test Session
    */
@@ -62,22 +62,22 @@ public static TestSession createGraphSession() {
   }
 
   /**
-   * Create a Test Session
+   * Creates a Test Session
    *
-   * @param mode
-   * @return
+   * @param mode the type of Session, either eager or graph
+   * @return returns the test session
    */
   public static TestSession createTestSession(Mode mode) {
     return mode == Mode.EAGER ? createEagerSession() : createGraphSession();
   }
 
-  /** Initialize the Test Session, default implementation is do nothing. */
+  /** Initializes the Test Session, default implementation is do nothing. */
   public void initialize() {
     // empty
   }
 
   /**
-   * Run the Operation
+   * Runs the Operation
    *
    * @param op the Operation to run
    */
@@ -86,7 +86,7 @@ public void run(Op op) {
   }
 
   /**
-   * Get the Graph
+   * Gets the Graph
    *
    * @return the graph if in Graph Mode, otherwise null.
    */
@@ -95,120 +95,118 @@ public Graph getGraph() {
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(Number expected, Operand input) {
     evaluate(new Number[] {expected}, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
-  public  void evaluate(Number expected, Op input) {
+  public void evaluate(Number expected, Op input) {
     evaluate(new Number[] {expected}, input);
   }
 
   /**
-   * Evaluate the input against the expected values
+   * Evaluates the input against the expected values
    *
    * @param expected the expected values
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
-  public  void evaluate(Number[] expected, Op input) {
-    Output output = input.op().output(0);
+  public void evaluate(Number[] expected, Op input) {
+    Output output = input.op().output(0);
     evaluate(expected, output);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(Number[] expected, Operand input) {
-    Output output = input.asOutput();
+    Output output = input.asOutput();
     evaluate(expected, output);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(byte expected, Operand input) {
     evaluate((double) expected, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(int expected, Operand input) {
     evaluate((double) expected, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(long expected, Operand input) {
     evaluate((double) expected, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(float expected, Operand input) {
     evaluate((double) expected, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public abstract  void evaluate(double expected, Operand input);
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(byte[] expected, Operand input) {
     Byte[] iArray = new Byte[expected.length];
@@ -217,12 +215,12 @@ public  void evaluate(byte[] expected, Operand input) {
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(int[] expected, Operand input) {
     Integer[] iArray = new Integer[expected.length];
@@ -231,12 +229,12 @@ public  void evaluate(int[] expected, Operand input) {
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(long[] expected, Operand input) {
     Long[] iArray = new Long[expected.length];
@@ -245,12 +243,12 @@ public  void evaluate(long[] expected, Operand input) {
   }
 
   /**
-   * Evaluate the input against the expected values
+   * Evaluates the input against the expected values
    *
    * @param expected the expected values
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(float[] expected, Operand input) {
     Float[] iArray = new Float[expected.length];
@@ -259,12 +257,12 @@ public  void evaluate(float[] expected, Operand input) {
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(double[] expected, Operand input) {
     Double[] iArray = new Double[expected.length];
@@ -273,207 +271,212 @@ public  void evaluate(double[] expected, Operand input) {
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public abstract  void evaluate(Number[] expected, Output input);
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(String expected, Operand input) {
     evaluate(new String[] {expected}, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(String expected, Op input) {
     evaluate(new String[] {expected}, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(String[] expected, Op input) {
-    Output output = input.op().output(0);
+    Output output = input.op().output(0);
     evaluate(expected, output);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(String[] expected, Operand input) {
-    Output output = input.asOutput();
+    Output output = input.asOutput();
     evaluate(expected, output);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public abstract void evaluate(String[] expected, Output input);
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(Boolean expected, Operand input) {
     evaluate(new Boolean[] {expected}, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(Boolean expected, Op input) {
     evaluate(new Boolean[] {expected}, input);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(Boolean[] expected, Op input) {
-    Output output = input.op().output(0);
+    Output output = input.op().output(0);
     evaluate(expected, output);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public void evaluate(Boolean[] expected, Operand input) {
-    Output output = input.asOutput();
+    Output output = input.asOutput();
     evaluate(expected, output);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public abstract void evaluate(Boolean[] expected, Output input);
 
+  /**
+   * Evaluates the input against the expected value
+   *
+   * @param expected the expected value
+   * @param input the operand to evaluate
+   * @param  the data type of the expected Operand
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
+   */
   public  void evaluate(Operand expected, Op input) {
-    Output output = input.op().output(0);
+    Output output = input.op().output(0);
     evaluate(expected, output);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(Operand expected, Operand input) {
     evaluate(expected.asOutput(), input.asOutput());
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public abstract  void evaluate(Output expected, Output input);
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public  void evaluate(FloatNdArray expected, Operand input) {
     evaluate(expected, input.asOutput());
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
    * @param expected the expected value
    * @param input the operand to evaluate
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public abstract  void evaluate(FloatNdArray expected, Output input);
 
+  /**
+   * Evaluates the input against the expected value
+   *
+   * @param input the operand to evaluate
+   * @param predicate the Predicate
+   * @param  the data type of the input
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
+   */
   public  void evaluate(Operand input, Predicate predicate) {
     evaluate(input.asOutput(), predicate);
   }
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
-   * @param expected the expected value
    * @param input the operand to evaluate
+   * @param predicate The Predicate that evaluates the each value from input
    * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
   public abstract  void evaluate(Output input, Predicate predicate);
 
   /**
-   * Evaluate the input against the expected value
+   * Evaluates the input against the expected value
    *
-   * @param expected the expected value
    * @param input the operand to evaluate
-   * @param  the data type of the input
-   * @throws org.opentest4j.AssertionFailedError
+   * @param predicate The Predicate that evaluates the each value from input
+   * @throws org.opentest4j.AssertionFailedError if the evaluation fails
    */
-  public  void evaluate(FloatNdArray input, Predicate predicate) {
+  public void evaluate(FloatNdArray input, Predicate predicate) {
     input.scalars().forEach(f -> assertTrue(predicate.test(f.getFloat())));
   }
 
@@ -493,9 +496,8 @@ public  void print(OutputStream out, Operand input) {
    *
    * @param out the output stream
    * @param input the op to print
-   * @param  the data type of the input
    */
-  public  void print(OutputStream out, Op input) {
+  public void print(OutputStream out, Op input) {
     print(new PrintWriter(new OutputStreamWriter(out)), input.op().output(0));
   }
 
@@ -513,7 +515,7 @@ public  void print(OutputStream out, Output input) {
   /**
    * Print the input
    *
-   * @param witer the output writer
+   * @param writer the output writer
    * @param input the operand to print
    * @param  the data type of the input
    */
@@ -524,18 +526,17 @@ public  void print(Writer writer, Operand input) {
   /**
    * Print the input
    *
-   * @param witer the output writer
+   * @param writer the output writer
    * @param input the op to print
-   * @param  the data type of the input
    */
-  public  void print(Writer writer, Op input) {
+  public void print(Writer writer, Op input) {
     print(new PrintWriter(writer), input.op().output(0));
   }
 
   /**
    * Print the input
    *
-   * @param witer the output writer
+   * @param writer the output writer
    * @param input the op to print
    * @param  the data type of the input
    */
@@ -546,7 +547,7 @@ public  void print(Writer writer, Output input) {
   /**
    * Print the input
    *
-   * @param witer the output writer
+   * @param writer the output writer
    * @param input the op to print
    */
   public abstract  void print(PrintWriter writer, Output input);

From ec4f6790ff666a4c23f60e1b4764874d6167d392 Mon Sep 17 00:00:00 2001
From: Jim Clarke 
Date: Wed, 9 Sep 2020 19:08:41 -0400
Subject: [PATCH 33/33] added @SuppressWarnings("unchecked") on Variable array

---
 .../test/java/org/tensorflow/framework/optimizers/AdamTest.java | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
index 1aeed5a9772..461fa75397f 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
@@ -105,7 +105,9 @@ public void testBasic() {
       Op update = instance.applyGradients(gradsAndVars, "AdamTest");
 
       /* Create and validate the shapes of the slots */
+      @SuppressWarnings("unchecked")
       Variable[] firstMomentSlots = new Variable[2];
+      @SuppressWarnings("unchecked")
       Variable[] secondMomentSlots = new Variable[2];
 
       firstMomentSlots[0] = instance.getSlot(var0.asOutput(), FIRST_MOMENT).get();