contents) {
}
/**
- * Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
- * Detects whether an image is a BMP, GIF, JPEG, or PNG, and performs the
+ * Function for decode_bmp, decode_gif, decode_jpeg, decode_webp, and decode_png.
+ * Detects whether an image is a BMP, GIF, JPEG, WebP, or PNG, and performs the
* appropriate operation to convert the input bytes string into a Tensor of type
* dtype.
- * NOTE: decode_gif returns a 4-D array [num_frames, height, width, 3], as
- * opposed to decode_bmp, decode_jpeg and decode_png, which return 3-D arrays
- * [height, width, num_channels]. Make sure to take this into account when
- * constructing your graph if you are intermixing GIF files with BMP, JPEG, and/or
- * PNG files. Alternately, set the expand_animations argument of this function to
- * False, in which case the op will return 3-dimensional tensors and will truncate
- * animated GIF files to the first frame.
+ *
NOTE: decode_gif and decode_webp return a 4-D
+ * array [num_frames, height, width, 3], as opposed to decode_bmp,
+ * decode_jpeg, and decode_png, which always return 3-D arrays [height,
+ * width, num_channels]. Make sure to take this into account when
+ * constructing your graph if you are intermixing animated files with
+ * BMP, JPEG, and/or PNG files. Alternately, set the expand_animations
+ * argument of this function to False, in which case the op will return
+ * 3-dimensional tensors and will truncate animations to the first frame.
*
NOTE: If the first frame of an animated GIF does not occupy the entire
* canvas (maximum frame width x maximum frame height), then it fills the
* unoccupied areas (in the first frame) with zeros (black). For frames after the
@@ -357,22 +359,24 @@ public DecodeGif decodeGif(Operand contents) {
* @param options carries optional attribute values
* @return a new instance of DecodeImage, with default output types
*/
- public DecodeImage decodeImage(Operand contents, DecodeImage.Options[] options) {
+ public DecodeImage decodeImage(Operand contents,
+ DecodeImage.Options... options) {
return DecodeImage.create(scope, contents, options);
}
/**
- * Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
- * Detects whether an image is a BMP, GIF, JPEG, or PNG, and performs the
+ * Function for decode_bmp, decode_gif, decode_jpeg, decode_webp, and decode_png.
+ * Detects whether an image is a BMP, GIF, JPEG, WebP, or PNG, and performs the
* appropriate operation to convert the input bytes string into a Tensor of type
* dtype.
- * NOTE: decode_gif returns a 4-D array [num_frames, height, width, 3], as
- * opposed to decode_bmp, decode_jpeg and decode_png, which return 3-D arrays
- * [height, width, num_channels]. Make sure to take this into account when
- * constructing your graph if you are intermixing GIF files with BMP, JPEG, and/or
- * PNG files. Alternately, set the expand_animations argument of this function to
- * False, in which case the op will return 3-dimensional tensors and will truncate
- * animated GIF files to the first frame.
+ *
NOTE: decode_gif and decode_webp return a 4-D
+ * array [num_frames, height, width, 3], as opposed to decode_bmp,
+ * decode_jpeg, and decode_png, which always return 3-D arrays [height,
+ * width, num_channels]. Make sure to take this into account when
+ * constructing your graph if you are intermixing animated files with
+ * BMP, JPEG, and/or PNG files. Alternately, set the expand_animations
+ * argument of this function to False, in which case the op will return
+ * 3-dimensional tensors and will truncate animations to the first frame.
*
NOTE: If the first frame of an animated GIF does not occupy the entire
* canvas (maximum frame width x maximum frame height), then it fills the
* unoccupied areas (in the first frame) with zeros (black). For frames after the
@@ -436,7 +440,7 @@ public DecodeJpeg decodeJpeg(Operand contents, DecodeJpeg.Options... op
* @param options carries optional attribute values
* @return a new instance of DecodePng, with default output types
*/
- public DecodePng decodePng(Operand contents, DecodePng.Options[] options) {
+ public DecodePng decodePng(Operand contents, DecodePng.Options... options) {
return DecodePng.create(scope, contents, options);
}
@@ -467,6 +471,51 @@ public DecodePng decodePng(Operand contents, Cla
return DecodePng.create(scope, contents, dtype, options);
}
+ /**
+ * Decode a WebP-encoded image to a uint8 tensor.
+ * The attr {@code channels} indicates the desired number of color channels for the
+ * decoded image.
+ * Accepted values are:
+ *
+ * - 0: Use the number of channels in the WebP-encoded image.
+ * - 3: output an RGB image.
+ * - 4: output an RGBA image.
+ *
+ * The number of channels must currently match that of the underlying file.
+ * For WebP animations, only 4-channel RGBA is supported.
+ *
+ * @param contents 0-D. The WebP-encoded image.
+ * @param options carries optional attribute values
+ * @return a new instance of DecodeWebP, with default output types
+ */
+ public DecodeWebP decodeWebP(Operand contents, DecodeWebP.Options... options) {
+ return DecodeWebP.create(scope, contents, options);
+ }
+
+ /**
+ * Decode a WebP-encoded image to a uint8 tensor.
+ * The attr {@code channels} indicates the desired number of color channels for the
+ * decoded image.
+ * Accepted values are:
+ *
+ * - 0: Use the number of channels in the WebP-encoded image.
+ * - 3: output an RGB image.
+ * - 4: output an RGBA image.
+ *
+ * The number of channels must currently match that of the underlying file.
+ * For WebP animations, only 4-channel RGBA is supported.
+ *
+ * @param contents 0-D. The WebP-encoded image.
+ * @param dtype The value of the dtype attribute
+ * @param options carries optional attribute values
+ * @param data type for {@code DecodeWebP} output and operands
+ * @return a new instance of DecodeWebP
+ */
+ public DecodeWebP decodeWebP(Operand contents, Class dtype,
+ DecodeWebP.Options... options) {
+ return DecodeWebP.create(scope, contents, dtype, options);
+ }
+
/**
* Draw bounding boxes on a batch of images.
* Outputs a copy of {@code images} but draws on top of the pixels zero or more bounding
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 535af3cda71..c9f086a3255 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
@@ -2127,7 +2127,7 @@ public MaxPoolGradWithArgmax maxPoolGradWithArgmax(Operan
* @return a new instance of MaxPoolWithArgmax, with default output types
*/
public MaxPoolWithArgmax maxPoolWithArgmax(Operand input,
- List ksize, List strides, String padding, MaxPoolWithArgmax.Options[] options) {
+ List ksize, List strides, String padding, MaxPoolWithArgmax.Options... options) {
return MaxPoolWithArgmax.create(scope, input, ksize, strides, padding, options);
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
index b9f5cd836f6..8483a4efb61 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
@@ -420,10 +420,10 @@ public final class Ops {
public final SummaryOps summary;
- public final ImageOps image;
-
public final RaggedOps ragged;
+ public final ImageOps image;
+
public final ShapeOps shape;
public final IoOps io;
@@ -457,8 +457,8 @@ public final class Ops {
train = new TrainOps(this);
quantization = new QuantizationOps(this);
summary = new SummaryOps(this);
- image = new ImageOps(this);
ragged = new RaggedOps(this);
+ image = new ImageOps(this);
shape = new ShapeOps(this);
io = new IoOps(this);
dtypes = new DtypesOps(this);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
index 8bd174ba427..88df6bf8a0e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
@@ -114,7 +114,7 @@ public final class QuantizationOps {
* @return a new instance of Dequantize, with default output types
*/
public Dequantize dequantize(Operand input,
- Operand minRange, Operand maxRange, Dequantize.Options[] options) {
+ Operand minRange, Operand maxRange, Dequantize.Options... options) {
return Dequantize.create(scope, input, minRange, maxRange, options);
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
index c5ff9a489a0..6000af11c9b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
@@ -210,7 +210,7 @@ public LogUniformCandidateSampler logUniformCandidateSampler(Operand tru
* @return a new instance of Multinomial, with default output types
*/
public Multinomial multinomial(Operand logits,
- Operand numSamples, Multinomial.Options[] options) {
+ Operand numSamples, Multinomial.Options... options) {
return Multinomial.create(scope, logits, numSamples, options);
}
@@ -327,7 +327,7 @@ public RandomGammaGrad randomGammaGrad(Operand alpha,
* @return a new instance of RandomPoisson, with default output types
*/
public RandomPoisson randomPoisson(Operand shape,
- Operand rate, RandomPoisson.Options[] options) {
+ Operand rate, RandomPoisson.Options... options) {
return RandomPoisson.create(scope, shape, rate, options);
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
index 56a82c2dbf6..2b49dd474a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
@@ -564,7 +564,7 @@ public ToNumber toNumber(Operand stringTensor, C
* @return a new instance of UnicodeDecode, with default output types
*/
public UnicodeDecode unicodeDecode(Operand input, String inputEncoding,
- UnicodeDecode.Options[] options) {
+ UnicodeDecode.Options... options) {
return UnicodeDecode.create(scope, input, inputEncoding, options);
}
@@ -626,7 +626,7 @@ public UnicodeDecode unicodeDecode(Operand input
* @return a new instance of UnicodeDecodeWithOffsets, with default output types
*/
public UnicodeDecodeWithOffsets unicodeDecodeWithOffsets(Operand input,
- String inputEncoding, UnicodeDecodeWithOffsets.Options[] options) {
+ String inputEncoding, UnicodeDecodeWithOffsets.Options... options) {
return UnicodeDecodeWithOffsets.create(scope, input, inputEncoding, options);
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
index 22a2ef5ae85..38961e1570a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
@@ -28,12 +28,18 @@
import org.tensorflow.op.xla.XlaHostCompute;
import org.tensorflow.op.xla.XlaRecvFromHost;
import org.tensorflow.op.xla.XlaSendToHost;
+import org.tensorflow.op.xla.XlaSparseActivationsUnstack;
import org.tensorflow.op.xla.XlaSparseCoreAdagrad;
import org.tensorflow.op.xla.XlaSparseCoreAdagradMomentum;
import org.tensorflow.op.xla.XlaSparseCoreAdam;
import org.tensorflow.op.xla.XlaSparseCoreFtrl;
import org.tensorflow.op.xla.XlaSparseCoreSgd;
import org.tensorflow.op.xla.XlaSparseDenseMatmul;
+import org.tensorflow.op.xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput;
+import org.tensorflow.op.xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput;
+import org.tensorflow.op.xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput;
+import org.tensorflow.op.xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput;
+import org.tensorflow.op.xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput;
import org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithAdagradAndCsrInput;
import org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput;
import org.tensorflow.op.xla.XlaSparseDenseMatmulGradWithAdamAndCsrInput;
@@ -42,6 +48,7 @@
import org.tensorflow.op.xla.XlaSparseDenseMatmulWithCsrInput;
import org.tensorflow.types.TFloat32;
import org.tensorflow.types.TInt32;
+import org.tensorflow.types.family.TNumber;
import org.tensorflow.types.family.TType;
/**
@@ -292,6 +299,24 @@ public XlaSendToHost xlaSendToHost(Operand input, String key) {
return XlaSendToHost.create(scope, input, key);
}
+ /**
+ * The XlaSparseActivationsUnstack operation
+ *
+ * @param stackedActivations The stackedActivations value
+ * @param numTables The value of the numTables attribute
+ * @param sampleCounts The value of the sampleCounts attribute
+ * @param features The value of the features attribute
+ * @param interleaved The value of the interleaved attribute
+ * @param dtype The value of the dtype attribute
+ * @param data type for {@code XlaSparseActivationsUnstack} output and operands
+ * @return a new instance of XlaSparseActivationsUnstack
+ */
+ public XlaSparseActivationsUnstack xlaSparseActivationsUnstack(
+ Operand stackedActivations, Long numTables, List sampleCounts,
+ List features, Boolean interleaved, Class dtype) {
+ return XlaSparseActivationsUnstack.create(scope, stackedActivations, numTables, sampleCounts, features, interleaved, dtype);
+ }
+
/**
* The XlaSparseCoreAdagrad operation
*
@@ -418,6 +443,217 @@ public XlaSparseDenseMatmul xlaSparseDenseMatmul(Operand rowIds,
return XlaSparseDenseMatmul.create(scope, rowIds, colIds, values, offsets, embeddingTable, maxIdsPerPartition, maxUniqueIdsPerPartition, inputSize);
}
+ /**
+ * The XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput operation
+ *
+ * @param rowPointers The rowPointers value
+ * @param sortedSampleIds The sortedSampleIds value
+ * @param sortedTokenIds The sortedTokenIds value
+ * @param sortedPosIds The sortedPosIds value
+ * @param sortedGains The sortedGains value
+ * @param weights The weights value
+ * @param preservedValencies The preservedValencies value
+ * @param preservedVectors The preservedVectors value
+ * @param preservedWeights The preservedWeights value
+ * @param activationGradients The activationGradients value
+ * @param learningRate The learningRate value
+ * @param combinerWeightsLearningRate The combinerWeightsLearningRate value
+ * @param embeddingTable The embeddingTable value
+ * @param accumulator The accumulator value
+ * @param maxValency The value of the maxValency attribute
+ * @param numWeights The value of the numWeights attribute
+ * @param combinerTableVjpComputation The value of the combinerTableVjpComputation attribute
+ * @param combinerWeightsVjpComputation The value of the combinerWeightsVjpComputation attribute
+ * @param tableName The value of the tableName attribute
+ * @param options carries optional attribute values
+ * @return a new instance of XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput
+ */
+ public XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput xlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput(
+ Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds,
+ Operand sortedPosIds, Operand sortedGains, Operand weights,
+ Operand preservedValencies, Operand preservedVectors,
+ Operand preservedWeights, Operand activationGradients,
+ Operand learningRate, Operand combinerWeightsLearningRate,
+ Operand embeddingTable, Operand accumulator, Long maxValency,
+ Long numWeights, ConcreteFunction combinerTableVjpComputation,
+ ConcreteFunction combinerWeightsVjpComputation, String tableName,
+ XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.Options... options) {
+ return XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.create(scope, rowPointers, sortedSampleIds, sortedTokenIds, sortedPosIds, sortedGains, weights, preservedValencies, preservedVectors, preservedWeights, activationGradients, learningRate, combinerWeightsLearningRate, embeddingTable, accumulator, maxValency, numWeights, combinerTableVjpComputation, combinerWeightsVjpComputation, tableName, options);
+ }
+
+ /**
+ * The XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput operation
+ *
+ * @param rowPointers The rowPointers value
+ * @param sortedSampleIds The sortedSampleIds value
+ * @param sortedTokenIds The sortedTokenIds value
+ * @param sortedPosIds The sortedPosIds value
+ * @param sortedGains The sortedGains value
+ * @param weights The weights value
+ * @param preservedValencies The preservedValencies value
+ * @param preservedVectors The preservedVectors value
+ * @param preservedWeights The preservedWeights value
+ * @param activationGradients The activationGradients value
+ * @param learningRate The learningRate value
+ * @param combinerWeightsLearningRate The combinerWeightsLearningRate value
+ * @param embeddingTable The embeddingTable value
+ * @param accumulator The accumulator value
+ * @param momenta The momenta value
+ * @param useNesterov The value of the useNesterov attribute
+ * @param exponent The value of the exponent attribute
+ * @param beta1 The value of the beta1 attribute
+ * @param beta2 The value of the beta2 attribute
+ * @param epsilon The value of the epsilon attribute
+ * @param maxValency The value of the maxValency attribute
+ * @param numWeights The value of the numWeights attribute
+ * @param combinerTableVjpComputation The value of the combinerTableVjpComputation attribute
+ * @param combinerWeightsVjpComputation The value of the combinerWeightsVjpComputation attribute
+ * @param tableName The value of the tableName attribute
+ * @param options carries optional attribute values
+ * @return a new instance of XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput
+ */
+ public XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput xlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput(
+ Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds,
+ Operand sortedPosIds, Operand sortedGains, Operand weights,
+ Operand preservedValencies, Operand preservedVectors,
+ Operand preservedWeights, Operand activationGradients,
+ Operand learningRate, Operand combinerWeightsLearningRate,
+ Operand embeddingTable, Operand accumulator, Operand momenta,
+ Boolean useNesterov, Float exponent, Float beta1, Float beta2, Float epsilon, Long maxValency,
+ Long numWeights, ConcreteFunction combinerTableVjpComputation,
+ ConcreteFunction combinerWeightsVjpComputation, String tableName,
+ XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput.Options... options) {
+ return XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput.create(scope, rowPointers, sortedSampleIds, sortedTokenIds, sortedPosIds, sortedGains, weights, preservedValencies, preservedVectors, preservedWeights, activationGradients, learningRate, combinerWeightsLearningRate, embeddingTable, accumulator, momenta, useNesterov, exponent, beta1, beta2, epsilon, maxValency, numWeights, combinerTableVjpComputation, combinerWeightsVjpComputation, tableName, options);
+ }
+
+ /**
+ * The XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput operation
+ *
+ * @param rowPointers The rowPointers value
+ * @param sortedSampleIds The sortedSampleIds value
+ * @param sortedTokenIds The sortedTokenIds value
+ * @param sortedPosIds The sortedPosIds value
+ * @param sortedGains The sortedGains value
+ * @param weights The weights value
+ * @param preservedValencies The preservedValencies value
+ * @param preservedVectors The preservedVectors value
+ * @param preservedWeights The preservedWeights value
+ * @param activationGradients The activationGradients value
+ * @param learningRate The learningRate value
+ * @param combinerWeightsLearningRate The combinerWeightsLearningRate value
+ * @param embeddingTable The embeddingTable value
+ * @param momenta The momenta value
+ * @param velocity The velocity value
+ * @param useSumInsideSqrt The value of the useSumInsideSqrt attribute
+ * @param beta1 The value of the beta1 attribute
+ * @param beta2 The value of the beta2 attribute
+ * @param epsilon The value of the epsilon attribute
+ * @param maxValency The value of the maxValency attribute
+ * @param numWeights The value of the numWeights attribute
+ * @param combinerTableVjpComputation The value of the combinerTableVjpComputation attribute
+ * @param combinerWeightsVjpComputation The value of the combinerWeightsVjpComputation attribute
+ * @param tableName The value of the tableName attribute
+ * @param options carries optional attribute values
+ * @return a new instance of XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput
+ */
+ public XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput xlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput(
+ Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds,
+ Operand sortedPosIds, Operand sortedGains, Operand weights,
+ Operand preservedValencies, Operand preservedVectors,
+ Operand preservedWeights, Operand activationGradients,
+ Operand learningRate, Operand combinerWeightsLearningRate,
+ Operand embeddingTable, Operand momenta, Operand velocity,
+ Boolean useSumInsideSqrt, Float beta1, Float beta2, Float epsilon, Long maxValency,
+ Long numWeights, ConcreteFunction combinerTableVjpComputation,
+ ConcreteFunction combinerWeightsVjpComputation, String tableName,
+ XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput.Options... options) {
+ return XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput.create(scope, rowPointers, sortedSampleIds, sortedTokenIds, sortedPosIds, sortedGains, weights, preservedValencies, preservedVectors, preservedWeights, activationGradients, learningRate, combinerWeightsLearningRate, embeddingTable, momenta, velocity, useSumInsideSqrt, beta1, beta2, epsilon, maxValency, numWeights, combinerTableVjpComputation, combinerWeightsVjpComputation, tableName, options);
+ }
+
+ /**
+ * The XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput operation
+ *
+ * @param rowPointers The rowPointers value
+ * @param sortedSampleIds The sortedSampleIds value
+ * @param sortedTokenIds The sortedTokenIds value
+ * @param sortedPosIds The sortedPosIds value
+ * @param sortedGains The sortedGains value
+ * @param weights The weights value
+ * @param preservedValencies The preservedValencies value
+ * @param preservedVectors The preservedVectors value
+ * @param preservedWeights The preservedWeights value
+ * @param activationGradients The activationGradients value
+ * @param tables The tables value
+ * @param hyperparameters The hyperparameters value
+ * @param combinerWeightsLearningRate The combinerWeightsLearningRate value
+ * @param maxValency The value of the maxValency attribute
+ * @param numWeights The value of the numWeights attribute
+ * @param combinerTableVjpComputation The value of the combinerTableVjpComputation attribute
+ * @param combinerWeightsVjpComputation The value of the combinerWeightsVjpComputation attribute
+ * @param optimizerCustomComputation The value of the optimizerCustomComputation attribute
+ * @param tableName The value of the tableName attribute
+ * @param options carries optional attribute values
+ * @return a new instance of XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput
+ */
+ public XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput xlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput(
+ Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds,
+ Operand sortedPosIds, Operand sortedGains, Operand weights,
+ Operand preservedValencies, Operand preservedVectors,
+ Operand preservedWeights, Operand activationGradients,
+ Iterable> tables, Iterable> hyperparameters,
+ Operand combinerWeightsLearningRate, Long maxValency, Long numWeights,
+ ConcreteFunction combinerTableVjpComputation, ConcreteFunction combinerWeightsVjpComputation,
+ ConcreteFunction optimizerCustomComputation, String tableName,
+ XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput.Options... options) {
+ return XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput.create(scope, rowPointers, sortedSampleIds, sortedTokenIds, sortedPosIds, sortedGains, weights, preservedValencies, preservedVectors, preservedWeights, activationGradients, tables, hyperparameters, combinerWeightsLearningRate, maxValency, numWeights, combinerTableVjpComputation, combinerWeightsVjpComputation, optimizerCustomComputation, tableName, options);
+ }
+
+ /**
+ * The XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput operation
+ *
+ * @param rowPointers The rowPointers value
+ * @param sortedSampleIds The sortedSampleIds value
+ * @param sortedTokenIds The sortedTokenIds value
+ * @param sortedPosIds The sortedPosIds value
+ * @param sortedGains The sortedGains value
+ * @param weights The weights value
+ * @param preservedValencies The preservedValencies value
+ * @param preservedVectors The preservedVectors value
+ * @param preservedWeights The preservedWeights value
+ * @param activationGradients The activationGradients value
+ * @param learningRate The learningRate value
+ * @param combinerWeightsLearningRate The combinerWeightsLearningRate value
+ * @param embeddingTable The embeddingTable value
+ * @param accumulator The accumulator value
+ * @param linear The linear value
+ * @param multiplyLinearByLearningRate The value of the multiplyLinearByLearningRate attribute
+ * @param beta The value of the beta attribute
+ * @param learningRatePower The value of the learningRatePower attribute
+ * @param l1RegularizationStrength The value of the l1RegularizationStrength attribute
+ * @param l2RegularizationStrength The value of the l2RegularizationStrength attribute
+ * @param maxValency The value of the maxValency attribute
+ * @param numWeights The value of the numWeights attribute
+ * @param combinerTableVjpComputation The value of the combinerTableVjpComputation attribute
+ * @param combinerWeightsVjpComputation The value of the combinerWeightsVjpComputation attribute
+ * @param tableName The value of the tableName attribute
+ * @param options carries optional attribute values
+ * @return a new instance of XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput
+ */
+ public XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput xlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput(
+ Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds,
+ Operand sortedPosIds, Operand sortedGains, Operand weights,
+ Operand preservedValencies, Operand preservedVectors,
+ Operand preservedWeights, Operand activationGradients,
+ Operand learningRate, Operand combinerWeightsLearningRate,
+ Operand embeddingTable, Operand accumulator, Operand linear,
+ Boolean multiplyLinearByLearningRate, Float beta, Float learningRatePower,
+ Float l1RegularizationStrength, Float l2RegularizationStrength, Long maxValency,
+ Long numWeights, ConcreteFunction combinerTableVjpComputation,
+ ConcreteFunction combinerWeightsVjpComputation, String tableName,
+ XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput.Options... options) {
+ return XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput.create(scope, rowPointers, sortedSampleIds, sortedTokenIds, sortedPosIds, sortedGains, weights, preservedValencies, preservedVectors, preservedWeights, activationGradients, learningRate, combinerWeightsLearningRate, embeddingTable, accumulator, linear, multiplyLinearByLearningRate, beta, learningRatePower, l1RegularizationStrength, l2RegularizationStrength, maxValency, numWeights, combinerTableVjpComputation, combinerWeightsVjpComputation, tableName, options);
+ }
+
/**
* The XlaSparseDenseMatmulGradWithAdagradAndCsrInput operation
*
@@ -579,15 +815,17 @@ public XlaSparseDenseMatmulGradWithSgdAndCsrInput xlaSparseDenseMatmulGradWithSg
* @param quantizationConfigHigh The value of the quantizationConfigHigh attribute
* @param quantizationConfigNumBuckets The value of the quantizationConfigNumBuckets attribute
* @param tableName The value of the tableName attribute
+ * @param options carries optional attribute values
+ * @param data type for {@code XlaSparseDenseMatmulWithCsrInput} output and operands
* @return a new instance of XlaSparseDenseMatmulWithCsrInput
*/
- public XlaSparseDenseMatmulWithCsrInput xlaSparseDenseMatmulWithCsrInput(
+ public XlaSparseDenseMatmulWithCsrInput xlaSparseDenseMatmulWithCsrInput(
Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds,
- Operand sortedGains, Operand embeddingTable,
+ Operand sortedGains, Operand embeddingTable,
Operand numMinibatchesPerPhysicalSparseCore, Long inputSize,
Float quantizationConfigLow, Float quantizationConfigHigh, Long quantizationConfigNumBuckets,
- String tableName) {
- return XlaSparseDenseMatmulWithCsrInput.create(scope, rowPointers, sortedSampleIds, sortedTokenIds, sortedGains, embeddingTable, numMinibatchesPerPhysicalSparseCore, inputSize, quantizationConfigLow, quantizationConfigHigh, quantizationConfigNumBuckets, tableName);
+ String tableName, XlaSparseDenseMatmulWithCsrInput.Options... options) {
+ return XlaSparseDenseMatmulWithCsrInput.create(scope, rowPointers, sortedSampleIds, sortedTokenIds, sortedGains, embeddingTable, numMinibatchesPerPhysicalSparseCore, inputSize, quantizationConfigLow, quantizationConfigHigh, quantizationConfigNumBuckets, tableName, options);
}
/**
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 4ff0f11c7bc..d83f728b452 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
@@ -102,7 +102,7 @@ public static DebugNumericsSummary create(Scope scope,
describeByClass = true
)
public static DebugNumericsSummary create(Scope scope, Operand input,
- Options[] options) {
+ Options... options) {
return create(scope, input, TFloat32.class, options);
}
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 1f9b0285c6c..25dfbfe50ff 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
@@ -38,7 +38,7 @@
* Converts each entry in the given tensor to strings.
* Supports many numeric types and boolean.
* For Unicode, see the
- * [https://www.tensorflow.org/tutorials/representation/unicode](Working with Unicode text)
+ * [https://www.tensorflow.org/text/guide/unicode](Working with Unicode text)
* tutorial.
*
Examples:
*
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java
index a5c7ee7845e..891c31bb514 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java
@@ -37,17 +37,18 @@
import org.tensorflow.types.family.TNumber;
/**
- * Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
- * Detects whether an image is a BMP, GIF, JPEG, or PNG, and performs the
+ * Function for decode_bmp, decode_gif, decode_jpeg, decode_webp, and decode_png.
+ * Detects whether an image is a BMP, GIF, JPEG, WebP, or PNG, and performs the
* appropriate operation to convert the input bytes string into a Tensor of type
* dtype.
- * NOTE: decode_gif returns a 4-D array [num_frames, height, width, 3], as
- * opposed to decode_bmp, decode_jpeg and decode_png, which return 3-D arrays
- * [height, width, num_channels]. Make sure to take this into account when
- * constructing your graph if you are intermixing GIF files with BMP, JPEG, and/or
- * PNG files. Alternately, set the expand_animations argument of this function to
- * False, in which case the op will return 3-dimensional tensors and will truncate
- * animated GIF files to the first frame.
+ *
NOTE: decode_gif and decode_webp return a 4-D
+ * array [num_frames, height, width, 3], as opposed to decode_bmp,
+ * decode_jpeg, and decode_png, which always return 3-D arrays [height,
+ * width, num_channels]. Make sure to take this into account when
+ * constructing your graph if you are intermixing animated files with
+ * BMP, JPEG, and/or PNG files. Alternately, set the expand_animations
+ * argument of this function to False, in which case the op will return
+ * 3-dimensional tensors and will truncate animations to the first frame.
*
NOTE: If the first frame of an animated GIF does not occupy the entire
* canvas (maximum frame width x maximum frame height), then it fills the
* unoccupied areas (in the first frame) with zeros (black). For frames after the
@@ -118,7 +119,7 @@ public static DecodeImage create(Scope scope, Operand create(Scope scope, Operand contents,
- Options[] options) {
+ Options... options) {
return create(scope, contents, TUint8.class, options);
}
@@ -135,10 +136,11 @@ public static Options channels(Long channels) {
/**
* Sets the expandAnimations option.
*
- * @param expandAnimations Controls the output shape of the returned op. If True, the returned op will
- * produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D tensor for all
- * GIFs, whether animated or not. If, False, the returned op will produce a 3-D
- * tensor for all file types and will truncate animated GIFs to the first frame.
+ * @param expandAnimations Controls the output shape of the returned op. If True, the returned op
+ * will produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D
+ * tensor for all GIFs and WebP images, whether animated or not. If,
+ * False, the returned op will produce a 3-D tensor for all file types
+ * and will truncate animated images to the first frame.
* @return this Options instance.
*/
public static Options expandAnimations(Boolean expandAnimations) {
@@ -185,10 +187,11 @@ public Options channels(Long channels) {
/**
* Sets the expandAnimations option.
*
- * @param expandAnimations Controls the output shape of the returned op. If True, the returned op will
- * produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D tensor for all
- * GIFs, whether animated or not. If, False, the returned op will produce a 3-D
- * tensor for all file types and will truncate animated GIFs to the first frame.
+ * @param expandAnimations Controls the output shape of the returned op. If True, the returned op
+ * will produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D
+ * tensor for all GIFs and WebP images, whether animated or not. If,
+ * False, the returned op will produce a 3-D tensor for all file types
+ * and will truncate animated images to the first frame.
* @return this Options instance.
*/
public Options expandAnimations(Boolean expandAnimations) {
@@ -217,10 +220,11 @@ public static class Inputs extends RawOpInputs> {
public final DataType dtype;
/**
- * Controls the output shape of the returned op. If True, the returned op will
- * produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D tensor for all
- * GIFs, whether animated or not. If, False, the returned op will produce a 3-D
- * tensor for all file types and will truncate animated GIFs to the first frame.
+ * Controls the output shape of the returned op. If True, the returned op
+ * will produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D
+ * tensor for all GIFs and WebP images, whether animated or not. If,
+ * False, the returned op will produce a 3-D tensor for all file types
+ * and will truncate animated images to the first frame.
*/
public final boolean expandAnimations;
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 dd6384caf7c..8352476fae0 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
@@ -113,7 +113,7 @@ public static DecodePng create(Scope scope, Operand create(Scope scope, Operand contents,
- Options[] options) {
+ Options... options) {
return create(scope, contents, TUint8.class, options);
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeWebP.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeWebP.java
new file mode 100644
index 00000000000..16a7b6b54cb
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeWebP.java
@@ -0,0 +1,189 @@
+/* Copyright 2018-2023 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.image;
+
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
+import org.tensorflow.Operand;
+import org.tensorflow.Operation;
+import org.tensorflow.OperationBuilder;
+import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
+import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.OpInputsMetadata;
+import org.tensorflow.op.annotation.OpMetadata;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.DataType;
+import org.tensorflow.types.TString;
+import org.tensorflow.types.TUint8;
+import org.tensorflow.types.family.TNumber;
+
+/**
+ * Decode a WebP-encoded image to a uint8 tensor.
+ * The attr {@code channels} indicates the desired number of color channels for the
+ * decoded image.
+ * Accepted values are:
+ *
+ * - 0: Use the number of channels in the WebP-encoded image.
+ * - 3: output an RGB image.
+ * - 4: output an RGBA image.
+ *
+ * The number of channels must currently match that of the underlying file.
+ * For WebP animations, only 4-channel RGBA is supported.
+ */
+@OpMetadata(
+ opType = DecodeWebP.OP_NAME,
+ inputsClass = DecodeWebP.Inputs.class
+)
+@Operator(
+ group = "image"
+)
+public final class DecodeWebP extends RawOp implements Operand {
+ /**
+ * The name of this op, as known by TensorFlow core engine
+ */
+ public static final String OP_NAME = "DecodeWebP";
+
+ private Output image;
+
+ public DecodeWebP(Operation operation) {
+ super(operation, OP_NAME);
+ int outputIdx = 0;
+ image = operation.output(outputIdx++);
+ }
+
+ /**
+ * Factory method to create a class wrapping a new DecodeWebP operation.
+ *
+ * @param scope current scope
+ * @param contents 0-D. The WebP-encoded image.
+ * @param dtype The value of the dtype attribute
+ * @param options carries optional attribute values
+ * @param data type for {@code DecodeWebP} output and operands
+ * @return a new instance of DecodeWebP
+ */
+ @Endpoint(
+ describeByClass = true
+ )
+ public static DecodeWebP create(Scope scope, Operand contents,
+ Class dtype, Options... options) {
+ OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "DecodeWebP");
+ opBuilder.addInput(contents.asOutput());
+ opBuilder.setAttr("dtype", Operands.toDataType(dtype));
+ if (options != null) {
+ for (Options opts : options) {
+ if (opts.channels != null) {
+ opBuilder.setAttr("channels", opts.channels);
+ }
+ }
+ }
+ return new DecodeWebP<>(opBuilder.build());
+ }
+
+ /**
+ * Factory method to create a class wrapping a new DecodeWebP operation, with the default output types.
+ *
+ * @param scope current scope
+ * @param contents 0-D. The WebP-encoded image.
+ * @param options carries optional attribute values
+ * @return a new instance of DecodeWebP, with default output types
+ */
+ @Endpoint(
+ describeByClass = true
+ )
+ public static DecodeWebP create(Scope scope, Operand contents,
+ Options... options) {
+ return create(scope, contents, TUint8.class, options);
+ }
+
+ /**
+ * Sets the channels option.
+ *
+ * @param channels Number of color channels for the decoded image.
+ * @return this Options instance.
+ */
+ public static Options channels(Long channels) {
+ return new Options().channels(channels);
+ }
+
+ /**
+ * Gets image.
+ * 4-D with shape {@code [num_frames, height, width, channels]}.
+ * @return image.
+ */
+ public Output image() {
+ return image;
+ }
+
+ @Override
+ public Output asOutput() {
+ return image;
+ }
+
+ /**
+ * Optional attributes for {@link org.tensorflow.op.image.DecodeWebP}
+ */
+ public static class Options {
+ private Long channels;
+
+ private Options() {
+ }
+
+ /**
+ * Sets the channels option.
+ *
+ * @param channels Number of color channels for the decoded image.
+ * @return this Options instance.
+ */
+ public Options channels(Long channels) {
+ this.channels = channels;
+ return this;
+ }
+ }
+
+ @OpInputsMetadata(
+ outputsClass = DecodeWebP.class
+ )
+ public static class Inputs extends RawOpInputs> {
+ /**
+ * 0-D. The WebP-encoded image.
+ */
+ public final Operand contents;
+
+ /**
+ * Number of color channels for the decoded image.
+ */
+ public final long channels;
+
+ /**
+ * The dtype attribute
+ */
+ public final DataType dtype;
+
+ public Inputs(GraphOperation op) {
+ super(new DecodeWebP<>(op), op, Arrays.asList("channels", "dtype"));
+ int inputIndex = 0;
+ contents = (Operand) op.input(inputIndex++);
+ channels = op.attributes().getAttrInt("channels");
+ dtype = op.attributes().getAttrType("dtype");
+ }
+ }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java
index bd19af1b703..78e871d2de7 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
@@ -133,7 +133,7 @@ public static MaxPoolWithArgmax cre
describeByClass = true
)
public static MaxPoolWithArgmax create(Scope scope,
- Operand input, List ksize, List strides, String padding, Options[] options) {
+ Operand input, List ksize, List strides, String padding, Options... options) {
return create(scope, input, ksize, strides, TInt64.class, padding, options);
}
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 a062ee1db29..e1333747ce9 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
@@ -156,7 +156,7 @@ public static Dequantize create(Scope scope,
describeByClass = true
)
public static Dequantize create(Scope scope, Operand input,
- Operand minRange, Operand maxRange, Options[] options) {
+ Operand minRange, Operand maxRange, Options... options) {
return create(scope, input, minRange, maxRange, TFloat32.class, options);
}
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 a213609fca6..c4625651dc9 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
@@ -109,7 +109,7 @@ public static Multinomial create(Scope scope,
describeByClass = true
)
public static Multinomial create(Scope scope, Operand logits,
- Operand numSamples, Options[] options) {
+ Operand numSamples, Options... options) {
return create(scope, logits, numSamples, TInt64.class, options);
}
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 3e5fc40fc2f..8abad16a003 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
@@ -118,7 +118,7 @@ public static RandomPoisson create(Scope scope,
describeByClass = true
)
public static RandomPoisson create(Scope scope, Operand shape,
- Operand rate, Options[] options) {
+ Operand rate, Options... options) {
return create(scope, shape, rate, TInt64.class, options);
}
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 40624c66adf..cc29b554bef 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
@@ -130,7 +130,7 @@ public static UnicodeDecode create(Scope scope, Operand create(Scope scope, Operand input,
- String inputEncoding, Options[] options) {
+ String inputEncoding, Options... options) {
return create(scope, input, inputEncoding, TInt64.class, options);
}
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 5989e8e7106..fb8887c4594 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
@@ -137,7 +137,7 @@ public static UnicodeDecodeWithOffsets create(Scope scope
describeByClass = true
)
public static UnicodeDecodeWithOffsets create(Scope scope, Operand input,
- String inputEncoding, Options[] options) {
+ String inputEncoding, Options... options) {
return create(scope, input, inputEncoding, TInt64.class, options);
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java
index 67f49871a2c..3e9453b7789 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicateMetadata.java
@@ -113,6 +113,9 @@ public static ReplicateMetadata create(Scope scope, Long numReplicas, Options...
if (opts.useSpmdForXlaPartitioning != null) {
opBuilder.setAttr("use_spmd_for_xla_partitioning", opts.useSpmdForXlaPartitioning);
}
+ if (opts.useShardyPartitioner != null) {
+ opBuilder.setAttr("use_shardy_partitioner", opts.useShardyPartitioner);
+ }
if (opts.tpuCompileOptionsProto != null) {
opBuilder.setAttr("tpu_compile_options_proto", opts.tpuCompileOptionsProto);
}
@@ -261,6 +264,16 @@ public static Options useSpmdForXlaPartitioning(Boolean useSpmdForXlaPartitionin
return new Options().useSpmdForXlaPartitioning(useSpmdForXlaPartitioning);
}
+ /**
+ * Sets the useShardyPartitioner option.
+ *
+ * @param useShardyPartitioner the useShardyPartitioner option
+ * @return this Options instance.
+ */
+ public static Options useShardyPartitioner(Boolean useShardyPartitioner) {
+ return new Options().useShardyPartitioner(useShardyPartitioner);
+ }
+
/**
* Sets the tpuCompileOptionsProto option.
*
@@ -295,6 +308,8 @@ public static class Options {
private Boolean useSpmdForXlaPartitioning;
+ private Boolean useShardyPartitioner;
+
private String tpuCompileOptionsProto;
private Options() {
@@ -454,6 +469,17 @@ public Options useSpmdForXlaPartitioning(Boolean useSpmdForXlaPartitioning) {
return this;
}
+ /**
+ * Sets the useShardyPartitioner option.
+ *
+ * @param useShardyPartitioner the useShardyPartitioner option
+ * @return this Options instance.
+ */
+ public Options useShardyPartitioner(Boolean useShardyPartitioner) {
+ this.useShardyPartitioner = useShardyPartitioner;
+ return this;
+ }
+
/**
* Sets the tpuCompileOptionsProto option.
*
@@ -525,13 +551,18 @@ public static class Inputs extends RawOpInputs {
*/
public final boolean useSpmdForXlaPartitioning;
+ /**
+ * The useShardyPartitioner attribute
+ */
+ public final boolean useShardyPartitioner;
+
/**
* The tpuCompileOptionsProto attribute
*/
public final String tpuCompileOptionsProto;
public Inputs(GraphOperation op) {
- super(new ReplicateMetadata(op), op, Arrays.asList("num_replicas", "num_cores_per_replica", "topology", "use_tpu", "device_assignment", "computation_shape", "host_compute_core", "padding_map", "step_marker_location", "allow_soft_placement", "use_spmd_for_xla_partitioning", "tpu_compile_options_proto"));
+ super(new ReplicateMetadata(op), op, Arrays.asList("num_replicas", "num_cores_per_replica", "topology", "use_tpu", "device_assignment", "computation_shape", "host_compute_core", "padding_map", "step_marker_location", "allow_soft_placement", "use_spmd_for_xla_partitioning", "use_shardy_partitioner", "tpu_compile_options_proto"));
int inputIndex = 0;
numReplicas = op.attributes().getAttrInt("num_replicas");
numCoresPerReplica = op.attributes().getAttrInt("num_cores_per_replica");
@@ -544,6 +575,7 @@ public Inputs(GraphOperation op) {
stepMarkerLocation = op.attributes().getAttrString("step_marker_location");
allowSoftPlacement = op.attributes().getAttrBool("allow_soft_placement");
useSpmdForXlaPartitioning = op.attributes().getAttrBool("use_spmd_for_xla_partitioning");
+ useShardyPartitioner = op.attributes().getAttrBool("use_shardy_partitioner");
tpuCompileOptionsProto = op.attributes().getAttrString("tpu_compile_options_proto");
}
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUDummyInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUDummyInput.java
new file mode 100644
index 00000000000..4b7fae6c11c
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUDummyInput.java
@@ -0,0 +1,114 @@
+/* Copyright 2018-2023 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.tpu;
+
+import java.util.Arrays;
+import org.tensorflow.GraphOperation;
+import org.tensorflow.Operand;
+import org.tensorflow.Operation;
+import org.tensorflow.OperationBuilder;
+import org.tensorflow.Output;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
+import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.OpInputsMetadata;
+import org.tensorflow.op.annotation.OpMetadata;
+import org.tensorflow.proto.DataType;
+import org.tensorflow.types.family.TNumber;
+
+/**
+ * Generates a zero-valued tensor for use as a dummy input to a TPU.
+ * For the internal use of the TF2XLA bridge in the XLA Broadcast pass. This op
+ */
+@OpMetadata(
+ opType = TPUDummyInput.OP_NAME,
+ inputsClass = TPUDummyInput.Inputs.class
+)
+public final class TPUDummyInput extends RawOp implements Operand {
+ /**
+ * The name of this op, as known by TensorFlow core engine
+ */
+ public static final String OP_NAME = "TPUDummyInput";
+
+ private Output output;
+
+ public TPUDummyInput(Operation operation) {
+ super(operation, OP_NAME);
+ int outputIdx = 0;
+ output = operation.output(outputIdx++);
+ }
+
+ /**
+ * Factory method to create a class wrapping a new TPUDummyInput operation.
+ *
+ * @param scope current scope
+ * @param dtype The element type of the produced tensor.
+ * @param shape The shape of the produced tensor.
+ * @param data type for {@code TPUDummyInput} output and operands
+ * @return a new instance of TPUDummyInput
+ */
+ @Endpoint(
+ describeByClass = true
+ )
+ public static TPUDummyInput create(Scope scope, Class dtype,
+ Shape shape) {
+ OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "TPUDummyInput");
+ opBuilder.setAttr("dtype", Operands.toDataType(dtype));
+ opBuilder.setAttr("shape", shape);
+ return new TPUDummyInput<>(opBuilder.build());
+ }
+
+ /**
+ * Gets output.
+ *
+ * @return output.
+ */
+ public Output output() {
+ return output;
+ }
+
+ @Override
+ public Output asOutput() {
+ return output;
+ }
+
+ @OpInputsMetadata(
+ outputsClass = TPUDummyInput.class
+ )
+ public static class Inputs extends RawOpInputs> {
+ /**
+ * The element type of the produced tensor.
+ */
+ public final DataType dtype;
+
+ /**
+ * The shape of the produced tensor.
+ */
+ public final Shape shape;
+
+ public Inputs(GraphOperation op) {
+ super(new TPUDummyInput<>(op), op, Arrays.asList("dtype", "shape"));
+ int inputIndex = 0;
+ dtype = op.attributes().getAttrType("dtype");
+ shape = op.attributes().getAttrShape("shape");
+ }
+ }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicateMetadata.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicateMetadata.java
index 1e5fab82839..968dde2b09a 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
@@ -116,6 +116,9 @@ public static TPUReplicateMetadata create(Scope scope, Long numReplicas, Options
if (opts.useSpmdForXlaPartitioning != null) {
opBuilder.setAttr("use_spmd_for_xla_partitioning", opts.useSpmdForXlaPartitioning);
}
+ if (opts.useShardyPartitioner != null) {
+ opBuilder.setAttr("use_shardy_partitioner", opts.useShardyPartitioner);
+ }
if (opts.tpuCompileOptionsProto != null) {
opBuilder.setAttr("tpu_compile_options_proto", opts.tpuCompileOptionsProto);
}
@@ -264,6 +267,16 @@ public static Options useSpmdForXlaPartitioning(Boolean useSpmdForXlaPartitionin
return new Options().useSpmdForXlaPartitioning(useSpmdForXlaPartitioning);
}
+ /**
+ * Sets the useShardyPartitioner option.
+ *
+ * @param useShardyPartitioner the useShardyPartitioner option
+ * @return this Options instance.
+ */
+ public static Options useShardyPartitioner(Boolean useShardyPartitioner) {
+ return new Options().useShardyPartitioner(useShardyPartitioner);
+ }
+
/**
* Sets the tpuCompileOptionsProto option.
*
@@ -298,6 +311,8 @@ public static class Options {
private Boolean useSpmdForXlaPartitioning;
+ private Boolean useShardyPartitioner;
+
private String tpuCompileOptionsProto;
private Options() {
@@ -457,6 +472,17 @@ public Options useSpmdForXlaPartitioning(Boolean useSpmdForXlaPartitioning) {
return this;
}
+ /**
+ * Sets the useShardyPartitioner option.
+ *
+ * @param useShardyPartitioner the useShardyPartitioner option
+ * @return this Options instance.
+ */
+ public Options useShardyPartitioner(Boolean useShardyPartitioner) {
+ this.useShardyPartitioner = useShardyPartitioner;
+ return this;
+ }
+
/**
* Sets the tpuCompileOptionsProto option.
*
@@ -528,13 +554,18 @@ public static class Inputs extends RawOpInputs {
*/
public final boolean useSpmdForXlaPartitioning;
+ /**
+ * The useShardyPartitioner attribute
+ */
+ public final boolean useShardyPartitioner;
+
/**
* The tpuCompileOptionsProto attribute
*/
public final String tpuCompileOptionsProto;
public Inputs(GraphOperation op) {
- super(new TPUReplicateMetadata(op), op, Arrays.asList("num_replicas", "num_cores_per_replica", "topology", "use_tpu", "device_assignment", "computation_shape", "host_compute_core", "padding_map", "step_marker_location", "allow_soft_placement", "use_spmd_for_xla_partitioning", "tpu_compile_options_proto"));
+ super(new TPUReplicateMetadata(op), op, Arrays.asList("num_replicas", "num_cores_per_replica", "topology", "use_tpu", "device_assignment", "computation_shape", "host_compute_core", "padding_map", "step_marker_location", "allow_soft_placement", "use_spmd_for_xla_partitioning", "use_shardy_partitioner", "tpu_compile_options_proto"));
int inputIndex = 0;
numReplicas = op.attributes().getAttrInt("num_replicas");
numCoresPerReplica = op.attributes().getAttrInt("num_cores_per_replica");
@@ -547,6 +578,7 @@ public Inputs(GraphOperation op) {
stepMarkerLocation = op.attributes().getAttrString("step_marker_location");
allowSoftPlacement = op.attributes().getAttrBool("allow_soft_placement");
useSpmdForXlaPartitioning = op.attributes().getAttrBool("use_spmd_for_xla_partitioning");
+ useShardyPartitioner = op.attributes().getAttrBool("use_shardy_partitioner");
tpuCompileOptionsProto = op.attributes().getAttrString("tpu_compile_options_proto");
}
}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseActivationsUnstack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseActivationsUnstack.java
new file mode 100644
index 00000000000..6dc42362b87
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseActivationsUnstack.java
@@ -0,0 +1,163 @@
+/* Copyright 2018-2023 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.xla;
+
+import java.util.Arrays;
+import java.util.Iterator;
+import java.util.List;
+import org.tensorflow.GraphOperation;
+import org.tensorflow.Operand;
+import org.tensorflow.Operation;
+import org.tensorflow.OperationBuilder;
+import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
+import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.OpInputsMetadata;
+import org.tensorflow.op.annotation.OpMetadata;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.proto.DataType;
+import org.tensorflow.types.family.TType;
+
+/**
+ * The XlaSparseActivationsUnstack operation
+ */
+@OpMetadata(
+ opType = XlaSparseActivationsUnstack.OP_NAME,
+ inputsClass = XlaSparseActivationsUnstack.Inputs.class
+)
+@Operator(
+ group = "xla"
+)
+public final class XlaSparseActivationsUnstack extends RawOp implements Iterable> {
+ /**
+ * The name of this op, as known by TensorFlow core engine
+ */
+ public static final String OP_NAME = "XlaSparseActivationsUnstack";
+
+ private List> unstackedActivations;
+
+ @SuppressWarnings("unchecked")
+ public XlaSparseActivationsUnstack(Operation operation) {
+ super(operation, OP_NAME);
+ int outputIdx = 0;
+ int unstackedActivationsLength = operation.outputListLength("unstacked_activations");
+ unstackedActivations = Arrays.asList((Output[]) operation.outputList(outputIdx, unstackedActivationsLength));
+ outputIdx += unstackedActivationsLength;
+ }
+
+ /**
+ * Factory method to create a class wrapping a new XlaSparseActivationsUnstack operation.
+ *
+ * @param scope current scope
+ * @param stackedActivations The stackedActivations value
+ * @param numTables The value of the numTables attribute
+ * @param sampleCounts The value of the sampleCounts attribute
+ * @param features The value of the features attribute
+ * @param interleaved The value of the interleaved attribute
+ * @param dtype The value of the dtype attribute
+ * @param data type for {@code XlaSparseActivationsUnstack} output and operands
+ * @return a new instance of XlaSparseActivationsUnstack
+ */
+ @Endpoint(
+ describeByClass = true
+ )
+ public static XlaSparseActivationsUnstack create(Scope scope,
+ Operand stackedActivations, Long numTables, List sampleCounts,
+ List features, Boolean interleaved, Class dtype) {
+ OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseActivationsUnstack");
+ opBuilder.addInput(stackedActivations.asOutput());
+ opBuilder.setAttr("num_tables", numTables);
+ long[] sampleCountsArray = new long[sampleCounts.size()];
+ for (int i = 0 ; i < sampleCountsArray.length ; i++) {
+ sampleCountsArray[i] = sampleCounts.get(i);
+ }
+ opBuilder.setAttr("sample_counts", sampleCountsArray);
+ long[] featuresArray = new long[features.size()];
+ for (int i = 0 ; i < featuresArray.length ; i++) {
+ featuresArray[i] = features.get(i);
+ }
+ opBuilder.setAttr("features", featuresArray);
+ opBuilder.setAttr("interleaved", interleaved);
+ opBuilder.setAttr("dtype", Operands.toDataType(dtype));
+ return new XlaSparseActivationsUnstack<>(opBuilder.build());
+ }
+
+ /**
+ * Gets unstackedActivations.
+ *
+ * @return unstackedActivations.
+ */
+ public List> unstackedActivations() {
+ return unstackedActivations;
+ }
+
+ @Override
+ @SuppressWarnings({"rawtypes", "unchecked"})
+ public Iterator> iterator() {
+ return (Iterator) unstackedActivations.iterator();
+ }
+
+ @OpInputsMetadata(
+ outputsClass = XlaSparseActivationsUnstack.class
+ )
+ public static class Inputs extends RawOpInputs> {
+ /**
+ * The stackedActivations input
+ */
+ public final Operand stackedActivations;
+
+ /**
+ * The sampleCounts attribute
+ */
+ public final long[] sampleCounts;
+
+ /**
+ * The features attribute
+ */
+ public final long[] features;
+
+ /**
+ * The interleaved attribute
+ */
+ public final boolean interleaved;
+
+ /**
+ * The inputDtype attribute
+ */
+ public final DataType inputDtype;
+
+ /**
+ * The dtype attribute
+ */
+ public final DataType dtype;
+
+ public Inputs(GraphOperation op) {
+ super(new XlaSparseActivationsUnstack<>(op), op, Arrays.asList("sample_counts", "features", "interleaved", "input_dtype", "dtype"));
+ int inputIndex = 0;
+ stackedActivations = (Operand) op.input(inputIndex++);
+ sampleCounts = op.attributes().getAttrIntList("sample_counts");
+ features = op.attributes().getAttrIntList("features");
+ interleaved = op.attributes().getAttrBool("interleaved");
+ inputDtype = op.attributes().getAttrType("input_dtype");
+ dtype = op.attributes().getAttrType("dtype");
+ }
+ }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.java
new file mode 100644
index 00000000000..0fd2a1347bc
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.java
@@ -0,0 +1,374 @@
+/* Copyright 2018-2023 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.xla;
+
+import java.util.Arrays;
+import org.tensorflow.ConcreteFunction;
+import org.tensorflow.GraphOperation;
+import org.tensorflow.Operand;
+import org.tensorflow.Operation;
+import org.tensorflow.OperationBuilder;
+import org.tensorflow.Output;
+import org.tensorflow.op.RawOp;
+import org.tensorflow.op.RawOpInputs;
+import org.tensorflow.op.Scope;
+import org.tensorflow.op.annotation.Endpoint;
+import org.tensorflow.op.annotation.OpInputsMetadata;
+import org.tensorflow.op.annotation.OpMetadata;
+import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.TInt32;
+
+/**
+ * The XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput operation
+ */
+@OpMetadata(
+ opType = XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.OP_NAME,
+ inputsClass = XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.Inputs.class
+)
+@Operator(
+ group = "xla"
+)
+public final class XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput extends RawOp {
+ /**
+ * The name of this op, as known by TensorFlow core engine
+ */
+ public static final String OP_NAME = "XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput";
+
+ private Output updatedEmbeddingTable;
+
+ private Output updatedAccumulator;
+
+ private Output updatedWeights;
+
+ public XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput(Operation operation) {
+ super(operation, OP_NAME);
+ int outputIdx = 0;
+ updatedEmbeddingTable = operation.output(outputIdx++);
+ updatedAccumulator = operation.output(outputIdx++);
+ updatedWeights = operation.output(outputIdx++);
+ }
+
+ /**
+ * Factory method to create a class wrapping a new XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput operation.
+ *
+ * @param scope current scope
+ * @param rowPointers The rowPointers value
+ * @param sortedSampleIds The sortedSampleIds value
+ * @param sortedTokenIds The sortedTokenIds value
+ * @param sortedPosIds The sortedPosIds value
+ * @param sortedGains The sortedGains value
+ * @param weights The weights value
+ * @param preservedValencies The preservedValencies value
+ * @param preservedVectors The preservedVectors value
+ * @param preservedWeights The preservedWeights value
+ * @param activationGradients The activationGradients value
+ * @param learningRate The learningRate value
+ * @param combinerWeightsLearningRate The combinerWeightsLearningRate value
+ * @param embeddingTable The embeddingTable value
+ * @param accumulator The accumulator value
+ * @param maxValency The value of the maxValency attribute
+ * @param numWeights The value of the numWeights attribute
+ * @param combinerTableVjpComputation The value of the combinerTableVjpComputation attribute
+ * @param combinerWeightsVjpComputation The value of the combinerWeightsVjpComputation attribute
+ * @param tableName The value of the tableName attribute
+ * @param options carries optional attribute values
+ * @return a new instance of XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput
+ */
+ @Endpoint(
+ describeByClass = true
+ )
+ public static XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput create(Scope scope,
+ Operand rowPointers, Operand sortedSampleIds, Operand sortedTokenIds,
+ Operand sortedPosIds, Operand sortedGains, Operand weights,
+ Operand preservedValencies, Operand preservedVectors,
+ Operand preservedWeights, Operand activationGradients,
+ Operand learningRate, Operand combinerWeightsLearningRate,
+ Operand embeddingTable, Operand accumulator, Long maxValency,
+ Long numWeights, ConcreteFunction combinerTableVjpComputation,
+ ConcreteFunction combinerWeightsVjpComputation, String tableName, Options... options) {
+ OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput");
+ opBuilder.addInput(rowPointers.asOutput());
+ opBuilder.addInput(sortedSampleIds.asOutput());
+ opBuilder.addInput(sortedTokenIds.asOutput());
+ opBuilder.addInput(sortedPosIds.asOutput());
+ opBuilder.addInput(sortedGains.asOutput());
+ opBuilder.addInput(weights.asOutput());
+ opBuilder.addInput(preservedValencies.asOutput());
+ opBuilder.addInput(preservedVectors.asOutput());
+ opBuilder.addInput(preservedWeights.asOutput());
+ opBuilder.addInput(activationGradients.asOutput());
+ opBuilder.addInput(learningRate.asOutput());
+ opBuilder.addInput(combinerWeightsLearningRate.asOutput());
+ opBuilder.addInput(embeddingTable.asOutput());
+ opBuilder.addInput(accumulator.asOutput());
+ opBuilder.setAttr("max_valency", maxValency);
+ opBuilder.setAttr("num_weights", numWeights);
+ opBuilder.setAttr("combiner_table_vjp_computation", combinerTableVjpComputation);
+ opBuilder.setAttr("combiner_weights_vjp_computation", combinerWeightsVjpComputation);
+ opBuilder.setAttr("table_name", tableName);
+ if (options != null) {
+ for (Options opts : options) {
+ if (opts.clipWeightMin != null) {
+ opBuilder.setAttr("clip_weight_min", opts.clipWeightMin);
+ }
+ if (opts.clipWeightMax != null) {
+ opBuilder.setAttr("clip_weight_max", opts.clipWeightMax);
+ }
+ if (opts.numSparsecoresPerDevice != null) {
+ opBuilder.setAttr("num_sparsecores_per_device", opts.numSparsecoresPerDevice);
+ }
+ }
+ }
+ return new XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput(opBuilder.build());
+ }
+
+ /**
+ * Sets the clipWeightMin option.
+ *
+ * @param clipWeightMin the clipWeightMin option
+ * @return this Options instance.
+ */
+ public static Options clipWeightMin(Float clipWeightMin) {
+ return new Options().clipWeightMin(clipWeightMin);
+ }
+
+ /**
+ * Sets the clipWeightMax option.
+ *
+ * @param clipWeightMax the clipWeightMax option
+ * @return this Options instance.
+ */
+ public static Options clipWeightMax(Float clipWeightMax) {
+ return new Options().clipWeightMax(clipWeightMax);
+ }
+
+ /**
+ * Sets the numSparsecoresPerDevice option.
+ *
+ * @param numSparsecoresPerDevice the numSparsecoresPerDevice option
+ * @return this Options instance.
+ */
+ public static Options numSparsecoresPerDevice(Long numSparsecoresPerDevice) {
+ return new Options().numSparsecoresPerDevice(numSparsecoresPerDevice);
+ }
+
+ /**
+ * Gets updatedEmbeddingTable.
+ *
+ * @return updatedEmbeddingTable.
+ */
+ public Output updatedEmbeddingTable() {
+ return updatedEmbeddingTable;
+ }
+
+ /**
+ * Gets updatedAccumulator.
+ *
+ * @return updatedAccumulator.
+ */
+ public Output