Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

org.tensorflow.op.core

Classes

Abort Raise a exception to abort the process when called.
Abort.Options Optional attributes for Abort
All Computes the "logical and" of elements across dimensions of a tensor.
All.Options Optional attributes for All
AllToAll <T> An Op to exchange data across TPU replicas.
AnonymousIteratorV2 A container for an iterator resource.
AnonymousMemoryCache
AnonymousMultiDeviceIterator A container for a multi device iterator resource.
AnonymousRandomSeedGenerator
AnonymousSeedGenerator
Any Computes the "logical or" of elements across dimensions of a tensor.
Any.Options Optional attributes for Any
ApplyAdagradV2 <T> Update '*var' according to the adagrad scheme.
ApplyAdagradV2.Options Optional attributes for ApplyAdagradV2
AssertCardinalityDataset
AssertNextDataset A transformation that asserts which transformations happen next.
AssertThat Asserts that the given condition is true.
AssertThat.Options Optional attributes for AssertThat
Assign <T> Update 'ref' by assigning 'value' to it.
Assign.Options Optional attributes for Assign
AssignAdd <T> Update 'ref' by adding 'value' to it.
AssignAdd.Options Optional attributes for AssignAdd
AssignAddVariableOp Adds a value to the current value of a variable.
AssignSub <T> Update 'ref' by subtracting 'value' from it.
AssignSub.Options Optional attributes for AssignSub
AssignSubVariableOp Subtracts a value from the current value of a variable.
AssignVariableOp Assigns a new value to a variable.
AutoShardDataset Creates a dataset that shards the input dataset.
AutoShardDataset.Options Optional attributes for AutoShardDataset
BandedTriangularSolve <T>
BandedTriangularSolve.Options Optional attributes for BandedTriangularSolve
Barrier Defines a barrier that persists across different graph executions.
Barrier.Options Optional attributes for Barrier
BarrierClose Closes the given barrier.
BarrierClose.Options Optional attributes for BarrierClose
BarrierIncompleteSize Computes the number of incomplete elements in the given barrier.
BarrierInsertMany For each key, assigns the respective value to the specified component.
BarrierReadySize Computes the number of complete elements in the given barrier.
BarrierTakeMany Takes the given number of completed elements from a barrier.
BarrierTakeMany.Options Optional attributes for BarrierTakeMany
Batch Batches all input tensors nondeterministically.
Batch.Options Optional attributes for Batch
BatchMatMulV2 <T> Multiplies slices of two tensors in batches.
BatchMatMulV2.Options Optional attributes for BatchMatMulV2
BatchToSpace <T> BatchToSpace for 4-D tensors of type T.
BatchToSpaceNd <T> BatchToSpace for N-D tensors of type T.
BesselI0 <T extends Number>
BesselI1 <T extends Number>
BesselJ0 <T extends Number>
BesselJ1 <T extends Number>
BesselK0 <T extends Number>
BesselK0e <T extends Number>
BesselK1 <T extends Number>
BesselK1e <T extends Number>
BesselY0 <T extends Number>
BesselY1 <T extends Number>
Bitcast <U> Bitcasts a tensor from one type to another without copying data.
BlockLSTM <T extends Number> Computes the LSTM cell forward propagation for all the time steps.
BlockLSTM.Options Optional attributes for BlockLSTM
BlockLSTMGrad <T extends Number> Computes the LSTM cell backward propagation for the entire time sequence.
BlockLSTMGradV2 <T extends Number> Computes the LSTM cell backward propagation for the entire time sequence.
BlockLSTMV2 <T extends Number> Computes the LSTM cell forward propagation for all the time steps.
BlockLSTMV2.Options Optional attributes for BlockLSTMV2
BoostedTreesAggregateStats Aggregates the summary of accumulated stats for the batch.
BoostedTreesBucketize Bucketize each feature based on bucket boundaries.
BoostedTreesCalculateBestFeatureSplit Calculates gains for each feature and returns the best possible split information for the feature.
BoostedTreesCalculateBestFeatureSplit.Options Optional attributes for BoostedTreesCalculateBestFeatureSplit
BoostedTreesCalculateBestFeatureSplitV2 Calculates gains for each feature and returns the best possible split information for each node.
BoostedTreesCalculateBestGainsPerFeature Calculates gains for each feature and returns the best possible split information for the feature.
BoostedTreesCenterBias Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior.
BoostedTreesCreateEnsemble Creates a tree ensemble model and returns a handle to it.
BoostedTreesCreateQuantileStreamResource Create the Resource for Quantile Streams.
BoostedTreesCreateQuantileStreamResource.Options Optional attributes for BoostedTreesCreateQuantileStreamResource
BoostedTreesDeserializeEnsemble Deserializes a serialized tree ensemble config and replaces current tree

ensemble.

BoostedTreesEnsembleResourceHandleOp Creates a handle to a BoostedTreesEnsembleResource
BoostedTreesEnsembleResourceHandleOp.Options Optional attributes for BoostedTreesEnsembleResourceHandleOp
BoostedTreesExampleDebugOutputs Debugging/model interpretability outputs for each example.
BoostedTreesFlushQuantileSummaries Flush the quantile summaries from each quantile stream resource.
BoostedTreesGetEnsembleStates Retrieves the tree ensemble resource stamp token, number of trees and growing statistics.
BoostedTreesMakeQuantileSummaries Makes the summary of quantiles for the batch.
BoostedTreesMakeStatsSummary Makes the summary of accumulated stats for the batch.
BoostedTreesPredict Runs multiple additive regression ensemble predictors on input instances and

computes the logits.

BoostedTreesQuantileStreamResourceAddSummaries Add the quantile summaries to each quantile stream resource.
BoostedTreesQuantileStreamResourceDeserialize Deserialize bucket boundaries and ready flag into current QuantileAccumulator.
BoostedTreesQuantileStreamResourceFlush Flush the summaries for a quantile stream resource.
BoostedTreesQuantileStreamResourceFlush.Options Optional attributes for BoostedTreesQuantileStreamResourceFlush
BoostedTreesQuantileStreamResourceGetBucketBoundaries Generate the bucket boundaries for each feature based on accumulated summaries.
BoostedTreesQuantileStreamResourceHandleOp Creates a handle to a BoostedTreesQuantileStreamResource.
BoostedTreesQuantileStreamResourceHandleOp.Options Optional attributes for BoostedTreesQuantileStreamResourceHandleOp
BoostedTreesSerializeEnsemble Serializes the tree ensemble to a proto.
BoostedTreesSparseAggregateStats Aggregates the summary of accumulated stats for the batch.
BoostedTreesSparseCalculateBestFeatureSplit Calculates gains for each feature and returns the best possible split information for the feature.
BoostedTreesSparseCalculateBestFeatureSplit.Options Optional attributes for BoostedTreesSparseCalculateBestFeatureSplit
BoostedTreesTrainingPredict Runs multiple additive regression ensemble predictors on input instances and

computes the update to cached logits.

BoostedTreesUpdateEnsemble Updates the tree ensemble by either adding a layer to the last tree being grown

or by starting a new tree.

BoostedTreesUpdateEnsembleV2 Updates the tree ensemble by adding a layer to the last tree being grown

or by starting a new tree.

BoostedTreesUpdateEnsembleV2.Options Optional attributes for BoostedTreesUpdateEnsembleV2
BroadcastDynamicShape <T extends Number> Return the shape of s0 op s1 with broadcast.
BroadcastGradientArgs <T extends Number> Return the reduction indices for computing gradients of s0 op s1 with broadcast.
BroadcastTo <T> Broadcast an array for a compatible shape.
Bucketize Bucketizes 'input' based on 'boundaries'.
CacheDatasetV2
CheckNumericsV2 <T extends Number> Checks a tensor for NaN, -Inf and +Inf values.
ChooseFastestDataset
ClipByValue <T> Clips tensor values to a specified min and max.
CollectiveBcastRecvV2 <U> Receives a tensor value broadcast from another device.
CollectiveBcastRecvV2.Options Optional attributes for CollectiveBcastRecvV2
CollectiveBcastSendV2 <T> Broadcasts a tensor value to one or more other devices.
CollectiveBcastSendV2.Options Optional attributes for CollectiveBcastSendV2
CollectiveGather <T extends Number> Mutually accumulates multiple tensors of identical type and shape.
CollectiveGather.Options Optional attributes for CollectiveGather
CollectiveGatherV2 <T extends Number> Mutually accumulates multiple tensors of identical type and shape.
CollectiveGatherV2.Options Optional attributes for CollectiveGatherV2
CollectivePermute <T> An Op to permute tensors across replicated TPU instances.
CollectiveReduceV2 <T extends Number> Mutually reduces multiple tensors of identical type and shape.
CollectiveReduceV2.Options Optional attributes for CollectiveReduceV2
CombinedNonMaxSuppression Greedily selects a subset of bounding boxes in descending order of score,

This operation performs non_max_suppression on the inputs per batch, across all classes.

CombinedNonMaxSuppression.Options Optional attributes for CombinedNonMaxSuppression
CompressElement Compresses a dataset element.
ComputeBatchSize Computes the static batch size of a dataset sans partial batches.
Concat <T> Concatenates tensors along one dimension.
ConfigureDistributedTPU Sets up the centralized structures for a distributed TPU system.
ConfigureDistributedTPU.Options Optional attributes for ConfigureDistributedTPU
ConfigureTPUEmbedding Sets up TPUEmbedding in a distributed TPU system.
Constant <T> An operator producing a constant value.
ConsumeMutexLock This op consumes a lock created by `MutexLock`.
ControlTrigger Does nothing.
Copy <T> Copy a tensor from CPU-to-CPU or GPU-to-GPU.
Copy.Options Optional attributes for Copy
CopyHost <T> Copy a tensor to host.
CopyHost.Options Optional attributes for CopyHost
CountUpTo <T extends Number> Increments 'ref' until it reaches 'limit'.
CrossReplicaSum <T extends Number> An Op to sum inputs across replicated TPU instances.
CSRSparseMatrixComponents <T> Reads out the CSR components at batch `index`.
CSRSparseMatrixToDense <T> Convert a (possibly batched) CSRSparseMatrix to dense.
CSRSparseMatrixToSparseTensor <T> Converts a (possibly batched) CSRSparesMatrix to a SparseTensor.
CSVDataset
CSVDatasetV2
CTCLossV2 Calculates the CTC Loss (log probability) for each batch entry.
CTCLossV2.Options Optional attributes for CTCLossV2
CudnnRNNBackpropV3 <T extends Number> Backprop step of CudnnRNNV3.
CudnnRNNBackpropV3.Options Optional attributes for CudnnRNNBackpropV3
CudnnRNNCanonicalToParamsV2 <T extends Number> Converts CudnnRNN params from canonical form to usable form.
CudnnRNNCanonicalToParamsV2.Options Optional attributes for CudnnRNNCanonicalToParamsV2
CudnnRNNParamsToCanonicalV2 <T extends Number> Retrieves CudnnRNN params in canonical form.
CudnnRNNParamsToCanonicalV2.Options Optional attributes for CudnnRNNParamsToCanonicalV2
CudnnRNNV3 <T extends Number> A RNN backed by cuDNN.
CudnnRNNV3.Options Optional attributes for CudnnRNNV3
CumulativeLogsumexp <T extends Number> Compute the cumulative product of the tensor `x` along `axis`.
CumulativeLogsumexp.Options Optional attributes for CumulativeLogsumexp
DataServiceDataset Creates a dataset that reads data from the tf.data service.
DataServiceDataset.Options Optional attributes for DataServiceDataset
DataServiceDatasetV2 Creates a dataset that reads data from the tf.data service.
DataServiceDatasetV2.Options Optional attributes for DataServiceDatasetV2
DatasetCardinality Returns the cardinality of `input_dataset`.
DatasetFromGraph Creates a dataset from the given `graph_def`.
DatasetToGraphV2 Returns a serialized GraphDef representing `input_dataset`.
DatasetToGraphV2.Options Optional attributes for DatasetToGraphV2
Dawsn <T extends Number>
DebugGradientIdentity <T> Identity op for gradient debugging.
DebugGradientRefIdentity <T> Identity op for gradient debugging.
DebugIdentity <T> Provides an identity mapping of the non-Ref type input tensor for debugging.
DebugIdentity.Options Optional attributes for DebugIdentity
DebugIdentityV2 <T> Debug Identity V2 Op.
DebugIdentityV2.Options Optional attributes for DebugIdentityV2
DebugNanCount Debug NaN Value Counter Op.
DebugNanCount.Options Optional attributes for DebugNanCount
DebugNumericSummary Debug Numeric Summary Op.
DebugNumericSummary.Options Optional attributes for DebugNumericSummary
DebugNumericSummaryV2 <U extends Number> Debug Numeric Summary V2 Op.
DebugNumericSummaryV2.Options Optional attributes for DebugNumericSummaryV2
DecodeImage <T extends Number> Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
DecodeImage.Options Optional attributes for DecodeImage
DecodePaddedRaw <T extends Number> Reinterpret the bytes of a string as a vector of numbers.
DecodePaddedRaw.Options Optional attributes for DecodePaddedRaw
DecodeProto The op extracts fields from a serialized protocol buffers message into tensors.
DecodeProto.Options Optional attributes for DecodeProto
DeepCopy <T> Makes a copy of `x`.
DeleteIterator A container for an iterator resource.
DeleteMemoryCache
DeleteMultiDeviceIterator A container for an iterator resource.
DeleteRandomSeedGenerator
DeleteSeedGenerator
DeleteSessionTensor Delete the tensor specified by its handle in the session.
DenseBincount <U extends Number> Counts the number of occurrences of each value in an integer array.
DenseBincount.Options Optional attributes for DenseBincount
DenseCountSparseOutput <U extends Number> Performs sparse-output bin counting for a tf.tensor input.
DenseCountSparseOutput.Options Optional attributes for DenseCountSparseOutput
DenseToCSRSparseMatrix Converts a dense tensor to a (possibly batched) CSRSparseMatrix.
DestroyResourceOp Deletes the resource specified by the handle.
DestroyResourceOp.Options Optional attributes for DestroyResourceOp
DestroyTemporaryVariable <T> Destroys the temporary variable and returns its final value.
DeviceIndex Return the index of device the op runs.
DirectedInterleaveDataset A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
DrawBoundingBoxesV2 <T extends Number> Draw bounding boxes on a batch of images.
DummyIterationCounter
DummyMemoryCache
DummySeedGenerator
DynamicPartition <T> Partitions `data` into `num_partitions` tensors using indices from `partitions`.
DynamicStitch <T> Interleave the values from the `data` tensors into a single tensor.
EditDistance Computes the (possibly normalized) Levenshtein Edit Distance.
EditDistance.Options Optional attributes for EditDistance
Eig <U> Computes the eigen decomposition of one or more square matrices.
Eig.Options Optional attributes for Eig
Einsum <T> Tensor contraction according to Einstein summation convention.
Empty <T> Creates a tensor with the given shape.
Empty.Options Optional attributes for Empty
EmptyTensorList Creates and returns an empty tensor list.
EmptyTensorMap Creates and returns an empty tensor map.
EncodeProto The op serializes protobuf messages provided in the input tensors.
EncodeProto.Options Optional attributes for EncodeProto
EnqueueTPUEmbeddingIntegerBatch An op that enqueues a list of input batch tensors to TPUEmbedding.
EnqueueTPUEmbeddingIntegerBatch.Options Optional attributes for EnqueueTPUEmbeddingIntegerBatch
EnqueueTPUEmbeddingRaggedTensorBatch Eases the porting of code that uses tf.nn.embedding_lookup().
EnqueueTPUEmbeddingRaggedTensorBatch.Options Optional attributes for EnqueueTPUEmbeddingRaggedTensorBatch
EnqueueTPUEmbeddingSparseBatch An op that enqueues TPUEmbedding input indices from a SparseTensor.
EnqueueTPUEmbeddingSparseBatch.Options Optional attributes for EnqueueTPUEmbeddingSparseBatch
EnqueueTPUEmbeddingSparseTensorBatch Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
EnqueueTPUEmbeddingSparseTensorBatch.Options Optional attributes for EnqueueTPUEmbeddingSparseTensorBatch
EnsureShape <T> Ensures that the tensor's shape matches the expected shape.
Enter <T> Creates or finds a child frame, and makes `data` available to the child frame.
Enter.Options Optional attributes for Enter
Erfinv <T extends Number>
EuclideanNorm <T> Computes the euclidean norm of elements across dimensions of a tensor.
EuclideanNorm.Options Optional attributes for EuclideanNorm
Exit <T> Exits the current frame to its parent frame.
ExpandDims <T> Inserts a dimension of 1 into a tensor's shape.
ExperimentalAutoShardDataset Creates a dataset that shards the input dataset.
ExperimentalAutoShardDataset.Options Optional attributes for ExperimentalAutoShardDataset
ExperimentalBytesProducedStatsDataset Records the bytes size of each element of `input_dataset` in a StatsAggregator.
ExperimentalChooseFastestDataset
ExperimentalDatasetCardinality Returns the cardinality of `input_dataset`.
ExperimentalDatasetToTFRecord Writes the given dataset to the given file using the TFRecord format.
ExperimentalDenseToSparseBatchDataset Creates a dataset that batches input elements into a SparseTensor.
ExperimentalLatencyStatsDataset Records the latency of producing `input_dataset` elements in a StatsAggregator.
ExperimentalMatchingFilesDataset
ExperimentalMaxIntraOpParallelismDataset Creates a dataset that overrides the maximum intra-op parallelism.
ExperimentalParseExampleDataset Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.
ExperimentalParseExampleDataset.Options Optional attributes for ExperimentalParseExampleDataset
ExperimentalPrivateThreadPoolDataset Creates a dataset that uses a custom thread pool to compute `input_dataset`.
ExperimentalRandomDataset Creates a Dataset that returns pseudorandom numbers.
ExperimentalRebatchDataset Creates a dataset that changes the batch size.
ExperimentalRebatchDataset.Options Optional attributes for ExperimentalRebatchDataset
ExperimentalSetStatsAggregatorDataset
ExperimentalSlidingWindowDataset Creates a dataset that passes a sliding window over `input_dataset`.
ExperimentalSqlDataset Creates a dataset that executes a SQL query and emits rows of the result set.
ExperimentalStatsAggregatorHandle Creates a statistics manager resource.
ExperimentalStatsAggregatorHandle.Options Optional attributes for ExperimentalStatsAggregatorHandle
ExperimentalStatsAggregatorSummary Produces a summary of any statistics recorded by the given statistics manager.
ExperimentalUnbatchDataset A dataset that splits the elements of its input into multiple elements.
Expint <T extends Number>
ExtractGlimpseV2 Extracts a glimpse from the input tensor.
ExtractGlimpseV2.Options Optional attributes for ExtractGlimpseV2
ExtractVolumePatches <T extends Number> Extract `patches` from `input` and put them in the `"depth"` output dimension.
Fill <U> Creates a tensor filled with a scalar value.
FinalizeDataset Creates a dataset by applying `tf.data.Options` to `input_dataset`.
FinalizeDataset.Options Optional attributes for FinalizeDataset
Fingerprint Generates fingerprint values.
FresnelCos <T extends Number>
FresnelSin <T extends Number>
FusedBatchNormGradV3 <T extends Number, U extends Number> Gradient for batch normalization.
FusedBatchNormGradV3.Options Optional attributes for FusedBatchNormGradV3
FusedBatchNormV3 <T extends Number, U extends Number> Batch normalization.
FusedBatchNormV3.Options Optional attributes for FusedBatchNormV3
Gather <T> Gather slices from `params` axis `axis` according to `indices`.
Gather.Options Optional attributes for Gather
GatherNd <T> Gather slices from `params` into a Tensor with shape specified by `indices`.
GenerateBoundingBoxProposals This op produces Region of Interests from given bounding boxes(bbox_deltas) encoded wrt anchors according to eq.2 in arXiv:1506.01497

The op selects top `pre_nms_topn` scoring boxes, decodes them with respect to anchors, applies non-maximal suppression on overlapping boxes with higher than `nms_threshold` intersection-over-union (iou) value, discarding boxes where shorter side is less than `min_size`.

GenerateBoundingBoxProposals.Options Optional attributes for GenerateBoundingBoxProposals
GetOptions Returns the `tf.data.Options` attached to `input_dataset`.
GetSessionHandle Store the input tensor in the state of the current session.
GetSessionTensor <T> Get the value of the tensor specified by its handle.
Gradients Adds operations to compute the partial derivatives of sum of y s w.r.t x s, i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2...

If Options.dx() values are set, they are as the initial symbolic partial derivatives of some loss function L w.r.t.

Gradients.Options Optional attributes for Gradients
GRUBlockCell <T extends Number> Computes the GRU cell forward propagation for 1 time step.
GRUBlockCellGrad <T extends Number> Computes the GRU cell back-propagation for 1 time step.
GuaranteeConst <T> Gives a guarantee to the TF runtime that the input tensor is a constant.
HashTable Creates a non-initialized hash table.
HashTable.Options Optional attributes for HashTable
HistogramFixedWidth <U extends Number> Return histogram of values.
Identity <T> Return a tensor with the same shape and contents as the input tensor or value.
IdentityN Returns a list of tensors with the same shapes and contents as the input

tensors.

IgnoreErrorsDataset Creates a dataset that contains the elements of `input_dataset` ignoring errors.
IgnoreErrorsDataset.Options Optional attributes for IgnoreErrorsDataset
ImageProjectiveTransformV2 <T extends Number> Applies the given transform to each of the images.
ImageProjectiveTransformV2.Options Optional attributes for ImageProjectiveTransformV2
ImageProjectiveTransformV3 <T extends Number> Applies the given transform to each of the images.
ImageProjectiveTransformV3.Options Optional attributes for ImageProjectiveTransformV3
ImmutableConst <T> Returns immutable tensor from memory region.
InfeedDequeue <T> A placeholder op for a value that will be fed into the computation.
InfeedDequeueTuple Fetches multiple values from infeed as an XLA tuple.
InfeedEnqueue An op which feeds a single Tensor value into the computation.
InfeedEnqueue.Options Optional attributes for InfeedEnqueue
InfeedEnqueuePrelinearizedBuffer An op which enqueues prelinearized buffer into TPU infeed.
InfeedEnqueuePrelinearizedBuffer.Options Optional attributes for InfeedEnqueuePrelinearizedBuffer
InfeedEnqueueTuple Feeds multiple Tensor values into the computation as an XLA tuple.
InfeedEnqueueTuple.Options Optional attributes for InfeedEnqueueTuple
InitializeTable Table initializer that takes two tensors for keys and values respectively.
InitializeTableFromDataset
InitializeTableFromTextFile Initializes a table from a text file.
InitializeTableFromTextFile.Options Optional attributes for InitializeTableFromTextFile
InplaceAdd <T> Adds v into specified rows of x.
InplaceSub <T> Subtracts `v` into specified rows of `x`.
InplaceUpdate <T> Updates specified rows 'i' with values 'v'.
IsBoostedTreesEnsembleInitialized Checks whether a tree ensemble has been initialized.
IsBoostedTreesQuantileStreamResourceInitialized Checks whether a quantile stream has been initialized.
IsotonicRegression <U extends Number> Solves a batch of isotonic regression problems.
IsVariableInitialized Checks whether a tensor has been initialized.
IteratorGetDevice Returns the name of the device on which `resource` has been placed.
KMC2ChainInitialization Returns the index of a data point that should be added to the seed set.
KmeansPlusPlusInitialization Selects num_to_sample rows of input using the KMeans++ criterion.
KthOrderStatistic Computes the Kth order statistic of a data set.
LinSpace <T extends Number> Generates values in an interval.
LMDBDataset Creates a dataset that emits the key-value pairs in one or more LMDB files.
LoadTPUEmbeddingAdadeltaParameters Load Adadelta embedding parameters.
LoadTPUEmbeddingAdadeltaParameters.Options Optional attributes for LoadTPUEmbeddingAdadeltaParameters
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug Load Adadelta parameters with debug support.
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingAdadeltaParametersGradAccumDebug
LoadTPUEmbeddingAdagradParameters Load Adagrad embedding parameters.
LoadTPUEmbeddingAdagradParameters.Options Optional attributes for LoadTPUEmbeddingAdagradParameters
LoadTPUEmbeddingAdagradParametersGradAccumDebug Load Adagrad embedding parameters with debug support.
LoadTPUEmbeddingAdagradParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingAdagradParametersGradAccumDebug
LoadTPUEmbeddingADAMParameters Load ADAM embedding parameters.
LoadTPUEmbeddingADAMParameters.Options Optional attributes for LoadTPUEmbeddingADAMParameters
LoadTPUEmbeddingADAMParametersGradAccumDebug Load ADAM embedding parameters with debug support.
LoadTPUEmbeddingADAMParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingADAMParametersGradAccumDebug
LoadTPUEmbeddingCenteredRMSPropParameters Load centered RMSProp embedding parameters.
LoadTPUEmbeddingCenteredRMSPropParameters.Options Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters
LoadTPUEmbeddingFrequencyEstimatorParameters Load frequency estimator embedding parameters.
LoadTPUEmbeddingFrequencyEstimatorParameters.Options Optional attributes for LoadTPUEmbeddingFrequencyEstimatorParameters
LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug Load frequency estimator embedding parameters with debug support.
LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
LoadTPUEmbeddingFTRLParameters Load FTRL embedding parameters.
LoadTPUEmbeddingFTRLParameters.Options Optional attributes for LoadTPUEmbeddingFTRLParameters
LoadTPUEmbeddingFTRLParametersGradAccumDebug Load FTRL embedding parameters with debug support.
LoadTPUEmbeddingFTRLParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingFTRLParametersGradAccumDebug
LoadTPUEmbeddingMDLAdagradLightParameters Load MDL Adagrad Light embedding parameters.
LoadTPUEmbeddingMDLAdagradLightParameters.Options Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters
LoadTPUEmbeddingMomentumParameters Load Momentum embedding parameters.
LoadTPUEmbeddingMomentumParameters.Options Optional attributes for LoadTPUEmbeddingMomentumParameters
LoadTPUEmbeddingMomentumParametersGradAccumDebug Load Momentum embedding parameters with debug support.
LoadTPUEmbeddingMomentumParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingMomentumParametersGradAccumDebug
LoadTPUEmbeddingProximalAdagradParameters Load proximal Adagrad embedding parameters.
LoadTPUEmbeddingProximalAdagradParameters.Options Optional attributes for LoadTPUEmbeddingProximalAdagradParameters
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug Load proximal Adagrad embedding parameters with debug support.
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug
LoadTPUEmbeddingProximalYogiParameters
LoadTPUEmbeddingProximalYogiParameters.Options Optional attributes for LoadTPUEmbeddingProximalYogiParameters
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingProximalYogiParametersGradAccumDebug
LoadTPUEmbeddingRMSPropParameters Load RMSProp embedding parameters.
LoadTPUEmbeddingRMSPropParameters.Options Optional attributes for LoadTPUEmbeddingRMSPropParameters
LoadTPUEmbeddingRMSPropParametersGradAccumDebug Load RMSProp embedding parameters with debug support.
LoadTPUEmbeddingRMSPropParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingRMSPropParametersGradAccumDebug
LoadTPUEmbeddingStochasticGradientDescentParameters Load SGD embedding parameters.
LoadTPUEmbeddingStochasticGradientDescentParameters.Options Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug Load SGD embedding parameters.
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
LookupTableExport <T, U> Outputs all keys and values in the table.
LookupTableFind <U> Looks up keys in a table, outputs the corresponding values.
LookupTableImport Replaces the contents of the table with the specified keys and values.
LookupTableInsert Updates the table to associates keys with values.
LookupTableRemove Removes keys and its associated values from a table.
LookupTableSize Computes the number of elements in the given table.
LoopCond Forwards the input to the output.
LowerBound <U extends Number> Applies lower_bound(sorted_search_values, values) along each row.
LSTMBlockCell <T extends Number> Computes the LSTM cell forward propagation for 1 time step.
LSTMBlockCell.Options Optional attributes for LSTMBlockCell
LSTMBlockCellGrad <T extends Number> Computes the LSTM cell backward propagation for 1 timestep.
Lu <T, U extends Number> Computes the LU decomposition of one or more square matrices.
MakeUnique Make all elements in the non-Batch dimension unique, but \"close\" to

their initial value.

MapClear Op removes all elements in the underlying container.
MapClear.Options Optional attributes for MapClear
MapIncompleteSize Op returns the number of incomplete elements in the underlying container.
MapIncompleteSize.Options Optional attributes for MapIncompleteSize
MapPeek Op peeks at the values at the specified key.
MapPeek.Options Optional attributes for MapPeek
MapSize Op returns the number of elements in the underlying container.
MapSize.Options Optional attributes for MapSize
MapStage Stage (key, values) in the underlying container which behaves like a hashtable.
MapStage.Options Optional attributes for MapStage
MapUnstage Op removes and returns the values associated with the key

from the underlying container.

MapUnstage.Options Optional attributes for MapUnstage
MapUnstageNoKey Op removes and returns a random (key, value)

from the underlying container.

MapUnstageNoKey.Options Optional attributes for MapUnstageNoKey
MatrixDiagPartV2 <T> Returns the batched diagonal part of a batched tensor.
MatrixDiagPartV3 <T> Returns the batched diagonal part of a batched tensor.
MatrixDiagPartV3.Options Optional attributes for MatrixDiagPartV3
MatrixDiagV2 <T> Returns a batched diagonal tensor with given batched diagonal values.
MatrixDiagV3 <T> Returns a batched diagonal tensor with given batched diagonal values.
MatrixDiagV3.Options Optional attributes for MatrixDiagV3
MatrixSetDiagV2 <T> Returns a batched matrix tensor with new batched diagonal values.
MatrixSetDiagV3 <T> Returns a batched matrix tensor with new batched diagonal values.
MatrixSetDiagV3.Options Optional attributes for MatrixSetDiagV3
Max <T> Computes the maximum of elements across dimensions of a tensor.
Max.Options Optional attributes for Max
MaxIntraOpParallelismDataset Creates a dataset that overrides the maximum intra-op parallelism.
Merge <T> Forwards the value of an available tensor from `inputs` to `output`.
Min <T> Computes the minimum of elements across dimensions of a tensor.
Min.Options Optional attributes for Min
MirrorPad <T> Pads a tensor with mirrored values.
MirrorPadGrad <T> Gradient op for `MirrorPad` op.
MlirPassthroughOp Wraps an arbitrary MLIR computation expressed as a module with a main() function.
MulNoNan <T> Returns x * y element-wise.
MutableDenseHashTable Creates an empty hash table that uses tensors as the backing store.
MutableDenseHashTable.Options Optional attributes for MutableDenseHashTable
MutableHashTable Creates an empty hash table.
MutableHashTable.Options Optional attributes for MutableHashTable
MutableHashTableOfTensors Creates an empty hash table.
MutableHashTableOfTensors.Options Optional attributes for MutableHashTableOfTensors
Mutex Creates a Mutex resource that can be locked by `MutexLock`.
Mutex.Options Optional attributes for Mutex
MutexLock Locks a mutex resource.
NcclAllReduce <T extends Number> Outputs a tensor containing the reduction across all input tensors.
NcclBroadcast <T extends Number> Sends `input` to all devices that are connected to the output.
NcclReduce <T extends Number> Reduces `input` from `num_devices` using `reduction` to a single device.
Ndtri <T extends Number>
NearestNeighbors Selects the k nearest centers for each point.
NextAfter <T extends Number> Returns the next representable value of `x1` in the direction of `x2`, element-wise.
NextIteration <T> Makes its input available to the next iteration.
NonDeterministicInts <U> Non-deterministically generates some integers.
NonMaxSuppressionV5 <T extends Number> Greedily selects a subset of bounding boxes in descending order of score,

pruning away boxes that have high intersection-over-union (IOU) overlap with previously selected boxes.

NonMaxSuppressionV5.Options Optional attributes for NonMaxSuppressionV5
NonSerializableDataset
NoOp Does nothing.
OneHot <U> Returns a one-hot tensor.
OneHot.Options Optional attributes for OneHot
OnesLike <T> Returns a tensor of ones with the same shape and type as x.
OptimizeDatasetV2 Creates a dataset by applying related optimizations to `input_dataset`.
OptimizeDatasetV2.Options Optional attributes for OptimizeDatasetV2
OptionsDataset Creates a dataset by attaching tf.data.Options to `input_dataset`.
OrderedMapClear Op removes all elements in the underlying container.
OrderedMapClear.Options Optional attributes for OrderedMapClear
OrderedMapIncompleteSize Op returns the number of incomplete elements in the underlying container.
OrderedMapIncompleteSize.Options Optional attributes for OrderedMapIncompleteSize
OrderedMapPeek Op peeks at the values at the specified key.
OrderedMapPeek.Options Optional attributes for OrderedMapPeek
OrderedMapSize Op returns the number of elements in the underlying container.
OrderedMapSize.Options Optional attributes for OrderedMapSize
OrderedMapStage Stage (key, values) in the underlying container which behaves like a ordered

associative container.

OrderedMapStage.Options Optional attributes for OrderedMapStage
OrderedMapUnstage Op removes and returns the values associated with the key

from the underlying container.

OrderedMapUnstage.Options Optional attributes for OrderedMapUnstage
OrderedMapUnstageNoKey Op removes and returns the (key, value) element with the smallest

key from the underlying container.

OrderedMapUnstageNoKey.Options Optional attributes for OrderedMapUnstageNoKey
OutfeedDequeue <T> Retrieves a single tensor from the computation outfeed.
OutfeedDequeue.Options Optional attributes for OutfeedDequeue
OutfeedDequeueTuple Retrieve multiple values from the computation outfeed.
OutfeedDequeueTuple.Options Optional attributes for OutfeedDequeueTuple
OutfeedDequeueTupleV2 Retrieve multiple values from the computation outfeed.
OutfeedDequeueV2 <T> Retrieves a single tensor from the computation outfeed.
OutfeedEnqueue Enqueue a Tensor on the computation outfeed.
OutfeedEnqueueTuple Enqueue multiple Tensor values on the computation outfeed.
Pad <T> Pads a tensor.
ParallelBatchDataset
ParallelBatchDataset.Options Optional attributes for ParallelBatchDataset
ParallelConcat <T> Concatenates a list of `N` tensors along the first dimension.
ParallelDynamicStitch <T> Interleave the values from the `data` tensors into a single tensor.
ParseExampleDatasetV2 Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.
ParseExampleDatasetV2.Options Optional attributes for ParseExampleDatasetV2
ParseExampleV2 Transforms a vector of tf.Example protos (as strings) into typed tensors.
ParseSequenceExampleV2 Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors.
ParseSequenceExampleV2.Options Optional attributes for ParseSequenceExampleV2
Placeholder <T> A placeholder op for a value that will be fed into the computation.
Placeholder.Options Optional attributes for Placeholder
PlaceholderWithDefault <T> A placeholder op that passes through `input` when its output is not fed.
Prelinearize An op which linearizes one Tensor value to an opaque variant tensor.
Prelinearize.Options Optional attributes for Prelinearize
PrelinearizeTuple An op which linearizes multiple Tensor values to an opaque variant tensor.
PrelinearizeTuple.Options Optional attributes for PrelinearizeTuple
Print Prints a string scalar.
Print.Options Optional attributes for Print
PrivateThreadPoolDataset Creates a dataset that uses a custom thread pool to compute `input_dataset`.
Prod <T> Computes the product of elements across dimensions of a tensor.
Prod.Options Optional attributes for Prod
QuantizeAndDequantizeV4 <T extends Number> Returns the gradient of `QuantizeAndDequantizeV4`.
QuantizeAndDequantizeV4.Options Optional attributes for QuantizeAndDequantizeV4
QuantizeAndDequantizeV4Grad <T extends Number> Returns the gradient of `QuantizeAndDequantizeV4`.
QuantizeAndDequantizeV4Grad.Options Optional attributes for QuantizeAndDequantizeV4Grad
QuantizedConcat <T> Concatenates quantized tensors along one dimension.
QuantizedConcatV2 <T>
QuantizedConv2DAndRelu <V>
QuantizedConv2DAndRelu.Options Optional attributes for QuantizedConv2DAndRelu
QuantizedConv2DAndReluAndRequantize <V>
QuantizedConv2DAndReluAndRequantize.Options Optional attributes for QuantizedConv2DAndReluAndRequantize
QuantizedConv2DAndRequantize <V>
QuantizedConv2DAndRequantize.Options Optional attributes for QuantizedConv2DAndRequantize
QuantizedConv2DPerChannel <V> Computes QuantizedConv2D per channel.
QuantizedConv2DPerChannel.Options Optional attributes for QuantizedConv2DPerChannel
QuantizedConv2DWithBias <V>
QuantizedConv2DWithBias.Options Optional attributes for QuantizedConv2DWithBias
QuantizedConv2DWithBiasAndRelu <V>
QuantizedConv2DWithBiasAndRelu.Options Optional attributes for QuantizedConv2DWithBiasAndRelu
QuantizedConv2DWithBiasAndReluAndRequantize <W>
QuantizedConv2DWithBiasAndReluAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize
QuantizedConv2DWithBiasAndRequantize <W>
QuantizedConv2DWithBiasAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasAndRequantize
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X>
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
QuantizedConv2DWithBiasSumAndRelu <V>
QuantizedConv2DWithBiasSumAndRelu.Options Optional attributes for QuantizedConv2DWithBiasSumAndRelu
QuantizedConv2DWithBiasSumAndReluAndRequantize <X>
QuantizedConv2DWithBiasSumAndReluAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize
QuantizedDepthwiseConv2D <V> Computes quantized depthwise Conv2D.
QuantizedDepthwiseConv2D.Options Optional attributes for QuantizedDepthwiseConv2D
QuantizedDepthwiseConv2DWithBias <V> Computes quantized depthwise Conv2D with Bias.
QuantizedDepthwiseConv2DWithBias.Options Optional attributes for QuantizedDepthwiseConv2DWithBias
QuantizedDepthwiseConv2DWithBiasAndRelu <V> Computes quantized depthwise Conv2D with Bias and Relu.
QuantizedDepthwiseConv2DWithBiasAndRelu.Options Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W> Computes quantized depthwise Conv2D with Bias, Relu and Requantize.
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
QuantizedMatMulWithBias <W> Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add.
QuantizedMatMulWithBias.Options Optional attributes for QuantizedMatMulWithBias
QuantizedMatMulWithBiasAndDequantize <W extends Number>
QuantizedMatMulWithBiasAndDequantize.Options Optional attributes for QuantizedMatMulWithBiasAndDequantize
QuantizedMatMulWithBiasAndRelu <V> Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion.
QuantizedMatMulWithBiasAndRelu.Options Optional attributes for QuantizedMatMulWithBiasAndRelu
QuantizedMatMulWithBiasAndReluAndRequantize <W> Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion.
QuantizedMatMulWithBiasAndReluAndRequantize.Options Optional attributes for QuantizedMatMulWithBiasAndReluAndRequantize
QuantizedMatMulWithBiasAndRequantize <W>
QuantizedMatMulWithBiasAndRequantize.Options Optional attributes for QuantizedMatMulWithBiasAndRequantize
QuantizedReshape <T> Reshapes a quantized tensor as per the Reshape op.
RaggedBincount <U extends Number> Counts the number of occurrences of each value in an integer array.
RaggedBincount.Options Optional attributes for RaggedBincount
RaggedCountSparseOutput <U extends Number> Performs sparse-output bin counting for a ragged tensor input.
RaggedCountSparseOutput.Options Optional attributes for RaggedCountSparseOutput
RaggedCross <T, U extends Number> Generates a feature cross from a list of tensors, and returns it as a RaggedTensor.
RaggedGather <T extends Number, U> Gather ragged slices from `params` axis `0` according to `indices`.
RaggedRange <U extends Number, T extends Number> Returns a `RaggedTensor` containing the specified sequences of numbers.
RaggedTensorFromVariant <U extends Number, T> Decodes a `variant` Tensor into a `RaggedTensor`.
RaggedTensorToSparse <U> Converts a `RaggedTensor` into a `SparseTensor` with the same values.
RaggedTensorToTensor <U> Create a dense tensor from a ragged tensor, possibly altering its shape.
RaggedTensorToVariant Encodes a `RaggedTensor` into a `variant` Tensor.
RaggedTensorToVariantGradient <U> Helper used to compute the gradient for `RaggedTensorToVariant`.
Range <T extends Number> Creates a sequence of numbers.
Rank Returns the rank of a tensor.
ReadVariableOp <T> Reads the value of a variable.
RebatchDataset Creates a dataset that changes the batch size.
RebatchDataset.Options Optional attributes for RebatchDataset
RebatchDatasetV2 Creates a dataset that changes the batch size.
Recv <T> Receives the named tensor from send_device on recv_device.
Recv.Options Optional attributes for Recv
RecvTPUEmbeddingActivations An op that receives embedding activations on the TPU.
ReduceAll Computes the "logical and" of elements across dimensions of a tensor.
ReduceAll.Options Optional attributes for ReduceAll
ReduceAny Computes the "logical or" of elements across dimensions of a tensor.
ReduceAny.Options Optional attributes for ReduceAny
ReduceMax <T> Computes the maximum of elements across dimensions of a tensor.
ReduceMax.Options Optional attributes for ReduceMax
ReduceMin <T> Computes the minimum of elements across dimensions of a tensor.
ReduceMin.Options Optional attributes for ReduceMin
ReduceProd <T> Computes the product of elements across dimensions of a tensor.
ReduceProd.Options Optional attributes for ReduceProd
ReduceSum <T> Computes the sum of elements across dimensions of a tensor.
ReduceSum.Options Optional attributes for ReduceSum
RefEnter <T> Creates or finds a child frame, and makes `data` available to the child frame.
RefEnter.Options Optional attributes for RefEnter
RefExit <T> Exits the current frame to its parent frame.
RefIdentity <T> Return the same ref tensor as the input ref tensor.
RefMerge <T> Forwards the value of an available tensor from `inputs` to `output`.
RefNextIteration <T> Makes its input available to the next iteration.
RefSelect <T> Forwards the `index`th element of `inputs` to `output`.
RefSwitch <T> Forwards the ref tensor `data` to the output port determined by `pred`.
RegisterDataset Registers a dataset with the tf.data service.
RequantizationRangePerChannel Computes requantization range per channel.
RequantizePerChannel <U> Requantizes input with min and max values known per channel.
Reshape <T> Reshapes a tensor.
ResourceAccumulatorApplyGradient Applies a gradient to a given accumulator.
ResourceAccumulatorNumAccumulated Returns the number of gradients aggregated in the given accumulators.
ResourceAccumulatorSetGlobalStep Updates the accumulator with a new value for global_step.
ResourceAccumulatorTakeGradient <T> Extracts the average gradient in the given ConditionalAccumulator.
ResourceApplyAdagradV2 Update '*var' according to the adagrad scheme.
ResourceApplyAdagradV2.Options Optional attributes for ResourceApplyAdagradV2
ResourceApplyAdamWithAmsgrad Update '*var' according to the Adam algorithm.
ResourceApplyAdamWithAmsgrad.Options Optional attributes for ResourceApplyAdamWithAmsgrad
ResourceApplyKerasMomentum Update '*var' according to the momentum scheme.
ResourceApplyKerasMomentum.Options Optional attributes for ResourceApplyKerasMomentum
ResourceConditionalAccumulator A conditional accumulator for aggregating gradients.
ResourceConditionalAccumulator.Options Optional attributes for ResourceConditionalAccumulator
ResourceCountUpTo <T extends Number> Increments variable pointed to by 'resource' until it reaches 'limit'.
ResourceGather <U> Gather slices from the variable pointed to by `resource` according to `indices`.
ResourceGather.Options Optional attributes for ResourceGather
ResourceGatherNd <U>
ResourceScatterAdd Adds sparse updates to the variable referenced by `resource`.
ResourceScatterDiv Divides sparse updates into the variable referenced by `resource`.
ResourceScatterMax Reduces sparse updates into the variable referenced by `resource` using the `max` operation.
ResourceScatterMin Reduces sparse updates into the variable referenced by `resource` using the `min` operation.
ResourceScatterMul Multiplies sparse updates into the variable referenced by `resource`.
ResourceScatterNdAdd Applies sparse addition to individual values or slices in a Variable.
ResourceScatterNdAdd.Options Optional attributes for ResourceScatterNdAdd
ResourceScatterNdMax
ResourceScatterNdMax.Options Optional attributes for ResourceScatterNdMax
ResourceScatterNdMin
ResourceScatterNdMin.Options Optional attributes for ResourceScatterNdMin
ResourceScatterNdSub Applies sparse subtraction to individual values or slices in a Variable.
ResourceScatterNdSub.Options Optional attributes for ResourceScatterNdSub
ResourceScatterNdUpdate Applies sparse `updates` to individual values or slices within a given

variable according to `indices`.

ResourceScatterNdUpdate.Options Optional attributes for ResourceScatterNdUpdate
ResourceScatterSub Subtracts sparse updates from the variable referenced by `resource`.
ResourceScatterUpdate Assigns sparse updates to the variable referenced by `resource`.
ResourceSparseApplyAdagradV2 Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
ResourceSparseApplyAdagradV2.Options Optional attributes for ResourceSparseApplyAdagradV2
ResourceSparseApplyKerasMomentum Update relevant entries in '*var' and '*accum' according to the momentum scheme.
ResourceSparseApplyKerasMomentum.Options Optional attributes for ResourceSparseApplyKerasMomentum
ResourceStridedSliceAssign Assign `value` to the sliced l-value reference of `ref`.
ResourceStridedSliceAssign.Options Optional attributes for ResourceStridedSliceAssign
RetrieveTPUEmbeddingAdadeltaParameters Retrieve Adadelta embedding parameters.
RetrieveTPUEmbeddingAdadeltaParameters.Options Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug Retrieve Adadelta embedding parameters with debug support.
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug
RetrieveTPUEmbeddingAdagradParameters Retrieve Adagrad embedding parameters.
RetrieveTPUEmbeddingAdagradParameters.Options Optional attributes for RetrieveTPUEmbeddingAdagradParameters
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug Retrieve Adagrad embedding parameters with debug support.
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingAdagradParametersGradAccumDebug
RetrieveTPUEmbeddingADAMParameters Retrieve ADAM embedding parameters.
RetrieveTPUEmbeddingADAMParameters.Options Optional attributes for RetrieveTPUEmbeddingADAMParameters
RetrieveTPUEmbeddingADAMParametersGradAccumDebug Retrieve ADAM embedding parameters with debug support.
RetrieveTPUEmbeddingADAMParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingADAMParametersGradAccumDebug
RetrieveTPUEmbeddingCenteredRMSPropParameters Retrieve centered RMSProp embedding parameters.
RetrieveTPUEmbeddingCenteredRMSPropParameters.Options Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters
RetrieveTPUEmbeddingFrequencyEstimatorParameters Retrieve frequency estimator embedding parameters.
RetrieveTPUEmbeddingFrequencyEstimatorParameters.Options Optional attributes for RetrieveTPUEmbeddingFrequencyEstimatorParameters
RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug Retrieve frequency estimator embedding parameters with debug support.
RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
RetrieveTPUEmbeddingFTRLParameters Retrieve FTRL embedding parameters.
RetrieveTPUEmbeddingFTRLParameters.Options Optional attributes for RetrieveTPUEmbeddingFTRLParameters
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug Retrieve FTRL embedding parameters with debug support.
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingFTRLParametersGradAccumDebug
RetrieveTPUEmbeddingMDLAdagradLightParameters Retrieve MDL Adagrad Light embedding parameters.
RetrieveTPUEmbeddingMDLAdagradLightParameters.Options Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters
RetrieveTPUEmbeddingMomentumParameters Retrieve Momentum embedding parameters.
RetrieveTPUEmbeddingMomentumParameters.Options Optional attributes for RetrieveTPUEmbeddingMomentumParameters
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug Retrieve Momentum embedding parameters with debug support.
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingMomentumParametersGradAccumDebug
RetrieveTPUEmbeddingProximalAdagradParameters Retrieve proximal Adagrad embedding parameters.
RetrieveTPUEmbeddingProximalAdagradParameters.Options Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug Retrieve proximal Adagrad embedding parameters with debug support.
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug
RetrieveTPUEmbeddingProximalYogiParameters
RetrieveTPUEmbeddingProximalYogiParameters.Options Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug
RetrieveTPUEmbeddingRMSPropParameters Retrieve RMSProp embedding parameters.
RetrieveTPUEmbeddingRMSPropParameters.Options Optional attributes for RetrieveTPUEmbeddingRMSPropParameters
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug Retrieve RMSProp embedding parameters with debug support.
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug
RetrieveTPUEmbeddingStochasticGradientDescentParameters Retrieve SGD embedding parameters.
RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug Retrieve SGD embedding parameters with debug support.
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
Reverse <T> Reverses specific dimensions of a tensor.
ReverseSequence <T> Reverses variable length slices.
ReverseSequence.Options Optional attributes for ReverseSequence
RiscAbs <T extends Number>
RiscAdd <T extends Number> Returns x + y element-wise.
RiscBinaryArithmetic <T extends Number>
RiscBinaryComparison
RiscBitcast <U>
RiscBroadcast <T>
RiscCast <U>
RiscCeil <T extends Number>
RiscCholesky <T extends Number>
RiscConcat <T>
RiscConv <T extends Number>
RiscConv.Options Optional attributes for RiscConv
RiscCos <T extends Number>
RiscDiv <T extends Number>
RiscDot <T extends Number>
RiscDot.Options Optional attributes for RiscDot
RiscExp <T extends Number>
RiscFft <T>
RiscFloor <T extends Number>
RiscGather <T>
RiscGather.Options Optional attributes for RiscGather
RiscImag <U extends Number>
RiscIsFinite
RiscLog <T extends Number>
RiscLogicalAnd
RiscLogicalNot
RiscLogicalOr
RiscMax <T extends Number> Returns max(x, y) element-wise.
RiscMin <T extends Number>
RiscMul <T extends Number>
RiscNeg <T extends Number>
RiscPad <T extends Number>
RiscPool <T extends Number>
RiscPool.Options Optional attributes for RiscPool
RiscPow <T extends Number>
RiscRandomUniform
RiscRandomUniform.Options Optional attributes for RiscRandomUniform
RiscReal <U extends Number>
RiscReduce <T extends Number>
RiscRem <T extends Number>
RiscReshape <T extends Number>
RiscReverse <T extends Number>
RiscScatter <U extends Number>
RiscShape <U extends Number>
RiscSign <T extends Number>
RiscSlice <T extends Number>
RiscSort <T extends Number>
RiscSqueeze <T>
RiscSqueeze.Options Optional attributes for RiscSqueeze
RiscSub <T extends Number>
RiscTranspose <T>
RiscTriangularSolve <T extends Number>
RiscTriangularSolve.Options Optional attributes for RiscTriangularSolve
RiscUnary <T extends Number>
RngReadAndSkip Advance the counter of a counter-based RNG.
RngSkip Advance the counter of a counter-based RNG.
Roll <T> Rolls the elements of a tensor along an axis.
SamplingDataset Creates a dataset that takes a Bernoulli sample of the contents of another dataset.
ScaleAndTranslate
ScaleAndTranslate.Options Optional attributes for ScaleAndTranslate
ScaleAndTranslateGrad <T extends Number>
ScaleAndTranslateGrad.Options Optional attributes for ScaleAndTranslateGrad
ScatterAdd <T> Adds sparse updates to a variable reference.
ScatterAdd.Options Optional attributes for ScatterAdd
ScatterDiv <T> Divides a variable reference by sparse updates.
ScatterDiv.Options Optional attributes for ScatterDiv
ScatterMax <T extends Number> Reduces sparse updates into a variable reference using the `max` operation.
ScatterMax.Options Optional attributes for ScatterMax
ScatterMin <T extends Number> Reduces sparse updates into a variable reference using the `min` operation.
ScatterMin.Options Optional attributes for ScatterMin
ScatterMul <T> Multiplies sparse updates into a variable reference.
ScatterMul.Options Optional attributes for ScatterMul
ScatterNd <U> Scatter `updates` into a new tensor according to `indices`.
ScatterNdAdd <T> Applies sparse addition to individual values or slices in a Variable.
ScatterNdAdd.Options Optional attributes for ScatterNdAdd
ScatterNdMax <T> Computes element-wise maximum.
ScatterNdMax.Options Optional attributes for ScatterNdMax
ScatterNdMin <T> Computes element-wise minimum.
ScatterNdMin.Options Optional attributes for ScatterNdMin
ScatterNdNonAliasingAdd <T> Applies sparse addition to `input` using individual values or slices

from `updates` according to indices `indices`.

ScatterNdSub <T> Applies sparse subtraction to individual values or slices in a Variable.
ScatterNdSub.Options Optional attributes for ScatterNdSub
ScatterNdUpdate <T> Applies sparse `updates` to individual values or slices within a given

variable according to `indices`.

ScatterNdUpdate.Options Optional attributes for ScatterNdUpdate
ScatterSub <T> Subtracts sparse updates to a variable reference.
ScatterSub.Options Optional attributes for ScatterSub
ScatterUpdate <T> Applies sparse updates to a variable reference.
ScatterUpdate.Options Optional attributes for ScatterUpdate
SelectV2 <T>
Send Sends the named tensor from send_device to recv_device.
Send.Options Optional attributes for Send
SendTPUEmbeddingGradients Performs gradient updates of embedding tables.
SetDiff1d <T, U extends Number> Computes the difference between two lists of numbers or strings.
SetSize Number of unique elements along last dimension of input `set`.
SetSize.Options Optional attributes for SetSize
Shape <U extends Number> Returns the shape of a tensor.
ShapeN <U extends Number> Returns shape of tensors.
ShardDataset Creates a `Dataset` that includes only 1/`num_shards` of this dataset.
ShardDataset.Options Optional attributes for ShardDataset
ShuffleAndRepeatDatasetV2
ShuffleAndRepeatDatasetV2.Options Optional attributes for ShuffleAndRepeatDatasetV2
ShuffleDatasetV2
ShuffleDatasetV3
ShuffleDatasetV3.Options Optional attributes for ShuffleDatasetV3
ShutdownDistributedTPU Shuts down a running distributed TPU system.
Size <U extends Number> Returns the size of a tensor.
Skipgram Parses a text file and creates a batch of examples.
Skipgram.Options Optional attributes for Skipgram
SleepDataset
Slice <T> Return a slice from 'input'.
SlidingWindowDataset Creates a dataset that passes a sliding window over `input_dataset`.
Snapshot <T> Returns a copy of the input tensor.
SnapshotDataset Creates a dataset that will write to / read from a snapshot.
SnapshotDataset.Options Optional attributes for SnapshotDataset
SobolSample <T extends Number> Generates points from the Sobol sequence.
SpaceToBatchNd <T> SpaceToBatch for N-D tensors of type T.
SparseApplyAdagradV2 <T> Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
SparseApplyAdagradV2.Options Optional attributes for SparseApplyAdagradV2
SparseBincount <U extends Number> Counts the number of occurrences of each value in an integer array.
SparseBincount.Options Optional attributes for SparseBincount
SparseCountSparseOutput <U extends Number> Performs sparse-output bin counting for a sparse tensor input.
SparseCountSparseOutput.Options Optional attributes for SparseCountSparseOutput
SparseCrossHashed Generates sparse cross from a list of sparse and dense tensors.
SparseCrossV2 Generates sparse cross from a list of sparse and dense tensors.
SparseMatrixAdd Sparse addition of two CSR matrices, C = alpha * A + beta * B.
SparseMatrixMatMul <T> Matrix-multiplies a sparse matrix with a dense matrix.
SparseMatrixMatMul.Options Optional attributes for SparseMatrixMatMul
SparseMatrixMul Element-wise multiplication of a sparse matrix with a dense tensor.
SparseMatrixNNZ Returns the number of nonzeroes of `sparse_matrix`.
SparseMatrixOrderingAMD Computes the Approximate Minimum Degree (AMD) ordering of `input`.
SparseMatrixSoftmax Calculates the softmax of a CSRSparseMatrix.
SparseMatrixSoftmaxGrad Calculates the gradient of the SparseMatrixSoftmax op.
SparseMatrixSparseCholesky Computes the sparse Cholesky decomposition of `input`.
SparseMatrixSparseMatMul Sparse-matrix-multiplies two CSR matrices `a` and `b`.
SparseMatrixSparseMatMul.Options Optional attributes for SparseMatrixSparseMatMul
SparseMatrixTranspose Transposes the inner (matrix) dimensions of a CSRSparseMatrix.
SparseMatrixTranspose.Options Optional attributes for SparseMatrixTranspose
SparseMatrixZeros Creates an all-zeros CSRSparseMatrix with shape `dense_shape`.
SparseTensorToCSRSparseMatrix Converts a SparseTensor to a (possibly batched) CSRSparseMatrix.
Spence <T extends Number>
Split <T> Splits a tensor into `num_split` tensors along one dimension.
SplitV <T> Splits a tensor into `num_split` tensors along one dimension.
Squeeze <T> Removes dimensions of size 1 from the shape of a tensor.
Squeeze.Options Optional attributes for Squeeze
Stack <T> Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.
Stack.Options Optional attributes for Stack
Stage Stage values similar to a lightweight Enqueue.
Stage.Options Optional attributes for Stage
StageClear Op removes all elements in the underlying container.
StageClear.Options Optional attributes for StageClear
StagePeek Op peeks at the values at the specified index.
StagePeek.Options Optional attributes for StagePeek
StageSize Op returns the number of elements in the underlying container.
StageSize.Options Optional attributes for StageSize
StatefulRandomBinomial <V extends Number>
StatefulStandardNormal <U> Outputs random values from a normal distribution.
StatefulStandardNormalV2 <U> Outputs random values from a normal distribution.
StatefulTruncatedNormal <U> Outputs random values from a truncated normal distribution.
StatefulUniform <U> Outputs random values from a uniform distribution.
StatefulUniformFullInt <U> Outputs random integers from a uniform distribution.
StatefulUniformInt <U> Outputs random integers from a uniform distribution.
StatelessParameterizedTruncatedNormal <V extends Number>
StatelessRandomBinomial <W extends Number> Outputs deterministic pseudorandom random numbers from a binomial distribution.
StatelessRandomGammaV2 <V extends Number> Outputs deterministic pseudorandom random numbers from a gamma distribution.
StatelessRandomGetAlg Picks the best counter-based RNG algorithm based on device.
StatelessRandomGetKeyCounter Scrambles seed into key and counter, using the best algorithm based on device.
StatelessRandomGetKeyCounterAlg Picks the best algorithm based on device, and scrambles seed into key and counter.
StatelessRandomNormalV2 <U extends Number> Outputs deterministic pseudorandom values from a normal distribution.
StatelessRandomPoisson <W extends Number> Outputs deterministic pseudorandom random numbers from a Poisson distribution.
StatelessRandomUniformFullInt <V extends Number> Outputs deterministic pseudorandom random integers from a uniform distribution.
StatelessRandomUniformFullIntV2 <U extends Number> Outputs deterministic pseudorandom random integers from a uniform distribution.
StatelessRandomUniformIntV2 <U extends Number> Outputs deterministic pseudorandom random integers from a uniform distribution.
StatelessRandomUniformV2 <U extends Number> Outputs deterministic pseudorandom random values from a uniform distribution.
StatelessSampleDistortedBoundingBox <T extends Number> Generate a randomly distorted bounding box for an image deterministically.
StatelessSampleDistortedBoundingBox.Options Optional attributes for StatelessSampleDistortedBoundingBox
StatelessTruncatedNormalV2 <U extends Number> Outputs deterministic pseudorandom values from a truncated normal distribution.
StatsAggregatorHandleV2
StatsAggregatorHandleV2.Options Optional attributes for StatsAggregatorHandleV2
StatsAggregatorSetSummaryWriter Set a summary_writer_interface to record statistics using given stats_aggregator.
StopGradient <T> Stops gradient computation.
StridedSlice <T> Return a strided slice from `input`.
StridedSlice.Options Optional attributes for StridedSlice
StridedSliceAssign <T> Assign `value` to the sliced l-value reference of `ref`.
StridedSliceAssign.Options Optional attributes for StridedSliceAssign
StridedSliceGrad <U> Returns the gradient of `StridedSlice`.
StridedSliceGrad.Options Optional attributes for StridedSliceGrad
StringLower Converts all uppercase characters into their respective lowercase replacements.
StringLower.Options Optional attributes for StringLower
StringNGrams <T extends Number> Creates ngrams from ragged string data.
StringUpper Converts all lowercase characters into their respective uppercase replacements.
StringUpper.Options Optional attributes for StringUpper
Sum <T> Computes the sum of elements across dimensions of a tensor.
Sum.Options Optional attributes for Sum
SwitchCond <T> Forwards `data` to the output port determined by `pred`.
TemporaryVariable <T> Returns a tensor that may be mutated, but only persists within a single step.
TemporaryVariable.Options Optional attributes for TemporaryVariable
TensorArray An array of Tensors of given size.
TensorArray.Options Optional attributes for TensorArray
TensorArrayClose Delete the TensorArray from its resource container.
TensorArrayConcat <T> Concat the elements from the TensorArray into value `value`.
TensorArrayConcat.Options Optional attributes for TensorArrayConcat
TensorArrayGather <T> Gather specific elements from the TensorArray into output `value`.
TensorArrayGather.Options Optional attributes for TensorArrayGather
TensorArrayGrad Creates a TensorArray for storing the gradients of values in the given handle.
TensorArrayGradWithShape Creates a TensorArray for storing multiple gradients of values in the given handle.
TensorArrayPack <T>
TensorArrayPack.Options Optional attributes for TensorArrayPack
TensorArrayRead <T> Read an element from the TensorArray into output `value`.
TensorArrayScatter Scatter the data from the input value into specific TensorArray elements.
TensorArraySize Get the current size of the TensorArray.
TensorArraySplit Split the data from the input value into TensorArray elements.
TensorArrayUnpack
TensorArrayWrite Push an element onto the tensor_array.
TensorListConcat <T> Concats all tensors in the list along the 0th dimension.
TensorListConcat.Options Optional attributes for TensorListConcat
TensorListConcatLists
TensorListConcatV2 <U> Concats all tensors in the list along the 0th dimension.
TensorListElementShape <T extends Number> The shape of the elements of the given list, as a tensor.
TensorListFromTensor Creates a TensorList which, when stacked, has the value of `tensor`.
TensorListGather <T> Creates a Tensor by indexing into the TensorList.
TensorListGetItem <T>
TensorListLength Returns the number of tensors in the input tensor list.
TensorListPopBack <T> Returns the last element of the input list as well as a list with all but that element.
TensorListPushBack Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`.
TensorListPushBackBatch
TensorListReserve List of the given size with empty elements.
TensorListResize Resizes the list.
TensorListScatter Creates a TensorList by indexing into a Tensor.
TensorListScatterIntoExistingList Scatters tensor at indices in an input list.
TensorListScatterV2 Creates a TensorList by indexing into a Tensor.
TensorListSetItem
TensorListSplit Splits a tensor into a list.
TensorListStack <T> Stacks all tensors in the list.
TensorListStack.Options Optional attributes for TensorListStack
TensorMapErase Returns a tensor map with item from given key erased.
TensorMapHasKey Returns whether the given key exists in the map.
TensorMapInsert Returns a map that is the 'input_handle' with the given key-value pair inserted.
TensorMapLookup <U> Returns the value from a given key in a tensor map.
TensorMapSize Returns the number of tensors in the input tensor map.
TensorMapStackKeys <T> Returns a Tensor stack of all keys in a tensor map.
TensorScatterAdd <T> Adds sparse `updates` to an existing tensor according to `indices`.
TensorScatterMax <T>
TensorScatterMin <T>
TensorScatterSub <T> Subtracts sparse `updates` from an existing tensor according to `indices`.
TensorScatterUpdate <T> Scatter `updates` into an existing tensor according to `indices`.
TensorStridedSliceUpdate <T> Assign `value` to the sliced l-value reference of `input`.
TensorStridedSliceUpdate.Options Optional attributes for TensorStridedSliceUpdate
ThreadPoolDataset Creates a dataset that uses a custom thread pool to compute `input_dataset`.
ThreadPoolHandle Creates a dataset that uses a custom thread pool to compute `input_dataset`.
ThreadPoolHandle.Options Optional attributes for ThreadPoolHandle
Tile <T> Constructs a tensor by tiling a given tensor.
Timestamp Provides the time since epoch in seconds.
ToBool Converts a tensor to a scalar predicate.
TopKUnique Returns the TopK unique values in the array in sorted order.
TopKWithUnique Returns the TopK values in the array in sorted order.
TPUCompilationResult Returns the result of a TPU compilation.
TPUCompileSucceededAssert Asserts that compilation succeeded.
TPUEmbeddingActivations An op enabling differentiation of TPU Embeddings.
TPUExecute Op that loads and executes a TPU program on a TPU device.
TPUExecuteAndUpdateVariables Op that executes a program with optional in-place variable updates.
TPUOrdinalSelector A TPU core selector Op.
TPUPartitionedInput <T> An op that groups a list of partitioned inputs together.
TPUPartitionedInput.Options Optional attributes for TPUPartitionedInput
TPUPartitionedOutput <T> An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned

outputs outside the XLA computation.

TPUPartitionedOutput.Options Optional attributes for TPUPartitionedOutput
TPUReplicatedInput <T> Connects N inputs to an N-way replicated TPU computation.
TPUReplicatedInput.Options Optional attributes for TPUReplicatedInput
TPUReplicatedOutput <T> Connects N outputs from an N-way replicated TPU computation.
TPUReplicateMetadata Metadata indicating how the TPU computation should be replicated.
TPUReplicateMetadata.Options Optional attributes for TPUReplicateMetadata
TPUReshardVariables Op that reshards on-device TPU variables to specified state.
TridiagonalMatMul <T> Calculate product with tridiagonal matrix.
TridiagonalSolve <T> Solves tridiagonal systems of equations.
TridiagonalSolve.Options Optional attributes for TridiagonalSolve
Unbatch <T> Reverses the operation of Batch for a single output Tensor.
Unbatch.Options Optional attributes for Unbatch
UnbatchGrad <T> Gradient of Unbatch.
UnbatchGrad.Options Optional attributes for UnbatchGrad
UncompressElement Uncompresses a compressed dataset element.
UnicodeDecode <T extends Number> Decodes each string in `input` into a sequence of Unicode code points.
UnicodeDecode.Options Optional attributes for UnicodeDecode
UnicodeEncode Encode a tensor of ints into unicode strings.
UnicodeEncode.Options Optional attributes for UnicodeEncode
Unique <T, V extends Number> Finds unique elements along an axis of a tensor.
UniqueDataset Creates a dataset that contains the unique elements of `input_dataset`.
UniqueWithCounts <T, V extends Number> Finds unique elements along an axis of a tensor.
UnravelIndex <T extends Number> Converts an array of flat indices into a tuple of coordinate arrays.
UnsortedSegmentJoin Joins the elements of `inputs` based on `segment_ids`.
UnsortedSegmentJoin.Options Optional attributes for UnsortedSegmentJoin
Unstack <T> Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors.
Unstack.Options Optional attributes for Unstack
Unstage Op is similar to a lightweight Dequeue.
Unstage.Options Optional attributes for Unstage
UnwrapDatasetVariant
UpperBound <U extends Number> Applies upper_bound(sorted_search_values, values) along each row.
VarHandleOp Creates a handle to a Variable resource.
VarHandleOp.Options Optional attributes for VarHandleOp
Variable <T> Holds state in the form of a tensor that persists across steps.
Variable.Options Optional attributes for Variable
VariableShape <T extends Number> Returns the shape of the variable pointed to by `resource`.
VarIsInitializedOp Checks whether a resource handle-based variable has been initialized.
Where Returns locations of nonzero / true values in a tensor.
Where3 <T> Selects elements from `x` or `y`, depending on `condition`.
WorkerHeartbeat Worker heartbeat op.
WrapDatasetVariant
WriteRawProtoSummary Writes a serialized proto summary.
XlaRecvFromHost <T> An op to receive a tensor from the host.
XlaSendToHost An op to send a tensor to the host.
Xlog1py <T> Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise.
Zeros <T> An operator creating a constant initialized with zeros of the shape given by `dims`.
ZerosLike <T> Returns a tensor of zeros with the same shape and type as x.