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. 
CollectiveGather<T extends Number> Mutually accumulates multiple tensors of identical type and shape. 
CollectiveGather.Options Optional attributes for CollectiveGather  
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  
DataServiceDataset.Options Optional attributes for DataServiceDataset  
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. 
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  
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 ys w.r.t xs, 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  
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  
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  
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  
OutfeedEnqueue Enqueue a Tensor on the computation outfeed. 
OutfeedEnqueueTuple Enqueue multiple Tensor values on the computation outfeed. 
Pad<T> Pads a tensor. 
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  
QuantizedConcat<T> Concatenates quantized tensors along one dimension. 
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. 
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. 
RemoteFusedGraphExecute Execute a sub graph on a remote processor. 
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  
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  
RngSkip Advance the counter of a counter-based RNG. 
Roll<T> Rolls the elements of a tensor along an axis. 
Rpc Perform batches of RPC requests. 
Rpc.Options Optional attributes for Rpc  
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. 
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. 
StatelessSampleDistortedBoundingBox<T extends Number> Generate a randomly distorted bounding box for an image deterministically. 
StatelessSampleDistortedBoundingBox.Options Optional attributes for StatelessSampleDistortedBoundingBox  
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. 
TensorForestCreateTreeVariable Creates a tree resource and returns a handle to it. 
TensorForestTreeDeserialize Deserializes a proto into the tree handle  
TensorForestTreeIsInitializedOp Checks whether a tree has been initialized. 
TensorForestTreePredict Output the logits for the given input data  
TensorForestTreeResourceHandleOp Creates a handle to a TensorForestTreeResource  
TensorForestTreeResourceHandleOp.Options Optional attributes for TensorForestTreeResourceHandleOp  
TensorForestTreeSerialize Serializes the tree handle to a proto  
TensorForestTreeSize Get the number of nodes in a tree  
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. 
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  
TridiagonalMatMul<T> Calculate product with tridiagonal matrix. 
TridiagonalSolve<T> Solves tridiagonal systems of equations. 
TridiagonalSolve.Options Optional attributes for TridiagonalSolve  
TryRpc Perform batches of RPC requests. 
TryRpc.Options Optional attributes for TryRpc  
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.