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.
AnonymousHashTable	Creates a uninitialized anonymous hash table.
AnonymousIteratorV2	A container for an iterator resource.
AnonymousIteratorV3	A container for an iterator resource.
AnonymousMemoryCache
AnonymousMultiDeviceIterator	A container for a multi device iterator resource.
AnonymousMultiDeviceIteratorV3	A container for a multi device iterator resource.
AnonymousMutableDenseHashTable	Creates an empty anonymous mutable hash table that uses tensors as the backing store.
AnonymousMutableDenseHashTable.Options	Optional attributes for AnonymousMutableDenseHashTable
AnonymousMutableHashTable	Creates an empty anonymous mutable hash table.
AnonymousMutableHashTableOfTensors	Creates an empty anonymous mutable hash table of vector values.
AnonymousMutableHashTableOfTensors.Options	Optional attributes for AnonymousMutableHashTableOfTensors
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
ApproxTopK<T extends Number>	Returns min/max k values and their indices of the input operand in an approximate manner.
ApproxTopK.Options	Optional attributes for ApproxTopK
AssertCardinalityDataset
AssertNextDataset	A transformation that asserts which transformations happen next.
AssertPrevDataset	A transformation that asserts which transformations happened previously.
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.
AssignVariableOp.Options	Optional attributes for AssignVariableOp
AssignVariableXlaConcatND	Concats input tensor across all dimensions.
AssignVariableXlaConcatND.Options	Optional attributes for AssignVariableXlaConcatND
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
BatchMatMulV3<V>	Multiplies slices of two tensors in batches.
BatchMatMulV3.Options	Optional attributes for BatchMatMulV3
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
CacheDatasetV2.Options	Optional attributes for 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.
CollateTPUEmbeddingMemory	An op that merges the string-encoded memory config protos from all hosts.
CollectiveAllToAllV2<T extends Number>	Mutually exchanges multiple tensors of identical type and shape.
CollectiveAllToAllV2.Options	Optional attributes for CollectiveAllToAllV2
CollectiveAllToAllV3<T extends Number>	Mutually exchanges multiple tensors of identical type and shape.
CollectiveAllToAllV3.Options	Optional attributes for CollectiveAllToAllV3
CollectiveAssignGroupV2	Assign group keys based on group assignment.
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
CollectiveInitializeCommunicator	Initializes a group for collective operations.
CollectiveInitializeCommunicator.Options	Optional attributes for CollectiveInitializeCommunicator
CollectivePermute<T>	An Op to permute tensors across replicated TPU instances.
CollectiveReduceScatterV2<T extends Number>	Mutually reduces multiple tensors of identical type and shape and scatters the result.
CollectiveReduceScatterV2.Options	Optional attributes for CollectiveReduceScatterV2
CollectiveReduceV2<T extends Number>	Mutually reduces multiple tensors of identical type and shape.
CollectiveReduceV2.Options	Optional attributes for CollectiveReduceV2
CollectiveReduceV3<T extends Number>	Mutually reduces multiple tensors of identical type and shape.
CollectiveReduceV3.Options	Optional attributes for CollectiveReduceV3
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
CompositeTensorVariantFromComponents	Encodes an `ExtensionType` value into a `variant` scalar Tensor.
CompositeTensorVariantToComponents	Decodes a `variant` scalar Tensor into an `ExtensionType` value.
CompressElement	Compresses a dataset element.
ComputeBatchSize	Computes the static batch size of a dataset sans partial batches.
ComputeDedupDataSize	An op computes the size of the deduplication data from embedding core and returns the updated config.
ComputeDedupDataTupleMask	An op computes tuple mask of deduplication data from embedding core.
Concat<T>	Concatenates tensors along one dimension.
ConfigureAndInitializeGlobalTPU	An op that sets up the centralized structures for a distributed TPU system.
ConfigureAndInitializeGlobalTPU.Options	Optional attributes for ConfigureAndInitializeGlobalTPU
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.
ConfigureTPUEmbeddingHost	An op that configures the TPUEmbedding software on a host.
ConfigureTPUEmbeddingMemory	An op that configures the TPUEmbedding software on a host.
ConnectTPUEmbeddingHosts	An op that sets up communication between TPUEmbedding host software instances after ConfigureTPUEmbeddingHost has been called on each host.
Constant<T>	An operator producing a constant value.
ConsumeMutexLock	This op consumes a lock created by `MutexLock`.
ControlTrigger	Does nothing.
Conv<T extends Number>	Computes a N-D convolution given (N+1+batch_dims)-D `input` and (N+2)-D `filter` tensors.
Conv.Options	Optional attributes for Conv
Conv2DBackpropFilterV2<T extends Number>	Computes the gradients of convolution with respect to the filter.
Conv2DBackpropFilterV2.Options	Optional attributes for Conv2DBackpropFilterV2
Conv2DBackpropInputV2<T extends Number>	Computes the gradients of convolution with respect to the input.
Conv2DBackpropInputV2.Options	Optional attributes for Conv2DBackpropInputV2
ConvertToCooTensor
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
CopyToMesh<T>
CopyToMeshGrad<T>
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`.
DatasetCardinality.Options	Optional attributes for DatasetCardinality
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
DebugIdentityV3<T>	Provides an identity mapping of the non-Ref type input tensor for debugging.
DebugIdentityV3.Options	Optional attributes for DebugIdentityV3
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.
DirectedInterleaveDataset.Options	Optional attributes for DirectedInterleaveDataset
DisableCopyOnRead	Turns off the copy-on-read mode.
DistributedSave
DistributedSave.Options	Optional attributes for DistributedSave
DrawBoundingBoxesV2<T extends Number>	Draw bounding boxes on a batch of images.
DTensorRestoreV2
DTensorSetGlobalTPUArray	An op that informs a host of the global ids of all the of TPUs in the system.
DummyIterationCounter
DummyMemoryCache
DummySeedGenerator
DynamicEnqueueTPUEmbeddingArbitraryTensorBatch	Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
DynamicEnqueueTPUEmbeddingArbitraryTensorBatch.Options	Optional attributes for DynamicEnqueueTPUEmbeddingArbitraryTensorBatch
DynamicEnqueueTPUEmbeddingRaggedTensorBatch
DynamicEnqueueTPUEmbeddingRaggedTensorBatch.Options	Optional attributes for DynamicEnqueueTPUEmbeddingRaggedTensorBatch
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
EnqueueTPUEmbeddingArbitraryTensorBatch	Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
EnqueueTPUEmbeddingArbitraryTensorBatch.Options	Optional attributes for EnqueueTPUEmbeddingArbitraryTensorBatch
EnqueueTPUEmbeddingBatch	An op that enqueues a list of input batch tensors to TPUEmbedding.
EnqueueTPUEmbeddingBatch.Options	Optional attributes for EnqueueTPUEmbeddingBatch
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
ExecuteTPUEmbeddingPartitioner	An op that executes the TPUEmbedding partitioner on the central configuration device and computes the HBM size (in bytes) required for TPUEmbedding operation.
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.
FFTND<T>	ND fast Fourier transform.
FileSystemSetConfiguration	Set configuration of the file system.
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
FinalizeTPUEmbedding	An op that finalizes the TPUEmbedding configuration.
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
GetElementAtIndex	Gets the element at the specified index in a dataset.
GetMinibatchesInCsrWithPhysicalReplica
GetMinibatchSplitsWithPhysicalReplica
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.
GlobalIterId
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.
IFFTND<T>	ND inverse fast Fourier transform.
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'.
IRFFTND<U extends Number>	ND inverse real fast Fourier transform.
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.
IsTPUEmbeddingInitialized	Whether TPU Embedding is initialized in a distributed TPU system.
IsTPUEmbeddingInitialized.Options	Optional attributes for IsTPUEmbeddingInitialized
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.
ListDataset	Creates a dataset that emits each of `tensors` once.
ListDataset.Options	Optional attributes for ListDataset
ListSnapshotChunksDataset
LMDBDataset	Creates a dataset that emits the key-value pairs in one or more LMDB files.
LoadAllTPUEmbeddingParameters	An op that loads optimization parameters into embedding memory.
LoadTPUEmbeddingAdadeltaParameters	Load Adadelta embedding parameters.
LoadTPUEmbeddingAdadeltaParameters.Options	Optional attributes for LoadTPUEmbeddingAdadeltaParameters
LoadTPUEmbeddingAdagradMomentumParameters	Load Adagrad Momentum embedding parameters.
LoadTPUEmbeddingAdagradMomentumParameters.Options	Optional attributes for LoadTPUEmbeddingAdagradMomentumParameters
LoadTPUEmbeddingAdagradParameters	Load Adagrad embedding parameters.
LoadTPUEmbeddingAdagradParameters.Options	Optional attributes for LoadTPUEmbeddingAdagradParameters
LoadTPUEmbeddingADAMParameters	Load ADAM embedding parameters.
LoadTPUEmbeddingADAMParameters.Options	Optional attributes for LoadTPUEmbeddingADAMParameters
LoadTPUEmbeddingCenteredRMSPropParameters	Load centered RMSProp embedding parameters.
LoadTPUEmbeddingCenteredRMSPropParameters.Options	Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters
LoadTPUEmbeddingFrequencyEstimatorParameters	Load frequency estimator embedding parameters.
LoadTPUEmbeddingFrequencyEstimatorParameters.Options	Optional attributes for LoadTPUEmbeddingFrequencyEstimatorParameters
LoadTPUEmbeddingFTRLParameters	Load FTRL embedding parameters.
LoadTPUEmbeddingFTRLParameters.Options	Optional attributes for LoadTPUEmbeddingFTRLParameters
LoadTPUEmbeddingMDLAdagradLightParameters	Load MDL Adagrad Light embedding parameters.
LoadTPUEmbeddingMDLAdagradLightParameters.Options	Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters
LoadTPUEmbeddingMomentumParameters	Load Momentum embedding parameters.
LoadTPUEmbeddingMomentumParameters.Options	Optional attributes for LoadTPUEmbeddingMomentumParameters
LoadTPUEmbeddingProximalAdagradParameters	Load proximal Adagrad embedding parameters.
LoadTPUEmbeddingProximalAdagradParameters.Options	Optional attributes for LoadTPUEmbeddingProximalAdagradParameters
LoadTPUEmbeddingProximalYogiParameters
LoadTPUEmbeddingProximalYogiParameters.Options	Optional attributes for LoadTPUEmbeddingProximalYogiParameters
LoadTPUEmbeddingRMSPropParameters	Load RMSProp embedding parameters.
LoadTPUEmbeddingRMSPropParameters.Options	Optional attributes for LoadTPUEmbeddingRMSPropParameters
LoadTPUEmbeddingStochasticGradientDescentParameters	Load SGD embedding parameters.
LoadTPUEmbeddingStochasticGradientDescentParameters.Options	Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters
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`.
MergeDedupData	An op merges elements of integer and float tensors into deduplication data as XLA tuple.
MergeDedupData.Options	Optional attributes for MergeDedupData
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`.
OptionsDataset.Options	Optional attributes for OptionsDataset
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>	Quantizes then dequantizes a tensor.
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.
RaggedFillEmptyRows<T>
RaggedFillEmptyRowsGrad<T>
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`.
RandomDatasetV2	Creates a Dataset that returns pseudorandom numbers.
RandomDatasetV2.Options	Optional attributes for RandomDatasetV2
RandomIndexShuffle<T extends Number>	Outputs the position of `value` in a permutation of [0, ..., max_index].
RandomIndexShuffle.Options	Optional attributes for RandomIndexShuffle
Range<T extends Number>	Creates a sequence of numbers.
Rank	Returns the rank of a tensor.
ReadVariableOp<T>	Reads the value of a variable.
ReadVariableXlaSplitND<T>	Splits resource variable input tensor across all dimensions.
ReadVariableXlaSplitND.Options	Optional attributes for ReadVariableXlaSplitND
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.
RegisterDataset.Options	Optional attributes for RegisterDataset
RegisterDatasetV2	Registers a dataset with the tf.data service.
RegisterDatasetV2.Options	Optional attributes for RegisterDatasetV2
Relayout<T>
RelayoutLike<T>
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
RetrieveAllTPUEmbeddingParameters	An op that retrieves optimization parameters from embedding to host memory.
RetrieveTPUEmbeddingAdadeltaParameters	Retrieve Adadelta embedding parameters.
RetrieveTPUEmbeddingAdadeltaParameters.Options	Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters
RetrieveTPUEmbeddingAdagradMomentumParameters	Retrieve Adagrad Momentum embedding parameters.
RetrieveTPUEmbeddingAdagradMomentumParameters.Options	Optional attributes for RetrieveTPUEmbeddingAdagradMomentumParameters
RetrieveTPUEmbeddingAdagradParameters	Retrieve Adagrad embedding parameters.
RetrieveTPUEmbeddingAdagradParameters.Options	Optional attributes for RetrieveTPUEmbeddingAdagradParameters
RetrieveTPUEmbeddingADAMParameters	Retrieve ADAM embedding parameters.
RetrieveTPUEmbeddingADAMParameters.Options	Optional attributes for RetrieveTPUEmbeddingADAMParameters
RetrieveTPUEmbeddingCenteredRMSPropParameters	Retrieve centered RMSProp embedding parameters.
RetrieveTPUEmbeddingCenteredRMSPropParameters.Options	Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters
RetrieveTPUEmbeddingFrequencyEstimatorParameters	Retrieve frequency estimator embedding parameters.
RetrieveTPUEmbeddingFrequencyEstimatorParameters.Options	Optional attributes for RetrieveTPUEmbeddingFrequencyEstimatorParameters
RetrieveTPUEmbeddingFTRLParameters	Retrieve FTRL embedding parameters.
RetrieveTPUEmbeddingFTRLParameters.Options	Optional attributes for RetrieveTPUEmbeddingFTRLParameters
RetrieveTPUEmbeddingMDLAdagradLightParameters	Retrieve MDL Adagrad Light embedding parameters.
RetrieveTPUEmbeddingMDLAdagradLightParameters.Options	Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters
RetrieveTPUEmbeddingMomentumParameters	Retrieve Momentum embedding parameters.
RetrieveTPUEmbeddingMomentumParameters.Options	Optional attributes for RetrieveTPUEmbeddingMomentumParameters
RetrieveTPUEmbeddingProximalAdagradParameters	Retrieve proximal Adagrad embedding parameters.
RetrieveTPUEmbeddingProximalAdagradParameters.Options	Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters
RetrieveTPUEmbeddingProximalYogiParameters
RetrieveTPUEmbeddingProximalYogiParameters.Options	Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters
RetrieveTPUEmbeddingRMSPropParameters	Retrieve RMSProp embedding parameters.
RetrieveTPUEmbeddingRMSPropParameters.Options	Optional attributes for RetrieveTPUEmbeddingRMSPropParameters
RetrieveTPUEmbeddingStochasticGradientDescentParameters	Retrieve SGD embedding parameters.
RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options	Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters
Reverse<T>	Reverses specific dimensions of a tensor.
ReverseSequence<T>	Reverses variable length slices.
ReverseSequence.Options	Optional attributes for ReverseSequence
RewriteDataset
RFFTND<U>	ND fast real Fourier transform.
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>	Scatters `updates` into a tensor of shape `shape` 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
SegmentMaxV2<T extends Number>	Computes the maximum along segments of a tensor.
SegmentMinV2<T extends Number>	Computes the minimum along segments of a tensor.
SegmentProdV2<T>	Computes the product along segments of a tensor.
SegmentSumV2<T>	Computes the sum along segments of a tensor.
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
ShuffleDatasetV2.Options	Optional attributes for ShuffleDatasetV2
ShuffleDatasetV3
ShuffleDatasetV3.Options	Optional attributes for ShuffleDatasetV3
ShutdownDistributedTPU	Shuts down a running distributed TPU system.
ShutdownTPUSystem	An op that shuts down the 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`.
SlidingWindowDataset.Options	Optional attributes for SlidingWindowDataset
Snapshot<T>	Returns a copy of the input tensor.
SnapshotChunkDataset
SnapshotChunkDataset.Options	Optional attributes for SnapshotChunkDataset
SnapshotDataset	Creates a dataset that will write to / read from a snapshot.
SnapshotDataset.Options	Optional attributes for SnapshotDataset
SnapshotDatasetReader
SnapshotDatasetReader.Options	Optional attributes for SnapshotDatasetReader
SnapshotNestedDatasetReader
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`.
SparseSegmentMeanGradV2<T extends Number, U extends Number>	Computes gradients for SparseSegmentMean.
SparseSegmentSqrtNGradV2<T extends Number, U extends Number>	Computes gradients for SparseSegmentSqrtN.
SparseSegmentSumGrad<T extends Number>	Computes gradients for SparseSegmentSum.
SparseSegmentSumGradV2<T extends Number, U extends Number>	Computes gradients for SparseSegmentSum.
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.
SplitDedupData<T extends Number, U extends Number>	An op splits input deduplication data XLA tuple into integer and floating point tensors.
SplitDedupData.Options	Optional attributes for SplitDedupData
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.
StatelessRandomGammaV3<U 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
StatelessShuffle<T>	Randomly and deterministically shuffles a tensor along its first dimension.
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.
StochasticCastToInt<U extends Number>	Stochastically cast a given tensor from floats to ints.
StopGradient<T>	Stops gradient computation.
StoreMinibatchStatisticsInFdo
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`.
SyncDevice	Synchronizes the device this op is run on.
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
TensorListSetItem.Options	Optional attributes for 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>	Apply a sparse update to a tensor taking the element-wise maximum.
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
TFRecordDatasetV2	Creates a dataset that emits the records from one or more TFRecord files.
TFRecordDatasetV2.Options	Optional attributes for TFRecordDatasetV2
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.
TPUAnnotateTensorsWithDynamicShape
TPUCompilationResult	Returns the result of a TPU compilation.
TPUCompileSucceededAssert	Asserts that compilation succeeded.
TPUCopyWithDynamicShape	Op that copies host tensor to device with dynamic shape support.
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.
TpuHandleToProtoKey	Converts XRT's uid handles to TensorFlow-friendly input format.
TPUOrdinalSelector	A TPU core selector Op.
TPUPartitionedInput<T>	An op that groups a list of partitioned inputs together.
TPUPartitionedInput.Options	Optional attributes for TPUPartitionedInput
TPUPartitionedInputV2<T>	An op that groups a list of partitioned inputs together.
TPUPartitionedInputV2.Options	Optional attributes for TPUPartitionedInputV2
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
TPUPartitionedOutputV2<T>	An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation.
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.
TPURoundRobin	Round-robin load balancing on TPU cores.
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
UniformDequantize<U extends Number>	Perform dequantization on the quantized Tensor `input`.
UniformDequantize.Options	Optional attributes for UniformDequantize
UniformQuantize<U>	Perform quantization on Tensor `input`.
UniformQuantize.Options	Optional attributes for UniformQuantize
UniformQuantizedAdd<T>	Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.
UniformQuantizedAdd.Options	Optional attributes for UniformQuantizedAdd
UniformQuantizedClipByValue<T>	Perform clip by value on the quantized Tensor `operand`.
UniformQuantizedClipByValue.Options	Optional attributes for UniformQuantizedClipByValue
UniformQuantizedConvolution<U>	Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`.
UniformQuantizedConvolution.Options	Optional attributes for UniformQuantizedConvolution
UniformQuantizedConvolutionHybrid<V extends Number>	Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`.
UniformQuantizedConvolutionHybrid.Options	Optional attributes for UniformQuantizedConvolutionHybrid
UniformQuantizedDot<U>	Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.
UniformQuantizedDot.Options	Optional attributes for UniformQuantizedDot
UniformQuantizedDotHybrid<V extends Number>	Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`.
UniformQuantizedDotHybrid.Options	Optional attributes for UniformQuantizedDotHybrid
UniformRequantize<U>	Given quantized tensor `input`, requantize it with new quantization parameters.
UniformRequantize.Options	Optional attributes for UniformRequantize
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`.
UniqueDataset.Options	Optional attributes for UniqueDataset
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
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`.
WindowOp
WorkerHeartbeat	Worker heartbeat op.
WrapDatasetVariant
WriteRawProtoSummary	Writes a serialized proto summary.
XlaConcatND<T>	Concats input tensor across all dimensions.
XlaConcatND.Options	Optional attributes for XlaConcatND
XlaRecvFromHost<T>	An op to receive a tensor from the host.
XlaRecvTPUEmbeddingActivations	An op that receives embedding activations on the TPU.
XlaRecvTPUEmbeddingDeduplicationData	Receives deduplication data (indices and weights) from the embedding core.
XlaSendToHost	An op to send a tensor to the host.
XlaSendTPUEmbeddingGradients	An op that performs gradient updates of embedding tables.
XlaSparseCoreAdagrad
XlaSparseCoreAdagradMomentum
XlaSparseCoreAdam
XlaSparseCoreFtrl
XlaSparseCoreSgd
XlaSparseDenseMatmul
XlaSparseDenseMatmulGradWithAdagradAndCsrInput
XlaSparseDenseMatmulGradWithAdagradAndCsrInput.Options	Optional attributes for XlaSparseDenseMatmulGradWithAdagradAndCsrInput
XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput
XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput.Options	Optional attributes for XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput
XlaSparseDenseMatmulGradWithAdamAndCsrInput
XlaSparseDenseMatmulGradWithAdamAndCsrInput.Options	Optional attributes for XlaSparseDenseMatmulGradWithAdamAndCsrInput
XlaSparseDenseMatmulGradWithFtrlAndCsrInput
XlaSparseDenseMatmulGradWithFtrlAndCsrInput.Options	Optional attributes for XlaSparseDenseMatmulGradWithFtrlAndCsrInput
XlaSparseDenseMatmulGradWithSgdAndCsrInput
XlaSparseDenseMatmulGradWithSgdAndCsrInput.Options	Optional attributes for XlaSparseDenseMatmulGradWithSgdAndCsrInput
XlaSparseDenseMatmulWithCsrInput
XlaSplitND<T>	Splits input tensor across all dimensions.
XlaSplitND.Options	Optional attributes for XlaSplitND
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.