Package org.tensorflow.op.core

Class Summary

Class	Description
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
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
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.
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.
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
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
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
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
BoostedTreesUpdateEnsemble	Updates the tree ensemble by either adding a layer to the last tree being grown
BoostedTreesUpdateEnsembleV2	Updates the tree ensemble by adding a layer to the last tree being grown
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
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.
CombinedNonMaxSuppression	Greedily selects a subset of bounding boxes in descending order of score,
CombinedNonMaxSuppression.Options	Optional attributes for CombinedNonMaxSuppression
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.
CountUpTo<T extends Number>	Increments 'ref' until it reaches 'limit'.
CrossReplicaSum<T extends Number>	An Op to sum inputs across replicated TPU instances.
CSVDataset
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
DatasetCardinality	Returns the cardinality of `input_dataset`.
DatasetFromGraph	Creates a dataset from the given `graph_def`.
DebugGradientIdentity<T>	Identity op for gradient debugging.
DebugGradientRefIdentity<T>	Identity op for gradient debugging.
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
DeleteSessionTensor	Delete the tensor specified by its handle in the session.
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.
DirectedInterleaveDataset	A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
DrawBoundingBoxesV2<T extends Number>	Draw bounding boxes on a batch of images.
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
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.
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
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
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.
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.
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.
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`.
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...
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
IgnoreErrorsDataset	Creates a dataset that contains the elements of `input_dataset` ignoring errors.
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.
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 with values in `v`.
IsBoostedTreesEnsembleInitialized	Checks whether a tree ensemble has been initialized.
IsBoostedTreesQuantileStreamResourceInitialized	Checks whether a quantile stream has been initialized.
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.
LinSpace<T extends Number>	Generates values in an interval.
LMDBDataset
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
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
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.
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
MapUnstage.Options	Optional attributes for MapUnstage
MapUnstageNoKey	Op removes and returns a random (key, value)
MapUnstageNoKey.Options	Optional attributes for MapUnstageNoKey
MatrixDiagPartV2<T>	Returns the batched diagonal part of a batched tensor.
MatrixDiagV2<T>	Returns a batched diagonal tensor with given batched diagonal values.
MatrixSetDiagV2<T>	Returns a batched matrix tensor with new batched diagonal values.
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.
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.
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,
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.
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
OrderedMapStage.Options	Optional attributes for OrderedMapStage
OrderedMapUnstage	Op removes and returns the values associated with the key
OrderedMapUnstage.Options	Optional attributes for OrderedMapUnstage
OrderedMapUnstageNoKey	Op removes and returns the (key, value) element with the smallest
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.
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.
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
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
QuantizedReshape<T>	Reshapes a quantized tensor as per the Reshape op.
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
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`.
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
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
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
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
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
ScatterNdNonAliasingAdd<T>	Applies sparse addition to `input` using individual values or slices
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
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>
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
ShuffleDatasetV2
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
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
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.
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
StringLower.Options	Optional attributes for StringLower
StringNGrams<T extends Number>	Creates ngrams from ragged string data.
StringUpper
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
TensorScatterAdd<T>	Adds sparse `updates` to an existing tensor according to `indices`.
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.
TPUCompilationResult	CompilationResultProto indicating the status of the TPU compilation.
TPUEmbeddingActivations	An op enabling differentiation of TPU Embeddings.
TPUOrdinalSelector	A TPU core selector Op.
TPUReplicatedInput<T>	Connects N inputs to an N-way replicated TPU computation.
TPUReplicatedOutput<T>	Connects outputs of an N-way replicated computation to N outputs.
TPUReplicateMetadata	Metadata indicaitng 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
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
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.