Uses of Package
org.tensorflow.op.core

Packages that use org.tensorflow.op.core

Package	Description
org.tensorflow.op
org.tensorflow.op.core

Classes in org.tensorflow.op.core used by org.tensorflow.op

Class and 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
Any Computes the "logical or" of elements across dimensions of a tensor.
Any.Options Optional attributes for Any
AssertThat Asserts that the given condition is true.
AssertThat.Options Optional attributes for AssertThat
Assign Update 'ref' by assigning 'value' to it.
Assign.Options Optional attributes for Assign
AssignAdd 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 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.
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 Multiplies slices of two tensors in batches.
BatchMatMulV2.Options Optional attributes for BatchMatMulV2
BatchToSpace BatchToSpace for 4-D tensors of type T.
BatchToSpaceNd BatchToSpace for N-D tensors of type T.
Bitcast Bitcasts a tensor from one type to another without copying data.
BroadcastDynamicShape Return the shape of s0 op s1 with broadcast.
BroadcastTo Broadcast an array for a compatible shape.
Bucketize Bucketizes 'input' based on 'boundaries'.
ClipByValue Clips tensor values to a specified min and max.
CombinedNonMaxSuppression Greedily selects a subset of bounding boxes in descending order of score,
CombinedNonMaxSuppression.Options Optional attributes for CombinedNonMaxSuppression
Concat Concatenates tensors along one dimension.
Constant An operator producing a constant value.
ConsumeMutexLock This op consumes a lock created by `MutexLock`.
ControlTrigger Does nothing.
CountUpTo Increments 'ref' until it reaches 'limit'.
CudnnRNNCanonicalToParamsV2 Converts CudnnRNN params from canonical form to usable form.
CudnnRNNCanonicalToParamsV2.Options Optional attributes for CudnnRNNCanonicalToParamsV2
CudnnRNNParamsToCanonicalV2 Retrieves CudnnRNN params in canonical form.
CudnnRNNParamsToCanonicalV2.Options Optional attributes for CudnnRNNParamsToCanonicalV2
DecodePaddedRaw Reinterpret the bytes of a string as a vector of numbers.
DecodePaddedRaw.Options Optional attributes for DecodePaddedRaw
DeepCopy Makes a copy of `x`.
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 Destroys the temporary variable and returns its final value.
DrawBoundingBoxesV2 Draw bounding boxes on a batch of images.
DynamicPartition Partitions `data` into `num_partitions` tensors using indices from `partitions`.
DynamicStitch 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 Tensor contraction according to Einstein summation convention.
Empty Creates a tensor with the given shape.
Empty.Options Optional attributes for Empty
EmptyTensorList Creates and returns an empty tensor list.
EnsureShape Ensures that the tensor's shape matches the expected shape.
EuclideanNorm Computes the euclidean norm of elements across dimensions of a tensor.
EuclideanNorm.Options Optional attributes for EuclideanNorm
ExpandDims Inserts a dimension of 1 into a tensor's shape.
ExtractVolumePatches Extract `patches` from `input` and put them in the "depth" output dimension.
Fill Creates a tensor filled with a scalar value.
Fingerprint Generates fingerprint values.
FusedBatchNormGradV3 Gradient for batch normalization.
FusedBatchNormGradV3.Options Optional attributes for FusedBatchNormGradV3
FusedBatchNormV3 Batch normalization.
FusedBatchNormV3.Options Optional attributes for FusedBatchNormV3
Gather Gather slices from `params` axis `axis` according to `indices`.
Gather.Options Optional attributes for Gather
GatherNd Gather slices from `params` into a Tensor with shape specified by `indices`.
GcsConfigureBlockCache Re-configures the GCS block cache with the new configuration values.
GcsConfigureCredentials Configures the credentials used by the GCS client of the local TF runtime.
GenerateBigQueryReaderPartitions Generates serialized partition messages suitable for batch reads.
GenerateBigQueryReaderPartitions.Options Optional attributes for GenerateBigQueryReaderPartitions
GetSessionHandle Store the input tensor in the state of the current session.
GetSessionTensor 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
GuaranteeConst 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 Return histogram of values.
Identity 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
ImmutableConst Returns immutable tensor from memory region.
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 Adds v into specified rows of x.
InplaceSub Subtracts `v` into specified rows of `x`.
InplaceUpdate Updates specified rows with values in `v`.
IsVariableInitialized Checks whether a tensor has been initialized.
LinSpace Generates values in an interval.
LookupTableExport Outputs all keys and values in the table.
LookupTableFind 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.
LookupTableSize Computes the number of elements in the given table.
LoopCond Forwards the input to the output.
Lu 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 Returns the batched diagonal part of a batched tensor.
MatrixDiagV2 Returns a batched diagonal tensor with given batched diagonal values.
MatrixSetDiagV2 Returns a batched matrix tensor with new batched diagonal values.
Max Computes the maximum of elements across dimensions of a tensor.
Max.Options Optional attributes for Max
Merge Forwards the value of an available tensor from `inputs` to `output`.
Min Computes the minimum of elements across dimensions of a tensor.
Min.Options Optional attributes for Min
MirrorPad Pads a tensor with mirrored values.
MulNoNan 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.
NextAfter Returns the next representable value of `x1` in the direction of `x2`, element-wise.
NextIteration Makes its input available to the next iteration.
NonMaxSuppressionV5 Greedily selects a subset of bounding boxes in descending order of score,
NonMaxSuppressionV5.Options Optional attributes for NonMaxSuppressionV5
NoOp Does nothing.
OneHot Returns a one-hot tensor.
OneHot.Options Optional attributes for OneHot
OnesLike 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
Pad Pads a tensor.
ParallelConcat Concatenates a list of `N` tensors along the first dimension.
ParallelDynamicStitch Interleave the values from the `data` tensors into a single tensor.
Placeholder A placeholder op for a value that will be fed into the computation.
Placeholder.Options Optional attributes for Placeholder
PlaceholderWithDefault A placeholder op that passes through `input` when its output is not fed.
Print Prints a string scalar.
Print.Options Optional attributes for Print
Prod Computes the product of elements across dimensions of a tensor.
Prod.Options Optional attributes for Prod
QuantizedConcat Concatenates quantized tensors along one dimension.
QuantizedReshape Reshapes a quantized tensor as per the Reshape op.
Range Creates a sequence of numbers.
Rank Returns the rank of a tensor.
ReadVariableOp Reads the value of a variable.
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 Computes the maximum of elements across dimensions of a tensor.
ReduceMax.Options Optional attributes for ReduceMax
ReduceMin Computes the minimum of elements across dimensions of a tensor.
ReduceMin.Options Optional attributes for ReduceMin
ReduceProd Computes the product of elements across dimensions of a tensor.
ReduceProd.Options Optional attributes for ReduceProd
ReduceSum Computes the sum of elements across dimensions of a tensor.
ReduceSum.Options Optional attributes for ReduceSum
RefNextIteration Makes its input available to the next iteration.
RefSelect Forwards the `index`th element of `inputs` to `output`.
RefSwitch Forwards the ref tensor `data` to the output port determined by `pred`.
RemoteFusedGraphExecute Execute a sub graph on a remote processor.
Reshape Reshapes a tensor.
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
ResourceCountUpTo Increments variable pointed to by 'resource' until it reaches 'limit'.
ResourceGather Gather slices from the variable pointed to by `resource` according to `indices`.
ResourceGather.Options Optional attributes for ResourceGather
ResourceGatherNd
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`.
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
Reverse Reverses specific dimensions of a tensor.
ReverseSequence Reverses variable length slices.
ReverseSequence.Options Optional attributes for ReverseSequence
Roll Rolls the elements of a tensor along an axis.
Rpc Perform batches of RPC requests.
Rpc.Options Optional attributes for Rpc
ScaleAndTranslate
ScaleAndTranslate.Options Optional attributes for ScaleAndTranslate
ScatterAdd Adds sparse updates to a variable reference.
ScatterAdd.Options Optional attributes for ScatterAdd
ScatterDiv Divides a variable reference by sparse updates.
ScatterDiv.Options Optional attributes for ScatterDiv
ScatterMax Reduces sparse updates into a variable reference using the `max` operation.
ScatterMax.Options Optional attributes for ScatterMax
ScatterMin Reduces sparse updates into a variable reference using the `min` operation.
ScatterMin.Options Optional attributes for ScatterMin
ScatterMul Multiplies sparse updates into a variable reference.
ScatterMul.Options Optional attributes for ScatterMul
ScatterNd Scatter `updates` into a new tensor according to `indices`.
ScatterNdAdd Applies sparse addition to individual values or slices in a Variable.
ScatterNdAdd.Options Optional attributes for ScatterNdAdd
ScatterNdNonAliasingAdd Applies sparse addition to `input` using individual values or slices
ScatterNdSub Applies sparse subtraction to individual values or slices in a Variable.
ScatterNdSub.Options Optional attributes for ScatterNdSub
ScatterNdUpdate Applies sparse `updates` to individual values or slices within a given
ScatterNdUpdate.Options Optional attributes for ScatterNdUpdate
ScatterSub Subtracts sparse updates to a variable reference.
ScatterSub.Options Optional attributes for ScatterSub
ScatterUpdate Applies sparse updates to a variable reference.
ScatterUpdate.Options Optional attributes for ScatterUpdate
SelectV2
SetDiff1d 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 Returns the shape of a tensor.
ShapeN Returns shape of tensors.
Size Returns the size of a tensor.
Skipgram Parses a text file and creates a batch of examples.
Skipgram.Options Optional attributes for Skipgram
Slice Return a slice from 'input'.
Snapshot Returns a copy of the input tensor.
SpaceToBatchNd SpaceToBatch for N-D tensors of type T.
Split Splits a tensor into `num_split` tensors along one dimension.
SplitV Splits a tensor into `num_split` tensors along one dimension.
Squeeze Removes dimensions of size 1 from the shape of a tensor.
Squeeze.Options Optional attributes for Squeeze
Stack 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
StatefulStandardNormal Outputs random values from a normal distribution.
StatefulStandardNormalV2 Outputs random values from a normal distribution.
StopGradient Stops gradient computation.
StridedSlice Return a strided slice from `input`.
StridedSlice.Options Optional attributes for StridedSlice
StridedSliceAssign Assign `value` to the sliced l-value reference of `ref`.
StridedSliceAssign.Options Optional attributes for StridedSliceAssign
StridedSliceGrad Returns the gradient of `StridedSlice`.
StridedSliceGrad.Options Optional attributes for StridedSliceGrad
StringLower
StringLower.Options Optional attributes for StringLower
StringNGrams Creates ngrams from ragged string data.
StringUpper
StringUpper.Options Optional attributes for StringUpper
Sum Computes the sum of elements across dimensions of a tensor.
Sum.Options Optional attributes for Sum
SwitchCond Forwards `data` to the output port determined by `pred`.
TemporaryVariable 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 Concat the elements from the TensorArray into value `value`.
TensorArrayConcat.Options Optional attributes for TensorArrayConcat
TensorArrayGather 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
TensorArrayPack.Options Optional attributes for TensorArrayPack
TensorArrayRead 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 Concats all tensors in the list along the 0th dimension.
TensorListConcat.Options Optional attributes for TensorListConcat
TensorListConcatLists
TensorListConcatV2 Concats all tensors in the list along the 0th dimension.
TensorListElementShape 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 Creates a Tensor by indexing into the TensorList.
TensorListGetItem
TensorListLength Returns the number of tensors in the input tensor list.
TensorListPopBack 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 Stacks all tensors in the list.
TensorListStack.Options Optional attributes for TensorListStack
TensorScatterAdd Adds sparse `updates` to an existing tensor according to `indices`.
TensorScatterSub Subtracts sparse `updates` from an existing tensor according to `indices`.
TensorScatterUpdate Scatter `updates` into an existing tensor according to `indices`.
TensorStridedSliceUpdate Assign `value` to the sliced l-value reference of `input`.
TensorStridedSliceUpdate.Options Optional attributes for TensorStridedSliceUpdate
Tile Constructs a tensor by tiling a given tensor.
Timestamp Provides the time since epoch in seconds.
TryRpc Perform batches of RPC requests.
TryRpc.Options Optional attributes for TryRpc
Unbatch Reverses the operation of Batch for a single output Tensor.
Unbatch.Options Optional attributes for Unbatch
UnbatchGrad Gradient of Unbatch.
UnbatchGrad.Options Optional attributes for UnbatchGrad
Unique Finds unique elements along an axis of a tensor.
UniqueWithCounts Finds unique elements along an axis of a tensor.
UnravelIndex 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 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
VarHandleOp Creates a handle to a Variable resource.
VarHandleOp.Options Optional attributes for VarHandleOp
Variable Holds state in the form of a tensor that persists across steps.
Variable.Options Optional attributes for Variable
VariableShape 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 Selects elements from `x` or `y`, depending on `condition`.
Zeros An operator creating a constant initialized with zeros of the shape given by `dims`.
ZerosLike Returns a tensor of zeros with the same shape and type as x.

Classes in org.tensorflow.op.core used by org.tensorflow.op.core

Class and 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 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 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 Update 'ref' by assigning 'value' to it.
Assign.Options Optional attributes for Assign
AssignAdd 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 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 Multiplies slices of two tensors in batches.
BatchMatMulV2.Options Optional attributes for BatchMatMulV2
BatchToSpace BatchToSpace for 4-D tensors of type T.
BatchToSpaceNd BatchToSpace for N-D tensors of type T.
Bitcast Bitcasts a tensor from one type to another without copying data.
BlockLSTM Computes the LSTM cell forward propagation for all the time steps.
BlockLSTM.Options Optional attributes for BlockLSTM
BlockLSTMGrad Computes the LSTM cell backward propagation for the entire time sequence.
BlockLSTMGradV2 Computes the LSTM cell backward propagation for the entire time sequence.
BlockLSTMV2 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 Return the shape of s0 op s1 with broadcast.
BroadcastGradientArgs Return the reduction indices for computing gradients of s0 op s1 with broadcast.
BroadcastTo Broadcast an array for a compatible shape.
Bucketize Bucketizes 'input' based on 'boundaries'.
CacheDatasetV2
ChooseFastestDataset
ClipByValue Clips tensor values to a specified min and max.
CollectiveGather Mutually accumulates multiple tensors of identical type and shape.
CollectiveGather.Options Optional attributes for CollectiveGather
CollectivePermute 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 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 An operator producing a constant value.
ConsumeMutexLock This op consumes a lock created by `MutexLock`.
ControlTrigger Does nothing.
CountUpTo Increments 'ref' until it reaches 'limit'.
CrossReplicaSum An Op to sum inputs across replicated TPU instances.
CSVDataset
CudnnRNNBackpropV3 Backprop step of CudnnRNNV3.
CudnnRNNBackpropV3.Options Optional attributes for CudnnRNNBackpropV3
CudnnRNNCanonicalToParamsV2 Converts CudnnRNN params from canonical form to usable form.
CudnnRNNCanonicalToParamsV2.Options Optional attributes for CudnnRNNCanonicalToParamsV2
CudnnRNNParamsToCanonicalV2 Retrieves CudnnRNN params in canonical form.
CudnnRNNParamsToCanonicalV2.Options Optional attributes for CudnnRNNParamsToCanonicalV2
CudnnRNNV3 A RNN backed by cuDNN.
CudnnRNNV3.Options Optional attributes for CudnnRNNV3
CumulativeLogsumexp 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 Identity op for gradient debugging.
DebugGradientRefIdentity Identity op for gradient debugging.
DecodePaddedRaw 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 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 Destroys the temporary variable and returns its final value.
DirectedInterleaveDataset A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
DrawBoundingBoxesV2 Draw bounding boxes on a batch of images.
DynamicPartition Partitions `data` into `num_partitions` tensors using indices from `partitions`.
DynamicStitch 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 Tensor contraction according to Einstein summation convention.
Empty 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 Ensures that the tensor's shape matches the expected shape.
Enter Creates or finds a child frame, and makes `data` available to the child frame.
Enter.Options Optional attributes for Enter
EuclideanNorm Computes the euclidean norm of elements across dimensions of a tensor.
EuclideanNorm.Options Optional attributes for EuclideanNorm
Exit Exits the current frame to its parent frame.
ExpandDims 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 Extract `patches` from `input` and put them in the "depth" output dimension.
Fill Creates a tensor filled with a scalar value.
Fingerprint Generates fingerprint values.
FusedBatchNormGradV3 Gradient for batch normalization.
FusedBatchNormGradV3.Options Optional attributes for FusedBatchNormGradV3
FusedBatchNormV3 Batch normalization.
FusedBatchNormV3.Options Optional attributes for FusedBatchNormV3
Gather Gather slices from `params` axis `axis` according to `indices`.
Gather.Options Optional attributes for Gather
GatherNd Gather slices from `params` into a Tensor with shape specified by `indices`.
GcsConfigureBlockCache Re-configures the GCS block cache with the new configuration values.
GcsConfigureCredentials Configures the credentials used by the GCS client of the local TF runtime.
GenerateBigQueryReaderPartitions Generates serialized partition messages suitable for batch reads.
GenerateBigQueryReaderPartitions.Options Optional attributes for GenerateBigQueryReaderPartitions
GetSessionHandle Store the input tensor in the state of the current session.
GetSessionTensor 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 Computes the GRU cell forward propagation for 1 time step.
GRUBlockCellGrad Computes the GRU cell back-propagation for 1 time step.
GuaranteeConst 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 Return histogram of values.
Identity 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 Returns immutable tensor from memory region.
InfeedDequeue 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 Adds v into specified rows of x.
InplaceSub Subtracts `v` into specified rows of `x`.
InplaceUpdate 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 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 Outputs all keys and values in the table.
LookupTableFind 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 Applies lower_bound(sorted_search_values, values) along each row.
LSTMBlockCell Computes the LSTM cell forward propagation for 1 time step.
LSTMBlockCell.Options Optional attributes for LSTMBlockCell
LSTMBlockCellGrad Computes the LSTM cell backward propagation for 1 timestep.
Lu 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 Returns the batched diagonal part of a batched tensor.
MatrixDiagV2 Returns a batched diagonal tensor with given batched diagonal values.
MatrixSetDiagV2 Returns a batched matrix tensor with new batched diagonal values.
Max 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 Forwards the value of an available tensor from `inputs` to `output`.
Min Computes the minimum of elements across dimensions of a tensor.
Min.Options Optional attributes for Min
MirrorPad Pads a tensor with mirrored values.
MirrorPadGrad Gradient op for `MirrorPad` op.
MulNoNan 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 Outputs a tensor containing the reduction across all input tensors.
NcclBroadcast Sends `input` to all devices that are connected to the output.
NcclReduce Reduces `input` from `num_devices` using `reduction` to a single device.
NearestNeighbors Selects the k nearest centers for each point.
NextAfter Returns the next representable value of `x1` in the direction of `x2`, element-wise.
NextIteration Makes its input available to the next iteration.
NonDeterministicInts Non-deterministically generates some integers.
NonMaxSuppressionV5 Greedily selects a subset of bounding boxes in descending order of score,
NonMaxSuppressionV5.Options Optional attributes for NonMaxSuppressionV5
NonSerializableDataset
NoOp Does nothing.
OneHot Returns a one-hot tensor.
OneHot.Options Optional attributes for OneHot
OnesLike 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 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 Pads a tensor.
ParallelConcat Concatenates a list of `N` tensors along the first dimension.
ParallelDynamicStitch Interleave the values from the `data` tensors into a single tensor.
Placeholder A placeholder op for a value that will be fed into the computation.
Placeholder.Options Optional attributes for Placeholder
PlaceholderWithDefault 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 Computes the product of elements across dimensions of a tensor.
Prod.Options Optional attributes for Prod
QuantizedConcat Concatenates quantized tensors along one dimension.
QuantizedConv2DAndRelu
QuantizedConv2DAndRelu.Options Optional attributes for QuantizedConv2DAndRelu
QuantizedConv2DAndReluAndRequantize
QuantizedConv2DAndReluAndRequantize.Options Optional attributes for QuantizedConv2DAndReluAndRequantize
QuantizedConv2DAndRequantize
QuantizedConv2DAndRequantize.Options Optional attributes for QuantizedConv2DAndRequantize
QuantizedConv2DPerChannel Computes QuantizedConv2D per channel.
QuantizedConv2DPerChannel.Options Optional attributes for QuantizedConv2DPerChannel
QuantizedConv2DWithBias
QuantizedConv2DWithBias.Options Optional attributes for QuantizedConv2DWithBias
QuantizedConv2DWithBiasAndRelu
QuantizedConv2DWithBiasAndRelu.Options Optional attributes for QuantizedConv2DWithBiasAndRelu
QuantizedConv2DWithBiasAndReluAndRequantize
QuantizedConv2DWithBiasAndReluAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize
QuantizedConv2DWithBiasAndRequantize
QuantizedConv2DWithBiasAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasAndRequantize
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
QuantizedConv2DWithBiasSumAndRelu
QuantizedConv2DWithBiasSumAndRelu.Options Optional attributes for QuantizedConv2DWithBiasSumAndRelu
QuantizedConv2DWithBiasSumAndReluAndRequantize
QuantizedConv2DWithBiasSumAndReluAndRequantize.Options Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize
QuantizedDepthwiseConv2D Computes quantized depthwise Conv2D.
QuantizedDepthwiseConv2D.Options Optional attributes for QuantizedDepthwiseConv2D
QuantizedDepthwiseConv2DWithBias Computes quantized depthwise Conv2D with Bias.
QuantizedDepthwiseConv2DWithBias.Options Optional attributes for QuantizedDepthwiseConv2DWithBias
QuantizedDepthwiseConv2DWithBiasAndRelu Computes quantized depthwise Conv2D with Bias and Relu.
QuantizedDepthwiseConv2DWithBiasAndRelu.Options Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize Computes quantized depthwise Conv2D with Bias, Relu and Requantize.
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
QuantizedMatMulWithBias Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add.
QuantizedMatMulWithBias.Options Optional attributes for QuantizedMatMulWithBias
QuantizedMatMulWithBiasAndRelu Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion.
QuantizedMatMulWithBiasAndRelu.Options Optional attributes for QuantizedMatMulWithBiasAndRelu
QuantizedMatMulWithBiasAndReluAndRequantize 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 Reshapes a quantized tensor as per the Reshape op.
RaggedGather Gather ragged slices from `params` axis `0` according to `indices`.
RaggedRange Returns a `RaggedTensor` containing the specified sequences of numbers.
RaggedTensorFromVariant Decodes a `variant` Tensor into a `RaggedTensor`.
RaggedTensorToSparse Converts a `RaggedTensor` into a `SparseTensor` with the same values.
RaggedTensorToTensor Create a dense tensor from a ragged tensor, possibly altering its shape.
RaggedTensorToVariant Encodes a `RaggedTensor` into a `variant` Tensor.
Range Creates a sequence of numbers.
Rank Returns the rank of a tensor.
ReadVariableOp 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 Computes the maximum of elements across dimensions of a tensor.
ReduceMax.Options Optional attributes for ReduceMax
ReduceMin Computes the minimum of elements across dimensions of a tensor.
ReduceMin.Options Optional attributes for ReduceMin
ReduceProd Computes the product of elements across dimensions of a tensor.
ReduceProd.Options Optional attributes for ReduceProd
ReduceSum Computes the sum of elements across dimensions of a tensor.
ReduceSum.Options Optional attributes for ReduceSum
RefEnter Creates or finds a child frame, and makes `data` available to the child frame.
RefEnter.Options Optional attributes for RefEnter
RefExit Exits the current frame to its parent frame.
RefIdentity Return the same ref tensor as the input ref tensor.
RefMerge Forwards the value of an available tensor from `inputs` to `output`.
RefNextIteration Makes its input available to the next iteration.
RefSelect Forwards the `index`th element of `inputs` to `output`.
RefSwitch 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 Requantizes input with min and max values known per channel.
Reshape 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 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 Increments variable pointed to by 'resource' until it reaches 'limit'.
ResourceGather Gather slices from the variable pointed to by `resource` according to `indices`.
ResourceGather.Options Optional attributes for ResourceGather
ResourceGatherNd
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 Reverses specific dimensions of a tensor.
ReverseSequence Reverses variable length slices.
ReverseSequence.Options Optional attributes for ReverseSequence
RngSkip Advance the counter of a counter-based RNG.
Roll 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
ScaleAndTranslateGrad.Options Optional attributes for ScaleAndTranslateGrad
ScatterAdd Adds sparse updates to a variable reference.
ScatterAdd.Options Optional attributes for ScatterAdd
ScatterDiv Divides a variable reference by sparse updates.
ScatterDiv.Options Optional attributes for ScatterDiv
ScatterMax Reduces sparse updates into a variable reference using the `max` operation.
ScatterMax.Options Optional attributes for ScatterMax
ScatterMin Reduces sparse updates into a variable reference using the `min` operation.
ScatterMin.Options Optional attributes for ScatterMin
ScatterMul Multiplies sparse updates into a variable reference.
ScatterMul.Options Optional attributes for ScatterMul
ScatterNd Scatter `updates` into a new tensor according to `indices`.
ScatterNdAdd Applies sparse addition to individual values or slices in a Variable.
ScatterNdAdd.Options Optional attributes for ScatterNdAdd
ScatterNdNonAliasingAdd Applies sparse addition to `input` using individual values or slices
ScatterNdSub Applies sparse subtraction to individual values or slices in a Variable.
ScatterNdSub.Options Optional attributes for ScatterNdSub
ScatterNdUpdate Applies sparse `updates` to individual values or slices within a given
ScatterNdUpdate.Options Optional attributes for ScatterNdUpdate
ScatterSub Subtracts sparse updates to a variable reference.
ScatterSub.Options Optional attributes for ScatterSub
ScatterUpdate Applies sparse updates to a variable reference.
ScatterUpdate.Options Optional attributes for ScatterUpdate
SelectV2
SendTPUEmbeddingGradients Performs gradient updates of embedding tables.
SetDiff1d 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 Returns the shape of a tensor.
ShapeN 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 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 Return a slice from 'input'.
SlidingWindowDataset Creates a dataset that passes a sliding window over `input_dataset`.
Snapshot 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 SpaceToBatch for N-D tensors of type T.
SparseApplyAdagradV2 Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
SparseApplyAdagradV2.Options Optional attributes for SparseApplyAdagradV2
Split Splits a tensor into `num_split` tensors along one dimension.
SplitV Splits a tensor into `num_split` tensors along one dimension.
Squeeze Removes dimensions of size 1 from the shape of a tensor.
Squeeze.Options Optional attributes for Squeeze
Stack 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
StatefulStandardNormal Outputs random values from a normal distribution.
StatefulStandardNormalV2 Outputs random values from a normal distribution.
StatefulTruncatedNormal Outputs random values from a truncated normal distribution.
StatefulUniform Outputs random values from a uniform distribution.
StatefulUniformFullInt Outputs random integers from a uniform distribution.
StatefulUniformInt 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 Stops gradient computation.
StridedSlice Return a strided slice from `input`.
StridedSlice.Options Optional attributes for StridedSlice
StridedSliceAssign Assign `value` to the sliced l-value reference of `ref`.
StridedSliceAssign.Options Optional attributes for StridedSliceAssign
StridedSliceGrad Returns the gradient of `StridedSlice`.
StridedSliceGrad.Options Optional attributes for StridedSliceGrad
StringLower
StringLower.Options Optional attributes for StringLower
StringNGrams Creates ngrams from ragged string data.
StringUpper
StringUpper.Options Optional attributes for StringUpper
Sum Computes the sum of elements across dimensions of a tensor.
Sum.Options Optional attributes for Sum
SwitchCond Forwards `data` to the output port determined by `pred`.
TemporaryVariable 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 Concat the elements from the TensorArray into value `value`.
TensorArrayConcat.Options Optional attributes for TensorArrayConcat
TensorArrayGather 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
TensorArrayPack.Options Optional attributes for TensorArrayPack
TensorArrayRead 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 Concats all tensors in the list along the 0th dimension.
TensorListConcat.Options Optional attributes for TensorListConcat
TensorListConcatLists
TensorListConcatV2 Concats all tensors in the list along the 0th dimension.
TensorListElementShape 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 Creates a Tensor by indexing into the TensorList.
TensorListGetItem
TensorListLength Returns the number of tensors in the input tensor list.
TensorListPopBack 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 Stacks all tensors in the list.
TensorListStack.Options Optional attributes for TensorListStack
TensorScatterAdd Adds sparse `updates` to an existing tensor according to `indices`.
TensorScatterSub Subtracts sparse `updates` from an existing tensor according to `indices`.
TensorScatterUpdate Scatter `updates` into an existing tensor according to `indices`.
TensorStridedSliceUpdate 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 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 Connects N inputs to an N-way replicated TPU computation.
TPUReplicatedOutput 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 Calculate product with tridiagonal matrix.
TridiagonalSolve Solves tridiagonal systems of equations.
TridiagonalSolve.Options Optional attributes for TridiagonalSolve
TryRpc Perform batches of RPC requests.
TryRpc.Options Optional attributes for TryRpc
Unbatch Reverses the operation of Batch for a single output Tensor.
Unbatch.Options Optional attributes for Unbatch
UnbatchGrad Gradient of Unbatch.
UnbatchGrad.Options Optional attributes for UnbatchGrad
UnicodeDecode 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 Finds unique elements along an axis of a tensor.
UniqueDataset Creates a dataset that contains the unique elements of `input_dataset`.
UniqueWithCounts Finds unique elements along an axis of a tensor.
UnravelIndex 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 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 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 Holds state in the form of a tensor that persists across steps.
Variable.Options Optional attributes for Variable
VariableShape 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 Selects elements from `x` or `y`, depending on `condition`.
WorkerHeartbeat Worker heartbeat op.
WrapDatasetVariant
WriteRawProtoSummary
Zeros An operator creating a constant initialized with zeros of the shape given by `dims`.
ZerosLike Returns a tensor of zeros with the same shape and type as x.