|
Abort
|
Raise a exception to abort the process when called.
|
|
All
|
Computes the "logical and" of elements across dimensions of a tensor.
|
|
AllToAll
<T>
|
An Op to exchange data across TPU replicas.
|
|
AnonymousIteratorV2
|
A container for an iterator resource.
|
|
AnonymousMemoryCache
|
|
|
AnonymousMultiDeviceIterator
|
A container for a multi device iterator resource.
|
|
AnonymousRandomSeedGenerator
|
|
|
AnonymousSeedGenerator
|
|
|
Any
|
Computes the "logical or" of elements across dimensions of a tensor.
|
|
ApplyAdagradV2
<T>
|
Update '*var' according to the adagrad scheme.
|
|
AssertCardinalityDataset
|
|
|
AssertNextDataset
|
A transformation that asserts which transformations happen next.
|
|
AssertThat
|
Asserts that the given condition is true.
|
|
Assign
<T>
|
Update 'ref' by assigning 'value' to it.
|
|
AssignAdd
<T>
|
Update 'ref' by adding 'value' to it.
|
|
AssignAddVariableOp
|
Adds a value to the current value of a variable.
|
|
AssignSub
<T>
|
Update 'ref' by subtracting 'value' from it.
|
|
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.
|
|
BandedTriangularSolve
<T>
|
|
|
Barrier
|
Defines a barrier that persists across different graph executions.
|
|
BarrierClose
|
Closes the given barrier.
|
|
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.
|
|
Batch
|
Batches all input tensors nondeterministically.
|
|
BatchMatMulV2
<T>
|
Multiplies slices of two tensors in batches.
|
|
BatchMatMulV3
<V>
|
Multiplies slices of two tensors in batches.
|
|
BatchToSpace
<T>
|
BatchToSpace for 4-D tensors of type T.
|
|
BatchToSpaceNd
<T>
|
BatchToSpace for N-D tensors of type T.
|
|
BesselI0
<T extends Number>
|
|
|
BesselI1
<T extends Number>
|
|
|
BesselJ0
<T extends Number>
|
|
|
BesselJ1
<T extends Number>
|
|
|
BesselK0
<T extends Number>
|
|
|
BesselK0e
<T extends Number>
|
|
|
BesselK1
<T extends Number>
|
|
|
BesselK1e
<T extends Number>
|
|
|
BesselY0
<T extends Number>
|
|
|
BesselY1
<T extends Number>
|
|
|
Bitcast
<U>
|
Bitcasts a tensor from one type to another without copying data.
|
|
BlockLSTM
<T extends Number>
|
Computes the LSTM cell forward propagation for all the time steps.
|
|
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.
|
|
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.
|
|
BoostedTreesCalculateBestFeatureSplitV2
|
Calculates gains for each feature and returns the best possible split information for each node.
|
|
BoostedTreesCalculateBestGainsPerFeature
|
Calculates gains for each feature and returns the best possible split information for the feature.
|
|
BoostedTreesCenterBias
|
Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior.
|
|
BoostedTreesCreateEnsemble
|
Creates a tree ensemble model and returns a handle to it.
|
|
BoostedTreesCreateQuantileStreamResource
|
Create the Resource for Quantile Streams.
|
|
BoostedTreesDeserializeEnsemble
|
Deserializes a serialized tree ensemble config and replaces current tree
ensemble.
|
|
BoostedTreesEnsembleResourceHandleOp
|
Creates a handle to a BoostedTreesEnsembleResource
|
|
BoostedTreesExampleDebugOutputs
|
Debugging/model interpretability outputs for each example.
|
|
BoostedTreesFlushQuantileSummaries
|
Flush the quantile summaries from each quantile stream resource.
|
|
BoostedTreesGetEnsembleStates
|
Retrieves the tree ensemble resource stamp token, number of trees and growing statistics.
|
|
BoostedTreesMakeQuantileSummaries
|
Makes the summary of quantiles for the batch.
|
|
BoostedTreesMakeStatsSummary
|
Makes the summary of accumulated stats for the batch.
|
|
BoostedTreesPredict
|
Runs multiple additive regression ensemble predictors on input instances and
computes the logits.
|
|
BoostedTreesQuantileStreamResourceAddSummaries
|
Add the quantile summaries to each quantile stream resource.
|
|
BoostedTreesQuantileStreamResourceDeserialize
|
Deserialize bucket boundaries and ready flag into current QuantileAccumulator.
|
|
BoostedTreesQuantileStreamResourceFlush
|
Flush the summaries for a quantile stream resource.
|
|
BoostedTreesQuantileStreamResourceGetBucketBoundaries
|
Generate the bucket boundaries for each feature based on accumulated summaries.
|
|
BoostedTreesQuantileStreamResourceHandleOp
|
Creates a handle to a BoostedTreesQuantileStreamResource.
|
|
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.
|
|
BoostedTreesTrainingPredict
|
Runs multiple additive regression ensemble predictors on input instances and
computes the update to cached logits.
|
|
BoostedTreesUpdateEnsemble
|
Updates the tree ensemble by either adding a layer to the last tree being grown
or by starting a new tree.
|
|
BoostedTreesUpdateEnsembleV2
|
Updates the tree ensemble by adding a layer to the last tree being grown
or by starting a new tree.
|
|
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'.
|
|
CSRSparseMatrixComponents
<T>
|
Reads out the CSR components at batch `index`.
|
|
CSRSparseMatrixToDense
<T>
|
Convert a (possibly batched) CSRSparseMatrix to dense.
|
|
CSRSparseMatrixToSparseTensor
<T>
|
Converts a (possibly batched) CSRSparesMatrix to a SparseTensor.
|
|
CSVDataset
|
|
|
CSVDatasetV2
|
|
|
CTCLossV2
|
Calculates the CTC Loss (log probability) for each batch entry.
|
|
CacheDatasetV2
|
|
|
CheckNumericsV2
<T extends Number>
|
Checks a tensor for NaN, -Inf and +Inf values.
|
|
ChooseFastestDataset
|
|
|
ClipByValue
<T>
|
Clips tensor values to a specified min and max.
|
|
CollectiveBcastRecvV2
<U>
|
Receives a tensor value broadcast from another device.
|
|
CollectiveBcastSendV2
<T>
|
Broadcasts a tensor value to one or more other devices.
|
|
CollectiveGather
<T extends Number>
|
Mutually accumulates multiple tensors of identical type and shape.
|
|
CollectiveGatherV2
<T extends Number>
|
Mutually accumulates multiple tensors of identical type and shape.
|
|
CollectivePermute
<T>
|
An Op to permute tensors across replicated TPU instances.
|
|
CollectiveReduceV2
<T extends Number>
|
Mutually reduces multiple tensors of identical type and shape.
|
|
CombinedNonMaxSuppression
|
Greedily selects a subset of bounding boxes in descending order of score,
This operation performs non_max_suppression on the inputs per batch, across
all classes.
|
|
CompositeTensorVariantFromComponents
|
Encodes an `ExtensionType` value into a `variant` scalar Tensor.
|
|
CompositeTensorVariantToComponents
|
Decodes a `variant` scalar Tensor into an `ExtensionType` value.
|
|
CompressElement
|
Compresses a dataset element.
|
|
ComputeBatchSize
|
Computes the static batch size of a dataset sans partial batches.
|
|
Concat
<T>
|
Concatenates tensors along one dimension.
|
|
ConfigureDistributedTPU
|
Sets up the centralized structures for a distributed TPU system.
|
|
ConfigureTPUEmbedding
|
Sets up TPUEmbedding in a distributed TPU system.
|
|
Constant
<T>
|
An operator producing a constant value.
|
|
ConsumeMutexLock
|
This op consumes a lock created by `MutexLock`.
|
|
ControlTrigger
|
Does nothing.
|
|
Copy
<T>
|
Copy a tensor from CPU-to-CPU or GPU-to-GPU.
|
|
CopyHost
<T>
|
Copy a tensor to host.
|
|
CountUpTo
<T extends Number>
|
Increments 'ref' until it reaches 'limit'.
|
|
CrossReplicaSum
<T extends Number>
|
An Op to sum inputs across replicated TPU instances.
|
|
CudnnRNNBackpropV3
<T extends Number>
|
Backprop step of CudnnRNNV3.
|
|
CudnnRNNCanonicalToParamsV2
<T extends Number>
|
Converts CudnnRNN params from canonical form to usable form.
|
|
CudnnRNNParamsToCanonicalV2
<T extends Number>
|
Retrieves CudnnRNN params in canonical form.
|
|
CudnnRNNV3
<T extends Number>
|
A RNN backed by cuDNN.
|
|
CumulativeLogsumexp
<T extends Number>
|
Compute the cumulative product of the tensor `x` along `axis`.
|
|
DataServiceDataset
|
Creates a dataset that reads data from the tf.data service.
|
|
DataServiceDatasetV2
|
Creates a dataset that reads data from the tf.data service.
|
|
DatasetCardinality
|
Returns the cardinality of `input_dataset`.
|
|
DatasetFromGraph
|
Creates a dataset from the given `graph_def`.
|
|
DatasetToGraphV2
|
Returns a serialized GraphDef representing `input_dataset`.
|
|
Dawsn
<T extends Number>
|
|
|
DebugGradientIdentity
<T>
|
Identity op for gradient debugging.
|
|
DebugGradientRefIdentity
<T>
|
Identity op for gradient debugging.
|
|
DebugIdentity
<T>
|
Provides an identity mapping of the non-Ref type input tensor for debugging.
|
|
DebugIdentityV2
<T>
|
Debug Identity V2 Op.
|
|
DebugNanCount
|
Debug NaN Value Counter Op.
|
|
DebugNumericSummary
|
Debug Numeric Summary Op.
|
|
DebugNumericSummaryV2
<U extends Number>
|
Debug Numeric Summary V2 Op.
|
|
DecodeImage
<T extends Number>
|
Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
|
|
DecodePaddedRaw
<T extends Number>
|
Reinterpret the bytes of a string as a vector of numbers.
|
|
DecodeProto
|
The op extracts fields from a serialized protocol buffers message into tensors.
|
|
DeepCopy
<T>
|
Makes a copy of `x`.
|
|
DeleteIterator
|
A container for an iterator resource.
|
|
DeleteMemoryCache
|
|
|
DeleteMultiDeviceIterator
|
A container for an iterator resource.
|
|
DeleteRandomSeedGenerator
|
|
|
DeleteSeedGenerator
|
|
|
DeleteSessionTensor
|
Delete the tensor specified by its handle in the session.
|
|
DenseBincount
<U extends Number>
|
Counts the number of occurrences of each value in an integer array.
|
|
DenseCountSparseOutput
<U extends Number>
|
Performs sparse-output bin counting for a tf.tensor input.
|
|
DenseToCSRSparseMatrix
|
Converts a dense tensor to a (possibly batched) CSRSparseMatrix.
|
|
DestroyResourceOp
|
Deletes the resource specified by the handle.
|
|
DestroyTemporaryVariable
<T>
|
Destroys the temporary variable and returns its final value.
|
|
DeviceIndex
|
Return the index of device the op runs.
|
|
DirectedInterleaveDataset
|
A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
|
|
DrawBoundingBoxesV2
<T extends Number>
|
Draw bounding boxes on a batch of images.
|
|
DummyIterationCounter
|
|
|
DummyMemoryCache
|
|
|
DummySeedGenerator
|
|
|
DynamicPartition
<T>
|
Partitions `data` into `num_partitions` tensors using indices from `partitions`.
|
|
DynamicStitch
<T>
|
Interleave the values from the `data` tensors into a single tensor.
|
|
EditDistance
|
Computes the (possibly normalized) Levenshtein Edit Distance.
|
|
Eig
<U>
|
Computes the eigen decomposition of one or more square matrices.
|
|
Einsum
<T>
|
Tensor contraction according to Einstein summation convention.
|
|
Empty
<T>
|
Creates a tensor with the given shape.
|
|
EmptyTensorList
|
Creates and returns an empty tensor list.
|
|
EmptyTensorMap
|
Creates and returns an empty tensor map.
|
|
EncodeProto
|
The op serializes protobuf messages provided in the input tensors.
|
|
EnqueueTPUEmbeddingIntegerBatch
|
An op that enqueues a list of input batch tensors to TPUEmbedding.
|
|
EnqueueTPUEmbeddingRaggedTensorBatch
|
Eases the porting of code that uses tf.nn.embedding_lookup().
|
|
EnqueueTPUEmbeddingSparseBatch
|
An op that enqueues TPUEmbedding input indices from a SparseTensor.
|
|
EnqueueTPUEmbeddingSparseTensorBatch
|
Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
|
|
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.
|
|
Erfinv
<T extends Number>
|
|
|
EuclideanNorm
<T>
|
Computes the euclidean norm of elements across dimensions of a tensor.
|
|
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.
|
|
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.
|
|
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.
|
|
ExperimentalStatsAggregatorSummary
|
Produces a summary of any statistics recorded by the given statistics manager.
|
|
ExperimentalUnbatchDataset
|
A dataset that splits the elements of its input into multiple elements.
|
|
Expint
<T extends Number>
|
|
|
ExtractGlimpseV2
|
Extracts a glimpse from the input tensor.
|
|
ExtractVolumePatches
<T extends Number>
|
Extract `patches` from `input` and put them in the `"depth"` output dimension.
|
|
Fill
<U>
|
Creates a tensor filled with a scalar value.
|
|
FinalizeDataset
|
Creates a dataset by applying `tf.data.Options` to `input_dataset`.
|
|
Fingerprint
|
Generates fingerprint values.
|
|
FresnelCos
<T extends Number>
|
|
|
FresnelSin
<T extends Number>
|
|
|
FusedBatchNormGradV3
<T extends Number, U extends Number>
|
Gradient for batch normalization.
|
|
FusedBatchNormV3
<T extends Number, U extends Number>
|
Batch normalization.
|
|
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.
|
|
Gather
<T>
|
Gather slices from `params` axis `axis` according to `indices`.
|
|
GatherNd
<T>
|
Gather slices from `params` into a Tensor with shape specified by `indices`.
|
|
GenerateBoundingBoxProposals
|
This op produces Region of Interests from given bounding boxes(bbox_deltas) encoded wrt anchors according to eq.2 in arXiv:1506.01497
The op selects top `pre_nms_topn` scoring boxes, decodes them with respect to anchors,
applies non-maximal suppression on overlapping boxes with higher than
`nms_threshold` intersection-over-union (iou) value, discarding boxes where shorter
side is less than `min_size`.
|
|
GetOptions
|
Returns the `tf.data.Options` attached to `input_dataset`.
|
|
GetSessionHandle
|
Store the input tensor in the state of the current session.
|
|
GetSessionTensor
<T>
|
Get the value of the tensor specified by its handle.
|
|
GuaranteeConst
<T>
|
Gives a guarantee to the TF runtime that the input tensor is a constant.
|
|
HashTable
|
Creates a non-initialized hash table.
|
|
HistogramFixedWidth
<U extends Number>
|
Return histogram of values.
|
|
Identity
<T>
|
Return a tensor with the same shape and contents as the input tensor or value.
|
|
IdentityN
|
Returns a list of tensors with the same shapes and contents as the input
tensors.
|
|
IgnoreErrorsDataset
|
Creates a dataset that contains the elements of `input_dataset` ignoring errors.
|
|
ImageProjectiveTransformV2
<T extends Number>
|
Applies the given transform to each of the images.
|
|
ImageProjectiveTransformV3
<T extends Number>
|
Applies the given transform to each of the images.
|
|
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.
|
|
InfeedEnqueuePrelinearizedBuffer
|
An op which enqueues prelinearized buffer into TPU infeed.
|
|
InfeedEnqueueTuple
|
Feeds multiple Tensor values into the computation as an XLA tuple.
|
|
InitializeTable
|
Table initializer that takes two tensors for keys and values respectively.
|
|
InitializeTableFromDataset
|
|
|
InitializeTableFromTextFile
|
Initializes a table from a text file.
|
|
InplaceAdd
<T>
|
Adds v into specified rows of x.
|
|
InplaceSub
<T>
|
Subtracts `v` into specified rows of `x`.
|
|
InplaceUpdate
<T>
|
Updates specified rows 'i' with values 'v'.
|
|
IsBoostedTreesEnsembleInitialized
|
Checks whether a tree ensemble has been initialized.
|
|
IsBoostedTreesQuantileStreamResourceInitialized
|
Checks whether a quantile stream has been initialized.
|
|
IsVariableInitialized
|
Checks whether a tensor has been initialized.
|
|
IsotonicRegression
<U extends Number>
|
Solves a batch of isotonic regression problems.
|
|
IteratorGetDevice
|
Returns the name of the device on which `resource` has been placed.
|
|
KMC2ChainInitialization
|
Returns the index of a data point that should be added to the seed set.
|
|
KmeansPlusPlusInitialization
|
Selects num_to_sample rows of input using the KMeans++ criterion.
|
|
KthOrderStatistic
|
Computes the Kth order statistic of a data set.
|
|
LMDBDataset
|
Creates a dataset that emits the key-value pairs in one or more LMDB files.
|
|
LSTMBlockCell
<T extends Number>
|
Computes the LSTM cell forward propagation for 1 time step.
|
|
LSTMBlockCellGrad
<T extends Number>
|
Computes the LSTM cell backward propagation for 1 timestep.
|
|
LinSpace
<T extends Number>
|
Generates values in an interval.
|
|
LoadTPUEmbeddingADAMParameters
|
Load ADAM embedding parameters.
|
|
LoadTPUEmbeddingADAMParametersGradAccumDebug
|
Load ADAM embedding parameters with debug support.
|
|
LoadTPUEmbeddingAdadeltaParameters
|
Load Adadelta embedding parameters.
|
|
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug
|
Load Adadelta parameters with debug support.
|
|
LoadTPUEmbeddingAdagradParameters
|
Load Adagrad embedding parameters.
|
|
LoadTPUEmbeddingAdagradParametersGradAccumDebug
|
Load Adagrad embedding parameters with debug support.
|
|
LoadTPUEmbeddingCenteredRMSPropParameters
|
Load centered RMSProp embedding parameters.
|
|
LoadTPUEmbeddingFTRLParameters
|
Load FTRL embedding parameters.
|
|
LoadTPUEmbeddingFTRLParametersGradAccumDebug
|
Load FTRL embedding parameters with debug support.
|
|
LoadTPUEmbeddingFrequencyEstimatorParameters
|
Load frequency estimator embedding parameters.
|
|
LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
|
Load frequency estimator embedding parameters with debug support.
|
|
LoadTPUEmbeddingMDLAdagradLightParameters
|
Load MDL Adagrad Light embedding parameters.
|
|
LoadTPUEmbeddingMomentumParameters
|
Load Momentum embedding parameters.
|
|
LoadTPUEmbeddingMomentumParametersGradAccumDebug
|
Load Momentum embedding parameters with debug support.
|
|
LoadTPUEmbeddingProximalAdagradParameters
|
Load proximal Adagrad embedding parameters.
|
|
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug
|
Load proximal Adagrad embedding parameters with debug support.
|
|
LoadTPUEmbeddingProximalYogiParameters
|
|
|
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug
|
|
|
LoadTPUEmbeddingRMSPropParameters
|
Load RMSProp embedding parameters.
|
|
LoadTPUEmbeddingRMSPropParametersGradAccumDebug
|
Load RMSProp embedding parameters with debug support.
|
|
LoadTPUEmbeddingStochasticGradientDescentParameters
|
Load SGD embedding parameters.
|
|
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
|
Load SGD embedding parameters.
|
|
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.
|
|
Lu
<T, U extends Number>
|
Computes the LU decomposition of one or more square matrices.
|
|
MakeUnique
|
Make all elements in the non-Batch dimension unique, but \"close\" to
their initial value.
|
|
MapClear
|
Op removes all elements in the underlying container.
|
|
MapIncompleteSize
|
Op returns the number of incomplete elements in the underlying container.
|
|
MapPeek
|
Op peeks at the values at the specified key.
|
|
MapSize
|
Op returns the number of elements in the underlying container.
|
|
MapStage
|
Stage (key, values) in the underlying container which behaves like a hashtable.
|
|
MapUnstage
|
Op removes and returns the values associated with the key
from the underlying container.
|
|
MapUnstageNoKey
|
Op removes and returns a random (key, value)
from the underlying container.
|
|
MatrixDiagPartV2
<T>
|
Returns the batched diagonal part of a batched tensor.
|
|
MatrixDiagPartV3
<T>
|
Returns the batched diagonal part of a batched tensor.
|
|
MatrixDiagV2
<T>
|
Returns a batched diagonal tensor with given batched diagonal values.
|
|
MatrixDiagV3
<T>
|
Returns a batched diagonal tensor with given batched diagonal values.
|
|
MatrixSetDiagV2
<T>
|
Returns a batched matrix tensor with new batched diagonal values.
|
|
MatrixSetDiagV3
<T>
|
Returns a batched matrix tensor with new batched diagonal values.
|
|
Max
<T>
|
Computes the maximum of elements across dimensions of a tensor.
|
|
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.
|
|
MirrorPad
<T>
|
Pads a tensor with mirrored values.
|
|
MirrorPadGrad
<T>
|
Gradient op for `MirrorPad` op.
|
|
MlirPassthroughOp
|
Wraps an arbitrary MLIR computation expressed as a module with a main() function.
|
|
MulNoNan
<T>
|
Returns x * y element-wise.
|
|
MutableDenseHashTable
|
Creates an empty hash table that uses tensors as the backing store.
|
|
MutableHashTable
|
Creates an empty hash table.
|
|
MutableHashTableOfTensors
|
Creates an empty hash table.
|
|
Mutex
|
Creates a Mutex resource that can be locked by `MutexLock`.
|
|
MutexLock
|
Locks a mutex resource.
|
|
NcclAllReduce
<T extends Number>
|
Outputs a tensor containing the reduction across all input tensors.
|
|
NcclBroadcast
<T extends Number>
|
Sends `input` to all devices that are connected to the output.
|
|
NcclReduce
<T extends Number>
|
Reduces `input` from `num_devices` using `reduction` to a single device.
|
|
Ndtri
<T extends Number>
|
|
|
NearestNeighbors
|
Selects the k nearest centers for each point.
|
|
NextAfter
<T extends Number>
|
Returns the next representable value of `x1` in the direction of `x2`, element-wise.
|
|
NextIteration
<T>
|
Makes its input available to the next iteration.
|
|
NoOp
|
Does nothing.
|
|
NonDeterministicInts
<U>
|
Non-deterministically generates some integers.
|
|
NonMaxSuppressionV5
<T extends Number>
|
Greedily selects a subset of bounding boxes in descending order of score,
pruning away boxes that have high intersection-over-union (IOU) overlap
with previously selected boxes.
|
|
NonSerializableDataset
|
|
|
OneHot
<U>
|
Returns a one-hot tensor.
|
|
OnesLike
<T>
|
Returns a tensor of ones with the same shape and type as x.
|
|
OptimizeDatasetV2
|
Creates a dataset by applying related optimizations to `input_dataset`.
|
|
OptionsDataset
|
Creates a dataset by attaching tf.data.Options to `input_dataset`.
|
|
OrderedMapClear
|
Op removes all elements in the underlying container.
|
|
OrderedMapIncompleteSize
|
Op returns the number of incomplete elements in the underlying container.
|
|
OrderedMapPeek
|
Op peeks at the values at the specified key.
|
|
OrderedMapSize
|
Op returns the number of elements in the underlying container.
|
|
OrderedMapStage
|
Stage (key, values) in the underlying container which behaves like a ordered
associative container.
|
|
OrderedMapUnstage
|
Op removes and returns the values associated with the key
from the underlying container.
|
|
OrderedMapUnstageNoKey
|
Op removes and returns the (key, value) element with the smallest
key from the underlying container.
|
|
OutfeedDequeue
<T>
|
Retrieves a single tensor from the computation outfeed.
|
|
OutfeedDequeueTuple
|
Retrieve multiple values from the computation outfeed.
|
|
OutfeedDequeueTupleV2
|
Retrieve multiple values from the computation outfeed.
|
|
OutfeedDequeueV2
<T>
|
Retrieves a single tensor from the computation outfeed.
|
|
OutfeedEnqueue
|
Enqueue a Tensor on the computation outfeed.
|
|
OutfeedEnqueueTuple
|
Enqueue multiple Tensor values on the computation outfeed.
|
|
Pad
<T>
|
Pads a tensor.
|
|
ParallelBatchDataset
|
|
|
ParallelConcat
<T>
|
Concatenates a list of `N` tensors along the first dimension.
|
|
ParallelDynamicStitch
<T>
|
Interleave the values from the `data` tensors into a single tensor.
|
|
ParseExampleDatasetV2
|
Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.
|
|
ParseExampleV2
|
Transforms a vector of tf.Example protos (as strings) into typed tensors.
|
|
ParseSequenceExampleV2
|
Transforms a vector of tf.io.SequenceExample protos (as strings) into
typed tensors.
|
|
Placeholder
<T>
|
A placeholder op for a value that will be fed into the computation.
|
|
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.
|
|
PrelinearizeTuple
|
An op which linearizes multiple Tensor values to an opaque variant tensor.
|
|
Print
|
Prints a string scalar.
|
|
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.
|
|
QuantizeAndDequantizeV4
<T extends Number>
|
Quantizes then dequantizes a tensor.
|
|
QuantizeAndDequantizeV4Grad
<T extends Number>
|
Returns the gradient of `QuantizeAndDequantizeV4`.
|
|
QuantizedConcat
<T>
|
Concatenates quantized tensors along one dimension.
|
|
QuantizedConcatV2
<T>
|
|
|
QuantizedConv2DAndRelu
<V>
|
|
|
QuantizedConv2DAndReluAndRequantize
<V>
|
|
|
QuantizedConv2DAndRequantize
<V>
|
|
|
QuantizedConv2DPerChannel
<V>
|
Computes QuantizedConv2D per channel.
|
|
QuantizedConv2DWithBias
<V>
|
|
|
QuantizedConv2DWithBiasAndRelu
<V>
|
|
|
QuantizedConv2DWithBiasAndReluAndRequantize
<W>
|
|
|
QuantizedConv2DWithBiasAndRequantize
<W>
|
|
|
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
<X>
|
|
|
QuantizedConv2DWithBiasSumAndRelu
<V>
|
|
|
QuantizedConv2DWithBiasSumAndReluAndRequantize
<X>
|
|
|
QuantizedDepthwiseConv2D
<V>
|
Computes quantized depthwise Conv2D.
|
|
QuantizedDepthwiseConv2DWithBias
<V>
|
Computes quantized depthwise Conv2D with Bias.
|
|
QuantizedDepthwiseConv2DWithBiasAndRelu
<V>
|
Computes quantized depthwise Conv2D with Bias and Relu.
|
|
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
<W>
|
Computes quantized depthwise Conv2D with Bias, Relu and Requantize.
|
|
QuantizedMatMulWithBias
<W>
|
Performs a quantized matrix multiplication of `a` by the matrix `b` with bias
add.
|
|
QuantizedMatMulWithBiasAndDequantize
<W extends Number>
|
|
|
QuantizedMatMulWithBiasAndRelu
<V>
|
Perform a quantized matrix multiplication of `a` by the matrix `b` with bias
add and relu fusion.
|
|
QuantizedMatMulWithBiasAndReluAndRequantize
<W>
|
Perform a quantized matrix multiplication of `a` by the matrix `b` with bias
add and relu and requantize fusion.
|
|
QuantizedMatMulWithBiasAndRequantize
<W>
|
|
|
QuantizedReshape
<T>
|
Reshapes a quantized tensor as per the Reshape op.
|
|
RaggedBincount
<U extends Number>
|
Counts the number of occurrences of each value in an integer array.
|
|
RaggedCountSparseOutput
<U extends Number>
|
Performs sparse-output bin counting for a ragged tensor input.
|
|
RaggedCross
<T, U extends Number>
|
Generates a feature cross from a list of tensors, and returns it as a
RaggedTensor.
|
|
RaggedGather
<T extends Number, U>
|
Gather ragged slices from `params` axis `0` according to `indices`.
|
|
RaggedRange
<U extends Number, T extends Number>
|
Returns a `RaggedTensor` containing the specified sequences of numbers.
|
|
RaggedTensorFromVariant
<U extends Number, T>
|
Decodes a `variant` Tensor into a `RaggedTensor`.
|
|
RaggedTensorToSparse
<U>
|
Converts a `RaggedTensor` into a `SparseTensor` with the same values.
|
|
RaggedTensorToTensor
<U>
|
Create a dense tensor from a ragged tensor, possibly altering its shape.
|
|
RaggedTensorToVariant
|
Encodes a `RaggedTensor` into a `variant` Tensor.
|
|
RaggedTensorToVariantGradient
<U>
|
Helper used to compute the gradient for `RaggedTensorToVariant`.
|
|
Range
<T extends Number>
|
Creates a sequence of numbers.
|
|
Rank
|
Returns the rank of a tensor.
|
|
ReadVariableOp
<T>
|
Reads the value of a variable.
|
|
RebatchDataset
|
Creates a dataset that changes the batch size.
|
|
RebatchDatasetV2
|
Creates a dataset that changes the batch size.
|
|
Recv
<T>
|
Receives the named tensor from send_device on recv_device.
|
|
RecvTPUEmbeddingActivations
|
An op that receives embedding activations on the TPU.
|
|
ReduceAll
|
Computes the "logical and" of elements across dimensions of a tensor.
|
|
ReduceAny
|
Computes the "logical or" of elements across dimensions of a tensor.
|
|
ReduceMax
<T>
|
Computes the maximum of elements across dimensions of a tensor.
|
|
ReduceMin
<T>
|
Computes the minimum of elements across dimensions of a tensor.
|
|
ReduceProd
<T>
|
Computes the product of elements across dimensions of a tensor.
|
|
ReduceSum
<T>
|
Computes the sum of elements across dimensions of a tensor.
|
|
RefEnter
<T>
|
Creates or finds a child frame, and makes `data` available to the child frame.
|
|
RefExit
<T>
|
Exits the current frame to its parent frame.
|
|
RefIdentity
<T>
|
Return the same ref tensor as the input ref tensor.
|
|
RefMerge
<T>
|
Forwards the value of an available tensor from `inputs` to `output`.
|
|
RefNextIteration
<T>
|
Makes its input available to the next iteration.
|
|
RefSelect
<T>
|
Forwards the `index`th element of `inputs` to `output`.
|
|
RefSwitch
<T>
|
Forwards the ref tensor `data` to the output port determined by `pred`.
|
|
RegisterDataset
|
Registers a dataset with the tf.data service.
|
|
RequantizationRangePerChannel
|
Computes requantization range per channel.
|
|
RequantizePerChannel
<U>
|
Requantizes input with min and max values known per channel.
|
|
Reshape
<T>
|
Reshapes a tensor.
|
|
ResourceAccumulatorApplyGradient
|
Applies a gradient to a given accumulator.
|
|
ResourceAccumulatorNumAccumulated
|
Returns the number of gradients aggregated in the given accumulators.
|
|
ResourceAccumulatorSetGlobalStep
|
Updates the accumulator with a new value for global_step.
|
|
ResourceAccumulatorTakeGradient
<T>
|
Extracts the average gradient in the given ConditionalAccumulator.
|
|
ResourceApplyAdagradV2
|
Update '*var' according to the adagrad scheme.
|
|
ResourceApplyAdamWithAmsgrad
|
Update '*var' according to the Adam algorithm.
|
|
ResourceApplyKerasMomentum
|
Update '*var' according to the momentum scheme.
|
|
ResourceConditionalAccumulator
|
A conditional accumulator for aggregating gradients.
|
|
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`.
|
|
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.
|
|
ResourceScatterNdMax
|
|
|
ResourceScatterNdMin
|
|
|
ResourceScatterNdSub
|
Applies sparse subtraction to individual values or slices in a Variable.
|
|
ResourceScatterNdUpdate
|
Applies sparse `updates` to individual values or slices within a given
variable according to `indices`.
|
|
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.
|
|
ResourceSparseApplyKerasMomentum
|
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
|
|
ResourceStridedSliceAssign
|
Assign `value` to the sliced l-value reference of `ref`.
|
|
RetrieveTPUEmbeddingADAMParameters
|
Retrieve ADAM embedding parameters.
|
|
RetrieveTPUEmbeddingADAMParametersGradAccumDebug
|
Retrieve ADAM embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingAdadeltaParameters
|
Retrieve Adadelta embedding parameters.
|
|
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug
|
Retrieve Adadelta embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingAdagradParameters
|
Retrieve Adagrad embedding parameters.
|
|
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug
|
Retrieve Adagrad embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingCenteredRMSPropParameters
|
Retrieve centered RMSProp embedding parameters.
|
|
RetrieveTPUEmbeddingFTRLParameters
|
Retrieve FTRL embedding parameters.
|
|
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug
|
Retrieve FTRL embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingFrequencyEstimatorParameters
|
Retrieve frequency estimator embedding parameters.
|
|
RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
|
Retrieve frequency estimator embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingMDLAdagradLightParameters
|
Retrieve MDL Adagrad Light embedding parameters.
|
|
RetrieveTPUEmbeddingMomentumParameters
|
Retrieve Momentum embedding parameters.
|
|
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug
|
Retrieve Momentum embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingProximalAdagradParameters
|
Retrieve proximal Adagrad embedding parameters.
|
|
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug
|
Retrieve proximal Adagrad embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingProximalYogiParameters
|
|
|
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug
|
|
|
RetrieveTPUEmbeddingRMSPropParameters
|
Retrieve RMSProp embedding parameters.
|
|
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug
|
Retrieve RMSProp embedding parameters with debug support.
|
|
RetrieveTPUEmbeddingStochasticGradientDescentParameters
|
Retrieve SGD embedding parameters.
|
|
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
|
Retrieve SGD embedding parameters with debug support.
|
|
Reverse
<T>
|
Reverses specific dimensions of a tensor.
|
|
ReverseSequence
<T>
|
Reverses variable length slices.
|
|
RiscAbs
<T extends Number>
|
|
|
RiscAdd
<T extends Number>
|
Returns x + y element-wise.
|
|
RiscBinaryArithmetic
<T extends Number>
|
|
|
RiscBinaryComparison
|
|
|
RiscBitcast
<U>
|
|
|
RiscBroadcast
<T>
|
|
|
RiscCast
<U>
|
|
|
RiscCeil
<T extends Number>
|
|
|
RiscCholesky
<T extends Number>
|
|
|
RiscConcat
<T>
|
|
|
RiscConv
<T extends Number>
|
|
|
RiscCos
<T extends Number>
|
|
|
RiscDiv
<T extends Number>
|
|
|
RiscDot
<T extends Number>
|
|
|
RiscExp
<T extends Number>
|
|
|
RiscFft
<T>
|
|
|
RiscFloor
<T extends Number>
|
|
|
RiscGather
<T>
|
|
|
RiscImag
<U extends Number>
|
|
|
RiscIsFinite
|
|
|
RiscLog
<T extends Number>
|
|
|
RiscLogicalAnd
|
|
|
RiscLogicalNot
|
|
|
RiscLogicalOr
|
|
|
RiscMax
<T extends Number>
|
Returns max(x, y) element-wise.
|
|
RiscMin
<T extends Number>
|
|
|
RiscMul
<T extends Number>
|
|
|
RiscNeg
<T extends Number>
|
|
|
RiscPad
<T extends Number>
|
|
|
RiscPool
<T extends Number>
|
|
|
RiscPow
<T extends Number>
|
|
|
RiscRandomUniform
|
|
|
RiscReal
<U extends Number>
|
|
|
RiscReduce
<T extends Number>
|
|
|
RiscRem
<T extends Number>
|
|
|
RiscReshape
<T extends Number>
|
|
|
RiscReverse
<T extends Number>
|
|
|
RiscScatter
<U extends Number>
|
|
|
RiscShape
<U extends Number>
|
|
|
RiscSign
<T extends Number>
|
|
|
RiscSlice
<T extends Number>
|
|
|
RiscSort
<T extends Number>
|
|
|
RiscSqueeze
<T>
|
|
|
RiscSub
<T extends Number>
|
|
|
RiscTranspose
<T>
|
|
|
RiscTriangularSolve
<T extends Number>
|
|
|
RiscUnary
<T extends Number>
|
|
|
RngReadAndSkip
|
Advance the counter of a counter-based RNG.
|
|
RngSkip
|
Advance the counter of a counter-based RNG.
|
|
Roll
<T>
|
Rolls the elements of a tensor along an axis.
|
|
SamplingDataset
|
Creates a dataset that takes a Bernoulli sample of the contents of another dataset.
|
|
ScaleAndTranslate
|
|
|
ScaleAndTranslateGrad
<T extends Number>
|
|
|
ScatterAdd
<T>
|
Adds sparse updates to a variable reference.
|
|
ScatterDiv
<T>
|
Divides a variable reference by sparse updates.
|
|
ScatterMax
<T extends Number>
|
Reduces sparse updates into a variable reference using the `max` operation.
|
|
ScatterMin
<T extends Number>
|
Reduces sparse updates into a variable reference using the `min` operation.
|
|
ScatterMul
<T>
|
Multiplies sparse updates into a variable reference.
|
|
ScatterNd
<U>
|
Scatter `updates` into a new tensor according to `indices`.
|
|
ScatterNdAdd
<T>
|
Applies sparse addition to individual values or slices in a Variable.
|
|
ScatterNdMax
<T>
|
Computes element-wise maximum.
|
|
ScatterNdMin
<T>
|
Computes element-wise minimum.
|
|
ScatterNdNonAliasingAdd
<T>
|
Applies sparse addition to `input` using individual values or slices
from `updates` according to indices `indices`.
|
|
ScatterNdSub
<T>
|
Applies sparse subtraction to individual values or slices in a Variable.
|
|
ScatterNdUpdate
<T>
|
Applies sparse `updates` to individual values or slices within a given
variable according to `indices`.
|
|
ScatterSub
<T>
|
Subtracts sparse updates to a variable reference.
|
|
ScatterUpdate
<T>
|
Applies sparse updates to a variable reference.
|
|
SelectV2
<T>
|
|
|
Send
|
Sends the named tensor from send_device to recv_device.
|
|
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`.
|
|
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.
|
|
ShuffleAndRepeatDatasetV2
|
|
|
ShuffleDatasetV2
|
|
|
ShuffleDatasetV3
|
|
|
ShutdownDistributedTPU
|
Shuts down a running distributed TPU system.
|
|
Size
<U extends Number>
|
Returns the size of a tensor.
|
|
Skipgram
|
Parses a text file and creates a batch of examples.
|
|
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.
|
|
SnapshotDatasetReader
|
|
|
SnapshotNestedDatasetReader
|
|
|
SobolSample
<T extends Number>
|
Generates points from the Sobol sequence.
|
|
SpaceToBatchNd
<T>
|
SpaceToBatch for N-D tensors of type T.
|
|
SparseApplyAdagradV2
<T>
|
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
|
|
SparseBincount
<U extends Number>
|
Counts the number of occurrences of each value in an integer array.
|
|
SparseCountSparseOutput
<U extends Number>
|
Performs sparse-output bin counting for a sparse tensor input.
|
|
SparseCrossHashed
|
Generates sparse cross from a list of sparse and dense tensors.
|
|
SparseCrossV2
|
Generates sparse cross from a list of sparse and dense tensors.
|
|
SparseMatrixAdd
|
Sparse addition of two CSR matrices, C = alpha * A + beta * B.
|
|
SparseMatrixMatMul
<T>
|
Matrix-multiplies a sparse matrix with a dense matrix.
|
|
SparseMatrixMul
|
Element-wise multiplication of a sparse matrix with a dense tensor.
|
|
SparseMatrixNNZ
|
Returns the number of nonzeroes of `sparse_matrix`.
|
|
SparseMatrixOrderingAMD
|
Computes the Approximate Minimum Degree (AMD) ordering of `input`.
|
|
SparseMatrixSoftmax
|
Calculates the softmax of a CSRSparseMatrix.
|
|
SparseMatrixSoftmaxGrad
|
Calculates the gradient of the SparseMatrixSoftmax op.
|
|
SparseMatrixSparseCholesky
|
Computes the sparse Cholesky decomposition of `input`.
|
|
SparseMatrixSparseMatMul
|
Sparse-matrix-multiplies two CSR matrices `a` and `b`.
|
|
SparseMatrixTranspose
|
Transposes the inner (matrix) dimensions of a CSRSparseMatrix.
|
|
SparseMatrixZeros
|
Creates an all-zeros CSRSparseMatrix with shape `dense_shape`.
|
|
SparseSegmentSumGrad
<T extends Number>
|
Computes gradients for SparseSegmentSum.
|
|
SparseTensorToCSRSparseMatrix
|
Converts a SparseTensor to a (possibly batched) CSRSparseMatrix.
|
|
Spence
<T extends Number>
|
|
|
Split
<T>
|
Splits a tensor into `num_split` tensors along one dimension.
|
|
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.
|
|
Stack
<T>
|
Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.
|
|
Stage
|
Stage values similar to a lightweight Enqueue.
|
|
StageClear
|
Op removes all elements in the underlying container.
|
|
StagePeek
|
Op peeks at the values at the specified index.
|
|
StageSize
|
Op returns the number of elements in the underlying container.
|
|
StatefulRandomBinomial
<V extends Number>
|
|
|
StatefulStandardNormal
<U>
|
Outputs random values from a normal distribution.
|
|
StatefulStandardNormalV2
<U>
|
Outputs random values from a normal distribution.
|
|
StatefulTruncatedNormal
<U>
|
Outputs random values from a truncated normal distribution.
|
|
StatefulUniform
<U>
|
Outputs random values from a uniform distribution.
|
|
StatefulUniformFullInt
<U>
|
Outputs random integers from a uniform distribution.
|
|
StatefulUniformInt
<U>
|
Outputs random integers from a uniform distribution.
|
|
StatelessParameterizedTruncatedNormal
<V extends Number>
|
|
|
StatelessRandomBinomial
<W extends Number>
|
Outputs deterministic pseudorandom random numbers from a binomial distribution.
|
|
StatelessRandomGammaV2
<V extends Number>
|
Outputs deterministic pseudorandom random numbers from a gamma distribution.
|
|
StatelessRandomGetAlg
|
Picks the best counter-based RNG algorithm based on device.
|
|
StatelessRandomGetKeyCounter
|
Scrambles seed into key and counter, using the best algorithm based on device.
|
|
StatelessRandomGetKeyCounterAlg
|
Picks the best algorithm based on device, and scrambles seed into key and counter.
|
|
StatelessRandomNormalV2
<U extends Number>
|
Outputs deterministic pseudorandom values from a normal distribution.
|
|
StatelessRandomPoisson
<W extends Number>
|
Outputs deterministic pseudorandom random numbers from a Poisson distribution.
|
|
StatelessRandomUniformFullInt
<V extends Number>
|
Outputs deterministic pseudorandom random integers from a uniform distribution.
|
|
StatelessRandomUniformFullIntV2
<U extends Number>
|
Outputs deterministic pseudorandom random integers from a uniform distribution.
|
|
StatelessRandomUniformIntV2
<U extends Number>
|
Outputs deterministic pseudorandom random integers from a uniform distribution.
|
|
StatelessRandomUniformV2
<U extends Number>
|
Outputs deterministic pseudorandom random values from a uniform distribution.
|
|
StatelessSampleDistortedBoundingBox
<T extends Number>
|
Generate a randomly distorted bounding box for an image deterministically.
|
|
StatelessTruncatedNormalV2
<U extends Number>
|
Outputs deterministic pseudorandom values from a truncated normal distribution.
|
|
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`.
|
|
StridedSliceAssign
<T>
|
Assign `value` to the sliced l-value reference of `ref`.
|
|
StridedSliceGrad
<U>
|
Returns the gradient of `StridedSlice`.
|
|
StringLower
|
Converts all uppercase characters into their respective lowercase replacements.
|
|
StringNGrams
<T extends Number>
|
Creates ngrams from ragged string data.
|
|
StringUpper
|
Converts all lowercase characters into their respective uppercase replacements.
|
|
Sum
<T>
|
Computes the sum of elements across dimensions of a tensor.
|
|
SwitchCond
<T>
|
Forwards `data` to the output port determined by `pred`.
|
|
TPUCompilationResult
|
Returns the result of a TPU compilation.
|
|
TPUCompileSucceededAssert
|
Asserts that compilation succeeded.
|
|
TPUEmbeddingActivations
|
An op enabling differentiation of TPU Embeddings.
|
|
TPUExecute
|
Op that loads and executes a TPU program on a TPU device.
|
|
TPUExecuteAndUpdateVariables
|
Op that executes a program with optional in-place variable updates.
|
|
TPUOrdinalSelector
|
A TPU core selector Op.
|
|
TPUPartitionedInput
<T>
|
An op that groups a list of partitioned inputs together.
|
|
TPUPartitionedOutput
<T>
|
An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned
outputs outside the XLA computation.
|
|
TPUReplicateMetadata
|
Metadata indicating how the TPU computation should be replicated.
|
|
TPUReplicatedInput
<T>
|
Connects N inputs to an N-way replicated TPU computation.
|
|
TPUReplicatedOutput
<T>
|
Connects N outputs from an N-way replicated TPU computation.
|
|
TPUReshardVariables
|
Op that reshards on-device TPU variables to specified state.
|
|
TemporaryVariable
<T>
|
Returns a tensor that may be mutated, but only persists within a single step.
|
|
TensorArray
|
An array of Tensors of given size.
|
|
TensorArrayClose
|
Delete the TensorArray from its resource container.
|
|
TensorArrayConcat
<T>
|
Concat the elements from the TensorArray into value `value`.
|
|
TensorArrayGather
<T>
|
Gather specific elements from the TensorArray into output `value`.
|
|
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>
|
|
|
TensorArrayRead
<T>
|
Read an element from the TensorArray into output `value`.
|
|
TensorArrayScatter
|
Scatter the data from the input value into specific TensorArray elements.
|
|
TensorArraySize
|
Get the current size of the TensorArray.
|
|
TensorArraySplit
|
Split the data from the input value into TensorArray elements.
|
|
TensorArrayUnpack
|
|
|
TensorArrayWrite
|
Push an element onto the tensor_array.
|
|
TensorListConcat
<T>
|
Concats all tensors in the list along the 0th dimension.
|
|
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.
|
|
TensorMapErase
|
Returns a tensor map with item from given key erased.
|
|
TensorMapHasKey
|
Returns whether the given key exists in the map.
|
|
TensorMapInsert
|
Returns a map that is the 'input_handle' with the given key-value pair inserted.
|
|
TensorMapLookup
<U>
|
Returns the value from a given key in a tensor map.
|
|
TensorMapSize
|
Returns the number of tensors in the input tensor map.
|
|
TensorMapStackKeys
<T>
|
Returns a Tensor stack of all keys in a tensor map.
|
|
TensorScatterAdd
<T>
|
Adds sparse `updates` to an existing tensor according to `indices`.
|
|
TensorScatterMax
<T>
|
|
|
TensorScatterMin
<T>
|
|
|
TensorScatterSub
<T>
|
Subtracts sparse `updates` from an existing tensor according to `indices`.
|
|
TensorScatterUpdate
<T>
|
Scatter `updates` into an existing tensor according to `indices`.
|
|
TensorStridedSliceUpdate
<T>
|
Assign `value` to the sliced l-value reference of `input`.
|
|
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`.
|
|
Tile
<T>
|
Constructs a tensor by tiling a given tensor.
|
|
Timestamp
|
Provides the time since epoch in seconds.
|
|
ToBool
|
Converts a tensor to a scalar predicate.
|
|
TopKUnique
|
Returns the TopK unique values in the array in sorted order.
|
|
TopKWithUnique
|
Returns the TopK values in the array in sorted order.
|
|
TridiagonalMatMul
<T>
|
Calculate product with tridiagonal matrix.
|
|
TridiagonalSolve
<T>
|
Solves tridiagonal systems of equations.
|
|
Unbatch
<T>
|
Reverses the operation of Batch for a single output Tensor.
|
|
UnbatchGrad
<T>
|
Gradient of Unbatch.
|
|
UncompressElement
|
Uncompresses a compressed dataset element.
|
|
UnicodeDecode
<T extends Number>
|
Decodes each string in `input` into a sequence of Unicode code points.
|
|
UnicodeEncode
|
Encode a tensor of ints into unicode strings.
|
|
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`.
|
|
Unstack
<T>
|
Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors.
|
|
Unstage
|
Op is similar to a lightweight Dequeue.
|
|
UnwrapDatasetVariant
|
|
|
UpperBound
<U extends Number>
|
Applies upper_bound(sorted_search_values, values) along each row.
|
|
VarHandleOp
|
Creates a handle to a Variable resource.
|
|
VarIsInitializedOp
|
Checks whether a resource handle-based variable has been initialized.
|
|
Variable
<T>
|
Holds state in the form of a tensor that persists across steps.
|
|
VariableShape
<T extends Number>
|
Returns the shape of the variable pointed to by `resource`.
|
|
Where
|
Returns locations of nonzero / true values in a tensor.
|
|
Where3
<T>
|
Selects elements from `x` or `y`, depending on `condition`.
|
|
Window
|
|
|
WorkerHeartbeat
|
Worker heartbeat op.
|
|
WrapDatasetVariant
|
|
|
WriteRawProtoSummary
|
Writes a serialized proto summary.
|
|
XlaRecvFromHost
<T>
|
An op to receive a tensor from the host.
|
|
XlaSendToHost
|
An op to send a tensor to the host.
|
|
Xlog1py
<T>
|
Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise.
|
|
ZerosLike
<T>
|
Returns a tensor of zeros with the same shape and type as x.
|
