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. |
AnonymousHashTable |
Creates a uninitialized anonymous hash table. |
AnonymousIteratorV2 |
A container for an iterator resource. |
AnonymousIteratorV3 |
A container for an iterator resource. |
AnonymousMemoryCache |
|
AnonymousMultiDeviceIterator |
A container for a multi device iterator resource. |
AnonymousMultiDeviceIteratorV3 |
A container for a multi device iterator resource. |
AnonymousMutableDenseHashTable |
Creates an empty anonymous mutable hash table that uses tensors as the backing store. |
AnonymousMutableHashTable |
Creates an empty anonymous mutable hash table. |
AnonymousMutableHashTableOfTensors |
Creates an empty anonymous mutable hash table of vector values. |
AnonymousRandomSeedGenerator |
|
AnonymousSeedGenerator |
|
Any |
Computes the "logical or" of elements across dimensions of a tensor. |
ApplyAdagradV2<T> |
Update '*var' according to the adagrad scheme. |
ApproxTopK<T extends Number> |
Returns min/max k values and their indices of the input operand in an approximate manner. |
AssertCardinalityDataset |
|
AssertNextDataset |
A transformation that asserts which transformations happen next. |
AssertPrevDataset |
A transformation that asserts which transformations happened previously. |
AssertThat |
Asserts that the given condition is true. |
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. |
AssignVariableXlaConcatND |
Concats input tensor across all dimensions. |
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. |
CollateTPUEmbeddingMemory |
An op that merges the string-encoded memory config protos from all hosts. |
CollectiveAllToAllV2<T extends Number> |
Mutually exchanges multiple tensors of identical type and shape. |
CollectiveAllToAllV3<T extends Number> |
Mutually exchanges multiple tensors of identical type and shape. |
CollectiveAssignGroupV2 |
Assign group keys based on group assignment. |
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. |
CollectiveInitializeCommunicator |
Initializes a group for collective operations. |
CollectivePermute<T> |
An Op to permute tensors across replicated TPU instances. |
CollectiveReduceScatterV2<T extends Number> |
Mutually reduces multiple tensors of identical type and shape and scatters the result. |
CollectiveReduceV2<T extends Number> |
Mutually reduces multiple tensors of identical type and shape. |
CollectiveReduceV3<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. |
ComputeDedupDataTupleMask |
An op computes tuple mask of deduplication data from embedding core. |
Concat<T> |
Concatenates tensors along one dimension. |
ConfigureAndInitializeGlobalTPU |
An op that sets up the centralized structures for a distributed TPU system. |
ConfigureDistributedTPU |
Sets up the centralized structures for a distributed TPU system. |
ConfigureTPUEmbedding |
Sets up TPUEmbedding in a distributed TPU system. |
ConfigureTPUEmbeddingHost |
An op that configures the TPUEmbedding software on a host. |
ConfigureTPUEmbeddingMemory |
An op that configures the TPUEmbedding software on a host. |
ConnectTPUEmbeddingHosts |
An op that sets up communication between TPUEmbedding host software instances
after ConfigureTPUEmbeddingHost has been called on each host. |
Constant<T> |
An operator producing a constant value. |
ConsumeMutexLock |
This op consumes a lock created by `MutexLock`. |
ControlTrigger |
Does nothing. |
Conv2DBackpropFilterV2<T extends Number> |
Computes the gradients of convolution with respect to the filter. |
Conv2DBackpropInputV2<T extends Number> |
Computes the gradients of convolution with respect to the input. |
Copy<T> |
Copy a tensor from CPU-to-CPU or GPU-to-GPU. |
CopyHost<T> |
Copy a tensor to host. |
CopyToMesh<T> |
|
CopyToMeshGrad<T> |
|
CountUpTo<T extends Number> |
Increments 'ref' until it reaches 'limit'. |
CrossReplicaSum<T extends Number> |
An Op to sum inputs across replicated TPU instances. |
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`. |
DTensorRestoreV2 |
|
DTensorSetGlobalTPUArray |
An op that informs a host of the global ids of all the of TPUs in the system. |
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. |
DisableCopyOnRead |
Turns off the copy-on-read mode. |
DistributedSave |
|
DrawBoundingBoxesV2<T extends Number> |
Draw bounding boxes on a batch of images. |
DummyIterationCounter |
|
DummyMemoryCache |
|
DummySeedGenerator |
|
DynamicEnqueueTPUEmbeddingArbitraryTensorBatch |
Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
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. |
EnqueueTPUEmbeddingArbitraryTensorBatch |
Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
EnqueueTPUEmbeddingBatch |
An op that enqueues a list of input batch tensors to TPUEmbedding. |
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. |
ExecuteTPUEmbeddingPartitioner |
An op that executes the TPUEmbedding partitioner on the central configuration
device and computes the HBM size (in bytes) required for TPUEmbedding operation. |
Exit<T> |
Exits the current frame to its parent frame. |
ExpandDims<T> |
Inserts a dimension of 1 into a tensor's shape. |
ExperimentalAutoShardDataset |
Creates a dataset that shards the input dataset. |
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. |
FileSystemSetConfiguration |
Set configuration of the file system. |
Fill<U> |
Creates a tensor filled with a scalar value. |
FinalizeDataset |
Creates a dataset by applying tf.data.Options to `input_dataset`. |
FinalizeTPUEmbedding |
An op that finalizes the TPUEmbedding configuration. |
Fingerprint |
Generates fingerprint values. |
FresnelCos<T extends Number> |
|
FresnelSin<T extends Number> |
|
FusedBatchNormGradV3<T extends Number, U extends Number> |
Gradient for batch normalization. |
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`. |
GetElementAtIndex |
Gets the element at the specified index in a dataset. |
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. |
Gradients |
Adds operations to compute the partial derivatives of sum of y s w.r.t x s,
i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2...
If Options.dx() values are set, they are as the initial symbolic partial derivatives of some loss
function L w.r.t. |
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. |
IsTPUEmbeddingInitialized |
Whether TPU Embedding is initialized in a distributed TPU system. |
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. |
ListDataset |
Creates a dataset that emits each of `tensors` once. |
LoadAllTPUEmbeddingParameters |
An op that loads optimization parameters into embedding memory. |
LoadTPUEmbeddingADAMParameters |
Load ADAM embedding parameters. |
LoadTPUEmbeddingAdadeltaParameters |
Load Adadelta embedding parameters. |
LoadTPUEmbeddingAdagradMomentumParameters |
Load Adagrad Momentum embedding parameters. |
LoadTPUEmbeddingAdagradParameters |
Load Adagrad embedding parameters. |
LoadTPUEmbeddingCenteredRMSPropParameters |
Load centered RMSProp embedding parameters. |
LoadTPUEmbeddingFTRLParameters |
Load FTRL embedding parameters. |
LoadTPUEmbeddingFrequencyEstimatorParameters |
Load frequency estimator embedding parameters. |
LoadTPUEmbeddingMDLAdagradLightParameters |
Load MDL Adagrad Light embedding parameters. |
LoadTPUEmbeddingMomentumParameters |
Load Momentum embedding parameters. |
LoadTPUEmbeddingProximalAdagradParameters |
Load proximal Adagrad embedding parameters. |
LoadTPUEmbeddingProximalYogiParameters |
|
LoadTPUEmbeddingRMSPropParameters |
Load RMSProp embedding parameters. |
LoadTPUEmbeddingStochasticGradientDescentParameters |
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`. |
MergeDedupData |
An op merges elements of integer and float tensors into deduplication data as
XLA tuple. |
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. |
PrimitiveOp |
A base class for Op implementations that are backed by a single Operation . |
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. |
RaggedFillEmptyRows<T> |
|
RaggedFillEmptyRowsGrad<T> |
|
RaggedGather<T extends Number, U> |
Gather ragged slices from `params` axis `0` according to `indices`. |
RaggedRange<U extends Number, T extends Number> |
Returns a `RaggedTensor` containing the specified sequences of numbers. |
RaggedTensorFromVariant<U extends Number, T> |
Decodes a `variant` Tensor into a `RaggedTensor`. |
RaggedTensorToSparse<U> |
Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
RaggedTensorToTensor<U> |
Create a dense tensor from a ragged tensor, possibly altering its shape. |
RaggedTensorToVariant |
Encodes a `RaggedTensor` into a `variant` Tensor. |
RaggedTensorToVariantGradient<U> |
Helper used to compute the gradient for `RaggedTensorToVariant`. |
RandomDatasetV2 |
Creates a Dataset that returns pseudorandom numbers. |
RandomIndexShuffle<T extends Number> |
Outputs the position of `value` in a permutation of [0, ..., max_index]. |
Range<T extends Number> |
Creates a sequence of numbers. |
Rank |
Returns the rank of a tensor. |
ReadVariableOp<T> |
Reads the value of a variable. |
ReadVariableXlaSplitND<T> |
Splits resource variable input tensor across all dimensions. |
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. |
RegisterDatasetV2 |
Registers a dataset with the tf.data service. |
Relayout<T> |
|
RelayoutGrad<T> |
|
RequantizationRangePerChannel |
Computes requantization range per channel. |
RequantizePerChannel<U> |
Requantizes input with min and max values known per channel. |
Reshape<T> |
Reshapes a tensor. |
ResourceAccumulatorApplyGradient |
Applies a gradient to a given accumulator. |
ResourceAccumulatorNumAccumulated |
Returns the number of gradients aggregated in the given accumulators. |
ResourceAccumulatorSetGlobalStep |
Updates the accumulator with a new value for global_step. |
ResourceAccumulatorTakeGradient<T> |
Extracts the average gradient in the given ConditionalAccumulator. |
ResourceApplyAdagradV2 |
Update '*var' according to the adagrad scheme. |
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`. |
RetrieveAllTPUEmbeddingParameters |
An op that retrieves optimization parameters from embedding to host memory. |
RetrieveTPUEmbeddingADAMParameters |
Retrieve ADAM embedding parameters. |
RetrieveTPUEmbeddingAdadeltaParameters |
Retrieve Adadelta embedding parameters. |
RetrieveTPUEmbeddingAdagradMomentumParameters |
Retrieve Adagrad Momentum embedding parameters. |
RetrieveTPUEmbeddingAdagradParameters |
Retrieve Adagrad embedding parameters. |
RetrieveTPUEmbeddingCenteredRMSPropParameters |
Retrieve centered RMSProp embedding parameters. |
RetrieveTPUEmbeddingFTRLParameters |
Retrieve FTRL embedding parameters. |
RetrieveTPUEmbeddingFrequencyEstimatorParameters |
Retrieve frequency estimator embedding parameters. |
RetrieveTPUEmbeddingMDLAdagradLightParameters |
Retrieve MDL Adagrad Light embedding parameters. |
RetrieveTPUEmbeddingMomentumParameters |
Retrieve Momentum embedding parameters. |
RetrieveTPUEmbeddingProximalAdagradParameters |
Retrieve proximal Adagrad embedding parameters. |
RetrieveTPUEmbeddingProximalYogiParameters |
|
RetrieveTPUEmbeddingRMSPropParameters |
Retrieve RMSProp embedding parameters. |
RetrieveTPUEmbeddingStochasticGradientDescentParameters |
Retrieve SGD embedding parameters. |
Reverse<T> |
Reverses specific dimensions of a tensor. |
ReverseSequence<T> |
Reverses variable length slices. |
RewriteDataset |
|
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> |
Scatters `updates` into a tensor of shape `shape` 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. |
SegmentMaxV2<T extends Number> |
Computes the maximum along segments of a tensor. |
SegmentMinV2<T extends Number> |
Computes the minimum along segments of a tensor. |
SegmentProdV2<T> |
Computes the product along segments of a tensor. |
SegmentSumV2<T> |
Computes the sum along segments of a tensor. |
SelectV2<T> |
|
Send |
Sends the named tensor from send_device to recv_device. |
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. |
ShutdownTPUSystem |
An op that shuts down the TPU system. |
Size<U extends Number> |
Returns the size of a tensor. |
Skipgram |
Parses a text file and creates a batch of examples. |
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. |
SplitDedupData<T extends Number, U extends Number> |
An op splits input deduplication data XLA tuple into integer and floating point
tensors. |
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. |
StatelessRandomGammaV3<U extends Number> |
Outputs deterministic pseudorandom random numbers from a gamma distribution. |
StatelessRandomGetAlg |
Picks the best counter-based RNG algorithm based on device. |
StatelessRandomGetKeyCounter |
Scrambles seed into key and counter, using the best algorithm based on device. |
StatelessRandomGetKeyCounterAlg |
Picks the best algorithm based on device, and scrambles seed into key and counter. |
StatelessRandomNormalV2<U extends Number> |
Outputs deterministic pseudorandom values from a normal distribution. |
StatelessRandomPoisson<W extends Number> |
Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
StatelessRandomUniformFullInt<V extends Number> |
Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformFullIntV2<U extends Number> |
Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformIntV2<U extends Number> |
Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformV2<U extends Number> |
Outputs deterministic pseudorandom random values from a uniform distribution. |
StatelessSampleDistortedBoundingBox<T extends Number> |
Generate a randomly distorted bounding box for an image deterministically. |
StatelessShuffle<T> |
Randomly and deterministically shuffles a tensor along its first dimension. |
StatelessTruncatedNormalV2<U extends Number> |
Outputs deterministic pseudorandom values from a truncated normal distribution. |
StatsAggregatorHandleV2 |
|
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`. |
SyncDevice |
Synchronizes the device this op is run on. |
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. |
TPUPartitionedInputV2<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. |
TPUPartitionedOutputV2<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. |
TPURoundRobin |
Round-robin load balancing on TPU cores. |
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 |