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 ND 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> | מפחית באופן הדדי מספר טנסורים מסוג וצורה זהים ומפזר את התוצאה. |
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 wrt x s, ie, 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 wrt |
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> | מחשב את המקסימום לאורך מקטעים של טנזור. |
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 ND 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 'input_handle' with the given key-value pair inserted. |
TensorMapLookup <U> | Returns the value from a given key in a tensor map. |
TensorMapSize | Returns the number of tensors in the input tensor map. |
TensorMapStackKeys <T> | Returns a Tensor stack of all keys in a tensor map. |
TensorScatterAdd <T> | Adds sparse `updates` to an existing tensor according to `indices`. |
TensorScatterMax <T> | Apply a sparse update to a tensor taking the element-wise maximum. |
TensorScatterMin <T> | |
TensorScatterSub <T> | Subtracts sparse `updates` from an existing tensor according to `indices`. |
TensorScatterUpdate <T> | Scatter `updates` into an existing tensor according to `indices`. |
TensorStridedSliceUpdate <T> | Assign `value` to the sliced l-value reference of `input`. |
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. |
TpuHandleToProtoKey | Converts XRT's uid handles to TensorFlow-friendly input format. |
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. |
UniformDequantize <U extends Number> | Perform dequantization on the quantized Tensor `input`. |
UniformQuantize <U> | Perform quantization on Tensor `input`. |
UniformQuantizedAdd <T> | Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
UniformQuantizedClipByValue <T> | Perform clip by value on the quantized Tensor `operand`. |
UniformQuantizedConvolution <U> | Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`. |
UniformQuantizedConvolutionHybrid <V extends Number> | Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`. |
UniformQuantizedDot <U> | Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
UniformQuantizedDotHybrid <V extends Number> | Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`. |
UniformRequantize <U> | Given quantized tensor `input`, requantize it with new quantization parameters. |
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 | |
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`. |
WindowOp | |
WorkerHeartbeat | Worker heartbeat op. |
WrapDatasetVariant | |
WriteRawProtoSummary | Writes a serialized proto summary. |
XlaConcatND <T> | Concats input tensor across all dimensions. |
XlaRecvFromHost <T> | An op to receive a tensor from the host. |
XlaRecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
XlaRecvTPUEmbeddingDeduplicationData | Receives deduplication data (indices and weights) from the embedding core. |
XlaSendTPUEmbeddingGradients | An op that performs gradient updates of embedding tables. |
XlaSendToHost | An op to send a tensor to the host. |
XlaSplitND <T> | Splits input tensor across all dimensions. |
Xlog1py <T> | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
Zeros <T> | An operator creating a constant initialized with zeros of the shape given by `dims`. |
ZerosLike <T> | Returns a tensor of zeros with the same shape and type as x. |