Classes
Abort | Raise a exception to abort the process when called. |
Abort.Options |
Optional attributes for
Abort
|
All | Computes the "logical and" of elements across dimensions of a tensor. |
All.Options |
Optional attributes for
All
|
AllToAll <T> | An Op to exchange data across TPU replicas. |
AnonymousIteratorV2 | A container for an iterator resource. |
AnonymousMemoryCache | |
AnonymousMultiDeviceIterator | A container for a multi device iterator resource. |
AnonymousRandomSeedGenerator | |
AnonymousSeedGenerator | |
Any | Computes the "logical or" of elements across dimensions of a tensor. |
Any.Options |
Optional attributes for
Any
|
ApplyAdagradV2 <T> | Update '*var' according to the adagrad scheme. |
ApplyAdagradV2.Options |
Optional attributes for
ApplyAdagradV2
|
AssertCardinalityDataset | |
AssertNextDataset | A transformation that asserts which transformations happen next. |
AssertThat | Asserts that the given condition is true. |
AssertThat.Options |
Optional attributes for
AssertThat
|
Assign <T> | Update 'ref' by assigning 'value' to it. |
Assign.Options |
Optional attributes for
Assign
|
AssignAdd <T> | Update 'ref' by adding 'value' to it. |
AssignAdd.Options |
Optional attributes for
AssignAdd
|
AssignAddVariableOp | Adds a value to the current value of a variable. |
AssignSub <T> | Update 'ref' by subtracting 'value' from it. |
AssignSub.Options |
Optional attributes for
AssignSub
|
AssignSubVariableOp | Subtracts a value from the current value of a variable. |
AssignVariableOp | Assigns a new value to a variable. |
AutoShardDataset | Creates a dataset that shards the input dataset. |
AutoShardDataset.Options |
Optional attributes for
AutoShardDataset
|
BandedTriangularSolve <T> | |
BandedTriangularSolve.Options |
Optional attributes for
BandedTriangularSolve
|
Barrier | Defines a barrier that persists across different graph executions. |
Barrier.Options |
Optional attributes for
Barrier
|
BarrierClose | Closes the given barrier. |
BarrierClose.Options |
Optional attributes for
BarrierClose
|
BarrierIncompleteSize | Computes the number of incomplete elements in the given barrier. |
BarrierInsertMany | For each key, assigns the respective value to the specified component. |
BarrierReadySize | Computes the number of complete elements in the given barrier. |
BarrierTakeMany | Takes the given number of completed elements from a barrier. |
BarrierTakeMany.Options |
Optional attributes for
BarrierTakeMany
|
Batch | Batches all input tensors nondeterministically. |
Batch.Options |
Optional attributes for
Batch
|
BatchMatMulV2 <T> | Multiplies slices of two tensors in batches. |
BatchMatMulV2.Options |
Optional attributes for
BatchMatMulV2
|
BatchMatMulV3 <V> | Multiplies slices of two tensors in batches. |
BatchMatMulV3.Options |
Optional attributes for
BatchMatMulV3
|
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. |
BlockLSTM.Options |
Optional attributes for
BlockLSTM
|
BlockLSTMGrad <T extends Number> | Computes the LSTM cell backward propagation for the entire time sequence. |
BlockLSTMGradV2 <T extends Number> | Computes the LSTM cell backward propagation for the entire time sequence. |
BlockLSTMV2 <T extends Number> | Computes the LSTM cell forward propagation for all the time steps. |
BlockLSTMV2.Options |
Optional attributes for
BlockLSTMV2
|
BoostedTreesAggregateStats | Aggregates the summary of accumulated stats for the batch. |
BoostedTreesBucketize | Bucketize each feature based on bucket boundaries. |
BoostedTreesCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
BoostedTreesCalculateBestFeatureSplit.Options |
Optional attributes for
BoostedTreesCalculateBestFeatureSplit
|
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. |
BoostedTreesCreateQuantileStreamResource.Options |
Optional attributes for
BoostedTreesCreateQuantileStreamResource
|
BoostedTreesDeserializeEnsemble |
Deserializes a serialized tree ensemble config and replaces current tree
ensemble. |
BoostedTreesEnsembleResourceHandleOp | Creates a handle to a BoostedTreesEnsembleResource |
BoostedTreesEnsembleResourceHandleOp.Options |
Optional attributes for
BoostedTreesEnsembleResourceHandleOp
|
BoostedTreesExampleDebugOutputs | Debugging/model interpretability outputs for each example. |
BoostedTreesFlushQuantileSummaries | Flush the quantile summaries from each quantile stream resource. |
BoostedTreesGetEnsembleStates | Retrieves the tree ensemble resource stamp token, number of trees and growing statistics. |
BoostedTreesMakeQuantileSummaries | Makes the summary of quantiles for the batch. |
BoostedTreesMakeStatsSummary | Makes the summary of accumulated stats for the batch. |
BoostedTreesPredict |
Runs multiple additive regression ensemble predictors on input instances and
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. |
BoostedTreesQuantileStreamResourceFlush.Options |
Optional attributes for
BoostedTreesQuantileStreamResourceFlush
|
BoostedTreesQuantileStreamResourceGetBucketBoundaries | Generate the bucket boundaries for each feature based on accumulated summaries. |
BoostedTreesQuantileStreamResourceHandleOp | Creates a handle to a BoostedTreesQuantileStreamResource. |
BoostedTreesQuantileStreamResourceHandleOp.Options |
Optional attributes for
BoostedTreesQuantileStreamResourceHandleOp
|
BoostedTreesSerializeEnsemble | Serializes the tree ensemble to a proto. |
BoostedTreesSparseAggregateStats | Aggregates the summary of accumulated stats for the batch. |
BoostedTreesSparseCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
BoostedTreesSparseCalculateBestFeatureSplit.Options |
Optional attributes for
BoostedTreesSparseCalculateBestFeatureSplit
|
BoostedTreesTrainingPredict |
Runs multiple additive regression ensemble predictors on input instances and
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. |
BoostedTreesUpdateEnsembleV2.Options |
Optional attributes for
BoostedTreesUpdateEnsembleV2
|
BroadcastDynamicShape <T extends Number> | Return the shape of s0 op s1 with broadcast. |
BroadcastGradientArgs <T extends Number> | Return the reduction indices for computing gradients of s0 op s1 with broadcast. |
BroadcastTo <T> | Broadcast an array for a compatible shape. |
Bucketize | Bucketizes 'input' based on 'boundaries'. |
CacheDatasetV2 | |
CheckNumericsV2 <T extends Number> | Checks a tensor for NaN, -Inf and +Inf values. |
ChooseFastestDataset | |
ClipByValue <T> | Clips tensor values to a specified min and max. |
CollectiveBcastRecvV2 <U> | Receives a tensor value broadcast from another device. |
CollectiveBcastRecvV2.Options |
Optional attributes for
CollectiveBcastRecvV2
|
CollectiveBcastSendV2 <T> | Broadcasts a tensor value to one or more other devices. |
CollectiveBcastSendV2.Options |
Optional attributes for
CollectiveBcastSendV2
|
CollectiveGather <T extends Number> | Mutually accumulates multiple tensors of identical type and shape. |
CollectiveGather.Options |
Optional attributes for
CollectiveGather
|
CollectiveGatherV2 <T extends Number> | Mutually accumulates multiple tensors of identical type and shape. |
CollectiveGatherV2.Options |
Optional attributes for
CollectiveGatherV2
|
CollectivePermute <T> | An Op to permute tensors across replicated TPU instances. |
CollectiveReduceV2 <T extends Number> | Mutually reduces multiple tensors of identical type and shape. |
CollectiveReduceV2.Options |
Optional attributes for
CollectiveReduceV2
|
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. |
CombinedNonMaxSuppression.Options |
Optional attributes for
CombinedNonMaxSuppression
|
CompositeTensorVariantFromComponents | Encodes an `ExtensionType` value into a `variant` scalar Tensor. |
CompositeTensorVariantToComponents | Decodes a `variant` scalar Tensor into an `ExtensionType` value. |
CompressElement | Compresses a dataset element. |
ComputeBatchSize | Computes the static batch size of a dataset sans partial batches. |
Concat <T> | Concatenates tensors along one dimension. |
ConfigureDistributedTPU | Sets up the centralized structures for a distributed TPU system. |
ConfigureDistributedTPU.Options |
Optional attributes for
ConfigureDistributedTPU
|
ConfigureTPUEmbedding | Sets up TPUEmbedding in a distributed TPU system. |
Constant <T> | An operator producing a constant value. |
ConsumeMutexLock | This op consumes a lock created by `MutexLock`. |
ControlTrigger | Does nothing. |
Copy <T> | Copy a tensor from CPU-to-CPU or GPU-to-GPU. |
Copy.Options |
Optional attributes for
Copy
|
CopyHost <T> | Copy a tensor to host. |
CopyHost.Options |
Optional attributes for
CopyHost
|
CountUpTo <T extends Number> | Increments 'ref' until it reaches 'limit'. |
CrossReplicaSum <T extends Number> | An Op to sum inputs across replicated TPU instances. |
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. |
CTCLossV2.Options |
Optional attributes for
CTCLossV2
|
CudnnRNNBackpropV3 <T extends Number> | Backprop step of CudnnRNNV3. |
CudnnRNNBackpropV3.Options |
Optional attributes for
CudnnRNNBackpropV3
|
CudnnRNNCanonicalToParamsV2 <T extends Number> | Converts CudnnRNN params from canonical form to usable form. |
CudnnRNNCanonicalToParamsV2.Options |
Optional attributes for
CudnnRNNCanonicalToParamsV2
|
CudnnRNNParamsToCanonicalV2 <T extends Number> | Retrieves CudnnRNN params in canonical form. |
CudnnRNNParamsToCanonicalV2.Options |
Optional attributes for
CudnnRNNParamsToCanonicalV2
|
CudnnRNNV3 <T extends Number> | A RNN backed by cuDNN. |
CudnnRNNV3.Options |
Optional attributes for
CudnnRNNV3
|
CumulativeLogsumexp <T extends Number> | Compute the cumulative product of the tensor `x` along `axis`. |
CumulativeLogsumexp.Options |
Optional attributes for
CumulativeLogsumexp
|
DataServiceDataset | Creates a dataset that reads data from the tf.data service. |
DataServiceDataset.Options |
Optional attributes for
DataServiceDataset
|
DataServiceDatasetV2 | Creates a dataset that reads data from the tf.data service. |
DataServiceDatasetV2.Options |
Optional attributes for
DataServiceDatasetV2
|
DatasetCardinality | Returns the cardinality of `input_dataset`. |
DatasetFromGraph | Creates a dataset from the given `graph_def`. |
DatasetToGraphV2 | Returns a serialized GraphDef representing `input_dataset`. |
DatasetToGraphV2.Options |
Optional attributes for
DatasetToGraphV2
|
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. |
DebugIdentity.Options |
Optional attributes for
DebugIdentity
|
DebugIdentityV2 <T> | Debug Identity V2 Op. |
DebugIdentityV2.Options |
Optional attributes for
DebugIdentityV2
|
DebugNanCount | Debug NaN Value Counter Op. |
DebugNanCount.Options |
Optional attributes for
DebugNanCount
|
DebugNumericSummary | Debug Numeric Summary Op. |
DebugNumericSummary.Options |
Optional attributes for
DebugNumericSummary
|
DebugNumericSummaryV2 <U extends Number> | Debug Numeric Summary V2 Op. |
DebugNumericSummaryV2.Options |
Optional attributes for
DebugNumericSummaryV2
|
DecodeImage <T extends Number> | Function for decode_bmp, decode_gif, decode_jpeg, and decode_png. |
DecodeImage.Options |
Optional attributes for
DecodeImage
|
DecodePaddedRaw <T extends Number> | Reinterpret the bytes of a string as a vector of numbers. |
DecodePaddedRaw.Options |
Optional attributes for
DecodePaddedRaw
|
DecodeProto | The op extracts fields from a serialized protocol buffers message into tensors. |
DecodeProto.Options |
Optional attributes for
DecodeProto
|
DeepCopy <T> | Makes a copy of `x`. |
DeleteIterator | A container for an iterator resource. |
DeleteMemoryCache | |
DeleteMultiDeviceIterator | A container for an iterator resource. |
DeleteRandomSeedGenerator | |
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. |
DenseBincount.Options |
Optional attributes for
DenseBincount
|
DenseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a tf.tensor input. |
DenseCountSparseOutput.Options |
Optional attributes for
DenseCountSparseOutput
|
DenseToCSRSparseMatrix | Converts a dense tensor to a (possibly batched) CSRSparseMatrix. |
DestroyResourceOp | Deletes the resource specified by the handle. |
DestroyResourceOp.Options |
Optional attributes for
DestroyResourceOp
|
DestroyTemporaryVariable <T> | Destroys the temporary variable and returns its final value. |
DeviceIndex | Return the index of device the op runs. |
DirectedInterleaveDataset | A substitute for `InterleaveDataset` on a fixed list of `N` datasets. |
DirectedInterleaveDataset.Options |
Optional attributes for
DirectedInterleaveDataset
|
DrawBoundingBoxesV2 <T extends Number> | Draw bounding boxes on a batch of images. |
DummyIterationCounter | |
DummyMemoryCache | |
DummySeedGenerator | |
DynamicPartition <T> | Partitions `data` into `num_partitions` tensors using indices from `partitions`. |
DynamicStitch <T> | Interleave the values from the `data` tensors into a single tensor. |
EditDistance | Computes the (possibly normalized) Levenshtein Edit Distance. |
EditDistance.Options |
Optional attributes for
EditDistance
|
Eig <U> | Computes the eigen decomposition of one or more square matrices. |
Eig.Options |
Optional attributes for
Eig
|
Einsum <T> | Tensor contraction according to Einstein summation convention. |
Empty <T> | Creates a tensor with the given shape. |
Empty.Options |
Optional attributes for
Empty
|
EmptyTensorList | Creates and returns an empty tensor list. |
EmptyTensorMap | Creates and returns an empty tensor map. |
EncodeProto | The op serializes protobuf messages provided in the input tensors. |
EncodeProto.Options |
Optional attributes for
EncodeProto
|
EnqueueTPUEmbeddingIntegerBatch | An op that enqueues a list of input batch tensors to TPUEmbedding. |
EnqueueTPUEmbeddingIntegerBatch.Options |
Optional attributes for
EnqueueTPUEmbeddingIntegerBatch
|
EnqueueTPUEmbeddingRaggedTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup(). |
EnqueueTPUEmbeddingRaggedTensorBatch.Options |
Optional attributes for
EnqueueTPUEmbeddingRaggedTensorBatch
|
EnqueueTPUEmbeddingSparseBatch | An op that enqueues TPUEmbedding input indices from a SparseTensor. |
EnqueueTPUEmbeddingSparseBatch.Options |
Optional attributes for
EnqueueTPUEmbeddingSparseBatch
|
EnqueueTPUEmbeddingSparseTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
EnqueueTPUEmbeddingSparseTensorBatch.Options |
Optional attributes for
EnqueueTPUEmbeddingSparseTensorBatch
|
EnsureShape <T> | Ensures that the tensor's shape matches the expected shape. |
Enter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
Enter.Options |
Optional attributes for
Enter
|
Erfinv <T extends Number> | |
EuclideanNorm <T> | Computes the euclidean norm of elements across dimensions of a tensor. |
EuclideanNorm.Options |
Optional attributes for
EuclideanNorm
|
Exit <T> | Exits the current frame to its parent frame. |
ExpandDims <T> | Inserts a dimension of 1 into a tensor's shape. |
ExperimentalAutoShardDataset | Creates a dataset that shards the input dataset. |
ExperimentalAutoShardDataset.Options |
Optional attributes for
ExperimentalAutoShardDataset
|
ExperimentalBytesProducedStatsDataset | Records the bytes size of each element of `input_dataset` in a StatsAggregator. |
ExperimentalChooseFastestDataset | |
ExperimentalDatasetCardinality | Returns the cardinality of `input_dataset`. |
ExperimentalDatasetToTFRecord | Writes the given dataset to the given file using the TFRecord format. |
ExperimentalDenseToSparseBatchDataset | Creates a dataset that batches input elements into a SparseTensor. |
ExperimentalLatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
ExperimentalMatchingFilesDataset | |
ExperimentalMaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
ExperimentalParseExampleDataset | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
ExperimentalParseExampleDataset.Options |
Optional attributes for
ExperimentalParseExampleDataset
|
ExperimentalPrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
ExperimentalRandomDataset | Creates a Dataset that returns pseudorandom numbers. |
ExperimentalRebatchDataset | Creates a dataset that changes the batch size. |
ExperimentalRebatchDataset.Options |
Optional attributes for
ExperimentalRebatchDataset
|
ExperimentalSetStatsAggregatorDataset | |
ExperimentalSlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
ExperimentalSqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
ExperimentalStatsAggregatorHandle | Creates a statistics manager resource. |
ExperimentalStatsAggregatorHandle.Options |
Optional attributes for
ExperimentalStatsAggregatorHandle
|
ExperimentalStatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
ExperimentalUnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
Expint <T extends Number> | |
ExtractGlimpseV2 | Extracts a glimpse from the input tensor. |
ExtractGlimpseV2.Options |
Optional attributes for
ExtractGlimpseV2
|
ExtractVolumePatches <T extends Number> | Extract `patches` from `input` and put them in the `"depth"` output dimension. |
Fill <U> | Creates a tensor filled with a scalar value. |
FinalizeDataset | Creates a dataset by applying `tf.data.Options` to `input_dataset`. |
FinalizeDataset.Options |
Optional attributes for
FinalizeDataset
|
Fingerprint | Generates fingerprint values. |
FresnelCos <T extends Number> | |
FresnelSin <T extends Number> | |
FusedBatchNormGradV3 <T extends Number, U extends Number> | Gradient for batch normalization. |
FusedBatchNormGradV3.Options |
Optional attributes for
FusedBatchNormGradV3
|
FusedBatchNormV3 <T extends Number, U extends Number> | Batch normalization. |
FusedBatchNormV3.Options |
Optional attributes for
FusedBatchNormV3
|
Gather <T> | Gather slices from `params` axis `axis` according to `indices`. |
Gather.Options |
Optional attributes for
Gather
|
GatherNd <T> | Gather slices from `params` into a Tensor with shape specified by `indices`. |
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`. |
GenerateBoundingBoxProposals.Options |
Optional attributes for
GenerateBoundingBoxProposals
|
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
|
Gradients.Options |
Optional attributes for
Gradients
|
GRUBlockCell <T extends Number> | Computes the GRU cell forward propagation for 1 time step. |
GRUBlockCellGrad <T extends Number> | Computes the GRU cell back-propagation for 1 time step. |
GuaranteeConst <T> | Gives a guarantee to the TF runtime that the input tensor is a constant. |
HashTable | Creates a non-initialized hash table. |
HashTable.Options |
Optional attributes for
HashTable
|
HistogramFixedWidth <U extends Number> | Return histogram of values. |
Identity <T> | Return a tensor with the same shape and contents as the input tensor or value. |
IdentityN |
Returns a list of tensors with the same shapes and contents as the input
tensors. |
IgnoreErrorsDataset | Creates a dataset that contains the elements of `input_dataset` ignoring errors. |
IgnoreErrorsDataset.Options |
Optional attributes for
IgnoreErrorsDataset
|
ImageProjectiveTransformV2 <T extends Number> | Applies the given transform to each of the images. |
ImageProjectiveTransformV2.Options |
Optional attributes for
ImageProjectiveTransformV2
|
ImageProjectiveTransformV3 <T extends Number> | Applies the given transform to each of the images. |
ImageProjectiveTransformV3.Options |
Optional attributes for
ImageProjectiveTransformV3
|
ImmutableConst <T> | Returns immutable tensor from memory region. |
InfeedDequeue <T> | A placeholder op for a value that will be fed into the computation. |
InfeedDequeueTuple | Fetches multiple values from infeed as an XLA tuple. |
InfeedEnqueue | An op which feeds a single Tensor value into the computation. |
InfeedEnqueue.Options |
Optional attributes for
InfeedEnqueue
|
InfeedEnqueuePrelinearizedBuffer | An op which enqueues prelinearized buffer into TPU infeed. |
InfeedEnqueuePrelinearizedBuffer.Options |
Optional attributes for
InfeedEnqueuePrelinearizedBuffer
|
InfeedEnqueueTuple | Feeds multiple Tensor values into the computation as an XLA tuple. |
InfeedEnqueueTuple.Options |
Optional attributes for
InfeedEnqueueTuple
|
InitializeTable | Table initializer that takes two tensors for keys and values respectively. |
InitializeTableFromDataset | |
InitializeTableFromTextFile | Initializes a table from a text file. |
InitializeTableFromTextFile.Options |
Optional attributes for
InitializeTableFromTextFile
|
InplaceAdd <T> | Adds v into specified rows of x. |
InplaceSub <T> | Subtracts `v` into specified rows of `x`. |
InplaceUpdate <T> | Updates specified rows 'i' with values 'v'. |
IsBoostedTreesEnsembleInitialized | Checks whether a tree ensemble has been initialized. |
IsBoostedTreesQuantileStreamResourceInitialized | Checks whether a quantile stream has been initialized. |
IsotonicRegression <U extends Number> | Solves a batch of isotonic regression problems. |
IsVariableInitialized | Checks whether a tensor has been initialized. |
IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
KMC2ChainInitialization | Returns the index of a data point that should be added to the seed set. |
KmeansPlusPlusInitialization | Selects num_to_sample rows of input using the KMeans++ criterion. |
KthOrderStatistic | Computes the Kth order statistic of a data set. |
LinSpace <T extends Number> | Generates values in an interval. |
LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
LoadTPUEmbeddingAdadeltaParameters.Options |
Optional attributes for
LoadTPUEmbeddingAdadeltaParameters
|
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug | Load Adadelta parameters with debug support. |
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingAdadeltaParametersGradAccumDebug
|
LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
LoadTPUEmbeddingAdagradParameters.Options |
Optional attributes for
LoadTPUEmbeddingAdagradParameters
|
LoadTPUEmbeddingAdagradParametersGradAccumDebug | Load Adagrad embedding parameters with debug support. |
LoadTPUEmbeddingAdagradParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingAdagradParametersGradAccumDebug
|
LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
LoadTPUEmbeddingADAMParameters.Options |
Optional attributes for
LoadTPUEmbeddingADAMParameters
|
LoadTPUEmbeddingADAMParametersGradAccumDebug | Load ADAM embedding parameters with debug support. |
LoadTPUEmbeddingADAMParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingADAMParametersGradAccumDebug
|
LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
LoadTPUEmbeddingCenteredRMSPropParameters.Options |
Optional attributes for
LoadTPUEmbeddingCenteredRMSPropParameters
|
LoadTPUEmbeddingFrequencyEstimatorParameters | Load frequency estimator embedding parameters. |
LoadTPUEmbeddingFrequencyEstimatorParameters.Options |
Optional attributes for
LoadTPUEmbeddingFrequencyEstimatorParameters
|
LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug | Load frequency estimator embedding parameters with debug support. |
LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
|
LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
LoadTPUEmbeddingFTRLParameters.Options |
Optional attributes for
LoadTPUEmbeddingFTRLParameters
|
LoadTPUEmbeddingFTRLParametersGradAccumDebug | Load FTRL embedding parameters with debug support. |
LoadTPUEmbeddingFTRLParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingFTRLParametersGradAccumDebug
|
LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
LoadTPUEmbeddingMDLAdagradLightParameters.Options |
Optional attributes for
LoadTPUEmbeddingMDLAdagradLightParameters
|
LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
LoadTPUEmbeddingMomentumParameters.Options |
Optional attributes for
LoadTPUEmbeddingMomentumParameters
|
LoadTPUEmbeddingMomentumParametersGradAccumDebug | Load Momentum embedding parameters with debug support. |
LoadTPUEmbeddingMomentumParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingMomentumParametersGradAccumDebug
|
LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
LoadTPUEmbeddingProximalAdagradParameters.Options |
Optional attributes for
LoadTPUEmbeddingProximalAdagradParameters
|
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug | Load proximal Adagrad embedding parameters with debug support. |
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug
|
LoadTPUEmbeddingProximalYogiParameters | |
LoadTPUEmbeddingProximalYogiParameters.Options |
Optional attributes for
LoadTPUEmbeddingProximalYogiParameters
|
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug | |
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingProximalYogiParametersGradAccumDebug
|
LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
LoadTPUEmbeddingRMSPropParameters.Options |
Optional attributes for
LoadTPUEmbeddingRMSPropParameters
|
LoadTPUEmbeddingRMSPropParametersGradAccumDebug | Load RMSProp embedding parameters with debug support. |
LoadTPUEmbeddingRMSPropParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingRMSPropParametersGradAccumDebug
|
LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
LoadTPUEmbeddingStochasticGradientDescentParameters.Options |
Optional attributes for
LoadTPUEmbeddingStochasticGradientDescentParameters
|
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Load SGD embedding parameters. |
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options |
Optional attributes for
LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
|
LookupTableExport <T, U> | Outputs all keys and values in the table. |
LookupTableFind <U> | Looks up keys in a table, outputs the corresponding values. |
LookupTableImport | Replaces the contents of the table with the specified keys and values. |
LookupTableInsert | Updates the table to associates keys with values. |
LookupTableRemove | Removes keys and its associated values from a table. |
LookupTableSize | Computes the number of elements in the given table. |
LoopCond | Forwards the input to the output. |
LowerBound <U extends Number> | Applies lower_bound(sorted_search_values, values) along each row. |
LSTMBlockCell <T extends Number> | Computes the LSTM cell forward propagation for 1 time step. |
LSTMBlockCell.Options |
Optional attributes for
LSTMBlockCell
|
LSTMBlockCellGrad <T extends Number> | Computes the LSTM cell backward propagation for 1 timestep. |
Lu <T, U extends Number> | Computes the LU decomposition of one or more square matrices. |
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. |
MapClear.Options |
Optional attributes for
MapClear
|
MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
MapIncompleteSize.Options |
Optional attributes for
MapIncompleteSize
|
MapPeek | Op peeks at the values at the specified key. |
MapPeek.Options |
Optional attributes for
MapPeek
|
MapSize | Op returns the number of elements in the underlying container. |
MapSize.Options |
Optional attributes for
MapSize
|
MapStage | Stage (key, values) in the underlying container which behaves like a hashtable. |
MapStage.Options |
Optional attributes for
MapStage
|
MapUnstage |
Op removes and returns the values associated with the key
from the underlying container. |
MapUnstage.Options |
Optional attributes for
MapUnstage
|
MapUnstageNoKey |
Op removes and returns a random (key, value)
from the underlying container. |
MapUnstageNoKey.Options |
Optional attributes for
MapUnstageNoKey
|
MatrixDiagPartV2 <T> | Returns the batched diagonal part of a batched tensor. |
MatrixDiagPartV3 <T> | Returns the batched diagonal part of a batched tensor. |
MatrixDiagPartV3.Options |
Optional attributes for
MatrixDiagPartV3
|
MatrixDiagV2 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
MatrixDiagV3 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
MatrixDiagV3.Options |
Optional attributes for
MatrixDiagV3
|
MatrixSetDiagV2 <T> | Returns a batched matrix tensor with new batched diagonal values. |
MatrixSetDiagV3 <T> | Returns a batched matrix tensor with new batched diagonal values. |
MatrixSetDiagV3.Options |
Optional attributes for
MatrixSetDiagV3
|
Max <T> | Computes the maximum of elements across dimensions of a tensor. |
Max.Options |
Optional attributes for
Max
|
MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
Merge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
Min <T> | Computes the minimum of elements across dimensions of a tensor. |
Min.Options |
Optional attributes for
Min
|
MirrorPad <T> | Pads a tensor with mirrored values. |
MirrorPadGrad <T> | Gradient op for `MirrorPad` op. |
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. |
MutableDenseHashTable.Options |
Optional attributes for
MutableDenseHashTable
|
MutableHashTable | Creates an empty hash table. |
MutableHashTable.Options |
Optional attributes for
MutableHashTable
|
MutableHashTableOfTensors | Creates an empty hash table. |
MutableHashTableOfTensors.Options |
Optional attributes for
MutableHashTableOfTensors
|
Mutex | Creates a Mutex resource that can be locked by `MutexLock`. |
Mutex.Options |
Optional attributes for
Mutex
|
MutexLock | Locks a mutex resource. |
NcclAllReduce <T extends Number> | Outputs a tensor containing the reduction across all input tensors. |
NcclBroadcast <T extends Number> | Sends `input` to all devices that are connected to the output. |
NcclReduce <T extends Number> | Reduces `input` from `num_devices` using `reduction` to a single device. |
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. |
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. |
NonMaxSuppressionV5.Options |
Optional attributes for
NonMaxSuppressionV5
|
NonSerializableDataset | |
NoOp | Does nothing. |
OneHot <U> | Returns a one-hot tensor. |
OneHot.Options |
Optional attributes for
OneHot
|
OnesLike <T> | Returns a tensor of ones with the same shape and type as x. |
OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
OptimizeDatasetV2.Options |
Optional attributes for
OptimizeDatasetV2
|
OptionsDataset | Creates a dataset by attaching tf.data.Options to `input_dataset`. |
OrderedMapClear | Op removes all elements in the underlying container. |
OrderedMapClear.Options |
Optional attributes for
OrderedMapClear
|
OrderedMapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
OrderedMapIncompleteSize.Options |
Optional attributes for
OrderedMapIncompleteSize
|
OrderedMapPeek | Op peeks at the values at the specified key. |
OrderedMapPeek.Options |
Optional attributes for
OrderedMapPeek
|
OrderedMapSize | Op returns the number of elements in the underlying container. |
OrderedMapSize.Options |
Optional attributes for
OrderedMapSize
|
OrderedMapStage |
Stage (key, values) in the underlying container which behaves like a ordered
associative container. |
OrderedMapStage.Options |
Optional attributes for
OrderedMapStage
|
OrderedMapUnstage |
Op removes and returns the values associated with the key
from the underlying container. |
OrderedMapUnstage.Options |
Optional attributes for
OrderedMapUnstage
|
OrderedMapUnstageNoKey |
Op removes and returns the (key, value) element with the smallest
key from the underlying container. |
OrderedMapUnstageNoKey.Options |
Optional attributes for
OrderedMapUnstageNoKey
|
OutfeedDequeue <T> | Retrieves a single tensor from the computation outfeed. |
OutfeedDequeue.Options |
Optional attributes for
OutfeedDequeue
|
OutfeedDequeueTuple | Retrieve multiple values from the computation outfeed. |
OutfeedDequeueTuple.Options |
Optional attributes for
OutfeedDequeueTuple
|
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 | |
ParallelBatchDataset.Options |
Optional attributes for
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. |
ParseExampleDatasetV2.Options |
Optional attributes for
ParseExampleDatasetV2
|
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. |
ParseSequenceExampleV2.Options |
Optional attributes for
ParseSequenceExampleV2
|
Placeholder <T> | A placeholder op for a value that will be fed into the computation. |
Placeholder.Options |
Optional attributes for
Placeholder
|
PlaceholderWithDefault <T> | A placeholder op that passes through `input` when its output is not fed. |
Prelinearize | An op which linearizes one Tensor value to an opaque variant tensor. |
Prelinearize.Options |
Optional attributes for
Prelinearize
|
PrelinearizeTuple | An op which linearizes multiple Tensor values to an opaque variant tensor. |
PrelinearizeTuple.Options |
Optional attributes for
PrelinearizeTuple
|
Prints a string scalar. | |
Print.Options |
Optional attributes for
Print
|
PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
Prod <T> | Computes the product of elements across dimensions of a tensor. |
Prod.Options |
Optional attributes for
Prod
|
QuantizeAndDequantizeV4 <T extends Number> | Quantizes then dequantizes a tensor. |
QuantizeAndDequantizeV4.Options |
Optional attributes for
QuantizeAndDequantizeV4
|
QuantizeAndDequantizeV4Grad <T extends Number> | Returns the gradient of `QuantizeAndDequantizeV4`. |
QuantizeAndDequantizeV4Grad.Options |
Optional attributes for
QuantizeAndDequantizeV4Grad
|
QuantizedConcat <T> | Concatenates quantized tensors along one dimension. |
QuantizedConcatV2 <T> | |
QuantizedConv2DAndRelu <V> | |
QuantizedConv2DAndRelu.Options |
Optional attributes for
QuantizedConv2DAndRelu
|
QuantizedConv2DAndReluAndRequantize <V> | |
QuantizedConv2DAndReluAndRequantize.Options |
Optional attributes for
QuantizedConv2DAndReluAndRequantize
|
QuantizedConv2DAndRequantize <V> | |
QuantizedConv2DAndRequantize.Options |
Optional attributes for
QuantizedConv2DAndRequantize
|
QuantizedConv2DPerChannel <V> | Computes QuantizedConv2D per channel. |
QuantizedConv2DPerChannel.Options |
Optional attributes for
QuantizedConv2DPerChannel
|
QuantizedConv2DWithBias <V> | |
QuantizedConv2DWithBias.Options |
Optional attributes for
QuantizedConv2DWithBias
|
QuantizedConv2DWithBiasAndRelu <V> | |
QuantizedConv2DWithBiasAndRelu.Options |
Optional attributes for
QuantizedConv2DWithBiasAndRelu
|
QuantizedConv2DWithBiasAndReluAndRequantize <W> | |
QuantizedConv2DWithBiasAndReluAndRequantize.Options |
Optional attributes for
QuantizedConv2DWithBiasAndReluAndRequantize
|
QuantizedConv2DWithBiasAndRequantize <W> | |
QuantizedConv2DWithBiasAndRequantize.Options |
Optional attributes for
QuantizedConv2DWithBiasAndRequantize
|
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X> | |
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options |
Optional attributes for
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
|
QuantizedConv2DWithBiasSumAndRelu <V> | |
QuantizedConv2DWithBiasSumAndRelu.Options |
Optional attributes for
QuantizedConv2DWithBiasSumAndRelu
|
QuantizedConv2DWithBiasSumAndReluAndRequantize <X> | |
QuantizedConv2DWithBiasSumAndReluAndRequantize.Options |
Optional attributes for
QuantizedConv2DWithBiasSumAndReluAndRequantize
|
QuantizedDepthwiseConv2D <V> | Computes quantized depthwise Conv2D. |
QuantizedDepthwiseConv2D.Options |
Optional attributes for
QuantizedDepthwiseConv2D
|
QuantizedDepthwiseConv2DWithBias <V> | Computes quantized depthwise Conv2D with Bias. |
QuantizedDepthwiseConv2DWithBias.Options |
Optional attributes for
QuantizedDepthwiseConv2DWithBias
|
QuantizedDepthwiseConv2DWithBiasAndRelu <V> | Computes quantized depthwise Conv2D with Bias and Relu. |
QuantizedDepthwiseConv2DWithBiasAndRelu.Options |
Optional attributes for
QuantizedDepthwiseConv2DWithBiasAndRelu
|
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W> | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options |
Optional attributes for
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
|
QuantizedMatMulWithBias <W> | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
QuantizedMatMulWithBias.Options |
Optional attributes for
QuantizedMatMulWithBias
|
QuantizedMatMulWithBiasAndDequantize <W extends Number> | |
QuantizedMatMulWithBiasAndDequantize.Options |
Optional attributes for
QuantizedMatMulWithBiasAndDequantize
|
QuantizedMatMulWithBiasAndRelu <V> | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion. |
QuantizedMatMulWithBiasAndRelu.Options |
Optional attributes for
QuantizedMatMulWithBiasAndRelu
|
QuantizedMatMulWithBiasAndReluAndRequantize <W> | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion. |
QuantizedMatMulWithBiasAndReluAndRequantize.Options |
Optional attributes for
QuantizedMatMulWithBiasAndReluAndRequantize
|
QuantizedMatMulWithBiasAndRequantize <W> | |
QuantizedMatMulWithBiasAndRequantize.Options |
Optional attributes for
QuantizedMatMulWithBiasAndRequantize
|
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. |
RaggedBincount.Options |
Optional attributes for
RaggedBincount
|
RaggedCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a ragged tensor input. |
RaggedCountSparseOutput.Options |
Optional attributes for
RaggedCountSparseOutput
|
RaggedCross <T, U extends Number> | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
RaggedGather <T extends Number, U> | Gather ragged slices from `params` axis `0` according to `indices`. |
RaggedRange <U extends Number, T extends Number> | Returns a `RaggedTensor` containing the specified sequences of numbers. |
RaggedTensorFromVariant <U extends Number, T> | Decodes a `variant` Tensor into a `RaggedTensor`. |
RaggedTensorToSparse <U> | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
RaggedTensorToTensor <U> | Create a dense tensor from a ragged tensor, possibly altering its shape. |
RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
RaggedTensorToVariantGradient <U> | Helper used to compute the gradient for `RaggedTensorToVariant`. |
Range <T extends Number> | Creates a sequence of numbers. |
Rank | Returns the rank of a tensor. |
ReadVariableOp <T> | Reads the value of a variable. |
RebatchDataset | Creates a dataset that changes the batch size. |
RebatchDataset.Options |
Optional attributes for
RebatchDataset
|
RebatchDatasetV2 | Creates a dataset that changes the batch size. |
Recv <T> | Receives the named tensor from send_device on recv_device. |
Recv.Options |
Optional attributes for
Recv
|
RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
ReduceAll | Computes the "logical and" of elements across dimensions of a tensor. |
ReduceAll.Options |
Optional attributes for
ReduceAll
|
ReduceAny | Computes the "logical or" of elements across dimensions of a tensor. |
ReduceAny.Options |
Optional attributes for
ReduceAny
|
ReduceMax <T> | Computes the maximum of elements across dimensions of a tensor. |
ReduceMax.Options |
Optional attributes for
ReduceMax
|
ReduceMin <T> | Computes the minimum of elements across dimensions of a tensor. |
ReduceMin.Options |
Optional attributes for
ReduceMin
|
ReduceProd <T> | Computes the product of elements across dimensions of a tensor. |
ReduceProd.Options |
Optional attributes for
ReduceProd
|
ReduceSum <T> | Computes the sum of elements across dimensions of a tensor. |
ReduceSum.Options |
Optional attributes for
ReduceSum
|
RefEnter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
RefEnter.Options |
Optional attributes for
RefEnter
|
RefExit <T> | Exits the current frame to its parent frame. |
RefIdentity <T> | Return the same ref tensor as the input ref tensor. |
RefMerge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
RefNextIteration <T> | Makes its input available to the next iteration. |
RefSelect <T> | Forwards the `index`th element of `inputs` to `output`. |
RefSwitch <T> | Forwards the ref tensor `data` to the output port determined by `pred`. |
RegisterDataset | Registers a dataset with the tf.data service. |
RequantizationRangePerChannel | Computes requantization range per channel. |
RequantizePerChannel <U> | Requantizes input with min and max values known per channel. |
Reshape <T> | Reshapes a tensor. |
ResourceAccumulatorApplyGradient | Applies a gradient to a given accumulator. |
ResourceAccumulatorNumAccumulated | Returns the number of gradients aggregated in the given accumulators. |
ResourceAccumulatorSetGlobalStep | Updates the accumulator with a new value for global_step. |
ResourceAccumulatorTakeGradient <T> | Extracts the average gradient in the given ConditionalAccumulator. |
ResourceApplyAdagradV2 | Update '*var' according to the adagrad scheme. |
ResourceApplyAdagradV2.Options |
Optional attributes for
ResourceApplyAdagradV2
|
ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
ResourceApplyAdamWithAmsgrad.Options |
Optional attributes for
ResourceApplyAdamWithAmsgrad
|
ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
ResourceApplyKerasMomentum.Options |
Optional attributes for
ResourceApplyKerasMomentum
|
ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
ResourceConditionalAccumulator.Options |
Optional attributes for
ResourceConditionalAccumulator
|
ResourceCountUpTo <T extends Number> | Increments variable pointed to by 'resource' until it reaches 'limit'. |
ResourceGather <U> | Gather slices from the variable pointed to by `resource` according to `indices`. |
ResourceGather.Options |
Optional attributes for
ResourceGather
|
ResourceGatherNd <U> | |
ResourceScatterAdd | Adds sparse updates to the variable referenced by `resource`. |
ResourceScatterDiv | Divides sparse updates into the variable referenced by `resource`. |
ResourceScatterMax | Reduces sparse updates into the variable referenced by `resource` using the `max` operation. |
ResourceScatterMin | Reduces sparse updates into the variable referenced by `resource` using the `min` operation. |
ResourceScatterMul | Multiplies sparse updates into the variable referenced by `resource`. |
ResourceScatterNdAdd | Applies sparse addition to individual values or slices in a Variable. |
ResourceScatterNdAdd.Options |
Optional attributes for
ResourceScatterNdAdd
|
ResourceScatterNdMax | |
ResourceScatterNdMax.Options |
Optional attributes for
ResourceScatterNdMax
|
ResourceScatterNdMin | |
ResourceScatterNdMin.Options |
Optional attributes for
ResourceScatterNdMin
|
ResourceScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable. |
ResourceScatterNdSub.Options |
Optional attributes for
ResourceScatterNdSub
|
ResourceScatterNdUpdate |
Applies sparse `updates` to individual values or slices within a given
variable according to `indices`. |
ResourceScatterNdUpdate.Options |
Optional attributes for
ResourceScatterNdUpdate
|
ResourceScatterSub | Subtracts sparse updates from the variable referenced by `resource`. |
ResourceScatterUpdate | Assigns sparse updates to the variable referenced by `resource`. |
ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
ResourceSparseApplyAdagradV2.Options |
Optional attributes for
ResourceSparseApplyAdagradV2
|
ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
ResourceSparseApplyKerasMomentum.Options |
Optional attributes for
ResourceSparseApplyKerasMomentum
|
ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
ResourceStridedSliceAssign.Options |
Optional attributes for
ResourceStridedSliceAssign
|
RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
RetrieveTPUEmbeddingAdadeltaParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingAdadeltaParameters
|
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug | Retrieve Adadelta embedding parameters with debug support. |
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug
|
RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
RetrieveTPUEmbeddingAdagradParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingAdagradParameters
|
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug | Retrieve Adagrad embedding parameters with debug support. |
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingAdagradParametersGradAccumDebug
|
RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
RetrieveTPUEmbeddingADAMParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingADAMParameters
|
RetrieveTPUEmbeddingADAMParametersGradAccumDebug | Retrieve ADAM embedding parameters with debug support. |
RetrieveTPUEmbeddingADAMParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingADAMParametersGradAccumDebug
|
RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
RetrieveTPUEmbeddingCenteredRMSPropParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingCenteredRMSPropParameters
|
RetrieveTPUEmbeddingFrequencyEstimatorParameters | Retrieve frequency estimator embedding parameters. |
RetrieveTPUEmbeddingFrequencyEstimatorParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingFrequencyEstimatorParameters
|
RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug | Retrieve frequency estimator embedding parameters with debug support. |
RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingFrequencyEstimatorParametersGradAccumDebug
|
RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
RetrieveTPUEmbeddingFTRLParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingFTRLParameters
|
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug | Retrieve FTRL embedding parameters with debug support. |
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingFTRLParametersGradAccumDebug
|
RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
RetrieveTPUEmbeddingMDLAdagradLightParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingMDLAdagradLightParameters
|
RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
RetrieveTPUEmbeddingMomentumParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingMomentumParameters
|
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug | Retrieve Momentum embedding parameters with debug support. |
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingMomentumParametersGradAccumDebug
|
RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
RetrieveTPUEmbeddingProximalAdagradParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingProximalAdagradParameters
|
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug | Retrieve proximal Adagrad embedding parameters with debug support. |
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug
|
RetrieveTPUEmbeddingProximalYogiParameters | |
RetrieveTPUEmbeddingProximalYogiParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingProximalYogiParameters
|
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug | |
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug
|
RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
RetrieveTPUEmbeddingRMSPropParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingRMSPropParameters
|
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug | Retrieve RMSProp embedding parameters with debug support. |
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug
|
RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options |
Optional attributes for
RetrieveTPUEmbeddingStochasticGradientDescentParameters
|
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Retrieve SGD embedding parameters with debug support. |
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options |
Optional attributes for
RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
|
Reverse <T> | Reverses specific dimensions of a tensor. |
ReverseSequence <T> | Reverses variable length slices. |
ReverseSequence.Options |
Optional attributes for
ReverseSequence
|
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> | |
RiscConv.Options |
Optional attributes for
RiscConv
|
RiscCos <T extends Number> | |
RiscDiv <T extends Number> | |
RiscDot <T extends Number> | |
RiscDot.Options |
Optional attributes for
RiscDot
|
RiscExp <T extends Number> | |
RiscFft <T> | |
RiscFloor <T extends Number> | |
RiscGather <T> | |
RiscGather.Options |
Optional attributes for
RiscGather
|
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> | |
RiscPool.Options |
Optional attributes for
RiscPool
|
RiscPow <T extends Number> | |
RiscRandomUniform | |
RiscRandomUniform.Options |
Optional attributes for
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> | |
RiscSqueeze.Options |
Optional attributes for
RiscSqueeze
|
RiscSub <T extends Number> | |
RiscTranspose <T> | |
RiscTriangularSolve <T extends Number> | |
RiscTriangularSolve.Options |
Optional attributes for
RiscTriangularSolve
|
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 | |
ScaleAndTranslate.Options |
Optional attributes for
ScaleAndTranslate
|
ScaleAndTranslateGrad <T extends Number> | |
ScaleAndTranslateGrad.Options |
Optional attributes for
ScaleAndTranslateGrad
|
ScatterAdd <T> | Adds sparse updates to a variable reference. |
ScatterAdd.Options |
Optional attributes for
ScatterAdd
|
ScatterDiv <T> | Divides a variable reference by sparse updates. |
ScatterDiv.Options |
Optional attributes for
ScatterDiv
|
ScatterMax <T extends Number> | Reduces sparse updates into a variable reference using the `max` operation. |
ScatterMax.Options |
Optional attributes for
ScatterMax
|
ScatterMin <T extends Number> | Reduces sparse updates into a variable reference using the `min` operation. |
ScatterMin.Options |
Optional attributes for
ScatterMin
|
ScatterMul <T> | Multiplies sparse updates into a variable reference. |
ScatterMul.Options |
Optional attributes for
ScatterMul
|
ScatterNd <U> | Scatter `updates` into a new tensor according to `indices`. |
ScatterNdAdd <T> | Applies sparse addition to individual values or slices in a Variable. |
ScatterNdAdd.Options |
Optional attributes for
ScatterNdAdd
|
ScatterNdMax <T> | Computes element-wise maximum. |
ScatterNdMax.Options |
Optional attributes for
ScatterNdMax
|
ScatterNdMin <T> | Computes element-wise minimum. |
ScatterNdMin.Options |
Optional attributes for
ScatterNdMin
|
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. |
ScatterNdSub.Options |
Optional attributes for
ScatterNdSub
|
ScatterNdUpdate <T> |
Applies sparse `updates` to individual values or slices within a given
variable according to `indices`. |
ScatterNdUpdate.Options |
Optional attributes for
ScatterNdUpdate
|
ScatterSub <T> | Subtracts sparse updates to a variable reference. |
ScatterSub.Options |
Optional attributes for
ScatterSub
|
ScatterUpdate <T> | Applies sparse updates to a variable reference. |
ScatterUpdate.Options |
Optional attributes for
ScatterUpdate
|
SelectV2 <T> | |
Send | Sends the named tensor from send_device to recv_device. |
Send.Options |
Optional attributes for
Send
|
SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
SetDiff1d <T, U extends Number> | Computes the difference between two lists of numbers or strings. |
SetSize | Number of unique elements along last dimension of input `set`. |
SetSize.Options |
Optional attributes for
SetSize
|
Shape <U extends Number> | Returns the shape of a tensor. |
ShapeN <U extends Number> | Returns shape of tensors. |
ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
ShardDataset.Options |
Optional attributes for
ShardDataset
|
ShuffleAndRepeatDatasetV2 | |
ShuffleAndRepeatDatasetV2.Options |
Optional attributes for
ShuffleAndRepeatDatasetV2
|
ShuffleDatasetV2 | |
ShuffleDatasetV3 | |
ShuffleDatasetV3.Options |
Optional attributes for
ShuffleDatasetV3
|
ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
Size <U extends Number> | Returns the size of a tensor. |
Skipgram | Parses a text file and creates a batch of examples. |
Skipgram.Options |
Optional attributes for
Skipgram
|
SleepDataset | |
Slice <T> | Return a slice from 'input'. |
SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
Snapshot <T> | Returns a copy of the input tensor. |
SnapshotDataset | Creates a dataset that will write to / read from a snapshot. |
SnapshotDataset.Options |
Optional attributes for
SnapshotDataset
|
SnapshotDatasetReader | |
SnapshotDatasetReader.Options |
Optional attributes for
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. |
SparseApplyAdagradV2.Options |
Optional attributes for
SparseApplyAdagradV2
|
SparseBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
SparseBincount.Options |
Optional attributes for
SparseBincount
|
SparseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a sparse tensor input. |
SparseCountSparseOutput.Options |
Optional attributes for
SparseCountSparseOutput
|
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. |
SparseMatrixMatMul.Options |
Optional attributes for
SparseMatrixMatMul
|
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`. |
SparseMatrixSparseMatMul.Options |
Optional attributes for
SparseMatrixSparseMatMul
|
SparseMatrixTranspose | Transposes the inner (matrix) dimensions of a CSRSparseMatrix. |
SparseMatrixTranspose.Options |
Optional attributes for
SparseMatrixTranspose
|
SparseMatrixZeros | Creates an all-zeros CSRSparseMatrix with shape `dense_shape`. |
SparseSegmentSumGrad <T extends Number> | Computes gradients for SparseSegmentSum. |
SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
Spence <T extends Number> | |
Split <T> | Splits a tensor into `num_split` tensors along one dimension. |
SplitV <T> | Splits a tensor into `num_split` tensors along one dimension. |
Squeeze <T> | Removes dimensions of size 1 from the shape of a tensor. |
Squeeze.Options |
Optional attributes for
Squeeze
|
Stack <T> | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
Stack.Options |
Optional attributes for
Stack
|
Stage | Stage values similar to a lightweight Enqueue. |
Stage.Options |
Optional attributes for
Stage
|
StageClear | Op removes all elements in the underlying container. |
StageClear.Options |
Optional attributes for
StageClear
|
StagePeek | Op peeks at the values at the specified index. |
StagePeek.Options |
Optional attributes for
StagePeek
|
StageSize | Op returns the number of elements in the underlying container. |
StageSize.Options |
Optional attributes for
StageSize
|
StatefulRandomBinomial <V extends Number> | |
StatefulStandardNormal <U> | Outputs random values from a normal distribution. |
StatefulStandardNormalV2 <U> | Outputs random values from a normal distribution. |
StatefulTruncatedNormal <U> | Outputs random values from a truncated normal distribution. |
StatefulUniform <U> | Outputs random values from a uniform distribution. |
StatefulUniformFullInt <U> | Outputs random integers from a uniform distribution. |
StatefulUniformInt <U> | Outputs random integers from a uniform distribution. |
StatelessParameterizedTruncatedNormal <V extends Number> | |
StatelessRandomBinomial <W extends Number> | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
StatelessRandomGammaV2 <V extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
StatelessRandomGetAlg | Picks the best counter-based RNG algorithm based on device. |
StatelessRandomGetKeyCounter | Scrambles seed into key and counter, using the best algorithm based on device. |
StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
StatelessRandomNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a normal distribution. |
StatelessRandomPoisson <W extends Number> | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
StatelessRandomUniformFullInt <V extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformFullIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
StatelessRandomUniformV2 <U extends Number> | Outputs deterministic pseudorandom random values from a uniform distribution. |
StatelessSampleDistortedBoundingBox <T extends Number> | Generate a randomly distorted bounding box for an image deterministically. |
StatelessSampleDistortedBoundingBox.Options |
Optional attributes for
StatelessSampleDistortedBoundingBox
|
StatelessTruncatedNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a truncated normal distribution. |
StatsAggregatorHandleV2 | |
StatsAggregatorHandleV2.Options |
Optional attributes for
StatsAggregatorHandleV2
|
StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
StopGradient <T> | Stops gradient computation. |
StridedSlice <T> | Return a strided slice from `input`. |
StridedSlice.Options |
Optional attributes for
StridedSlice
|
StridedSliceAssign <T> | Assign `value` to the sliced l-value reference of `ref`. |
StridedSliceAssign.Options |
Optional attributes for
StridedSliceAssign
|
StridedSliceGrad <U> | Returns the gradient of `StridedSlice`. |
StridedSliceGrad.Options |
Optional attributes for
StridedSliceGrad
|
StringLower | Converts all uppercase characters into their respective lowercase replacements. |
StringLower.Options |
Optional attributes for
StringLower
|
StringNGrams <T extends Number> | Creates ngrams from ragged string data. |
StringUpper | Converts all lowercase characters into their respective uppercase replacements. |
StringUpper.Options |
Optional attributes for
StringUpper
|
Sum <T> | Computes the sum of elements across dimensions of a tensor. |
Sum.Options |
Optional attributes for
Sum
|
SwitchCond <T> | Forwards `data` to the output port determined by `pred`. |
TemporaryVariable <T> | Returns a tensor that may be mutated, but only persists within a single step. |
TemporaryVariable.Options |
Optional attributes for
TemporaryVariable
|
TensorArray | An array of Tensors of given size. |
TensorArray.Options |
Optional attributes for
TensorArray
|
TensorArrayClose | Delete the TensorArray from its resource container. |
TensorArrayConcat <T> | Concat the elements from the TensorArray into value `value`. |
TensorArrayConcat.Options |
Optional attributes for
TensorArrayConcat
|
TensorArrayGather <T> | Gather specific elements from the TensorArray into output `value`. |
TensorArrayGather.Options |
Optional attributes for
TensorArrayGather
|
TensorArrayGrad | Creates a TensorArray for storing the gradients of values in the given handle. |
TensorArrayGradWithShape | Creates a TensorArray for storing multiple gradients of values in the given handle. |
TensorArrayPack <T> | |
TensorArrayPack.Options |
Optional attributes for
TensorArrayPack
|
TensorArrayRead <T> | Read an element from the TensorArray into output `value`. |
TensorArrayScatter | Scatter the data from the input value into specific TensorArray elements. |
TensorArraySize | Get the current size of the TensorArray. |
TensorArraySplit | Split the data from the input value into TensorArray elements. |
TensorArrayUnpack | |
TensorArrayWrite | Push an element onto the tensor_array. |
TensorListConcat <T> | Concats all tensors in the list along the 0th dimension. |
TensorListConcat.Options |
Optional attributes for
TensorListConcat
|
TensorListConcatLists | |
TensorListConcatV2 <U> | Concats all tensors in the list along the 0th dimension. |
TensorListElementShape <T extends Number> | The shape of the elements of the given list, as a tensor. |
TensorListFromTensor | Creates a TensorList which, when stacked, has the value of `tensor`. |
TensorListGather <T> | Creates a Tensor by indexing into the TensorList. |
TensorListGetItem <T> | |
TensorListLength | Returns the number of tensors in the input tensor list. |
TensorListPopBack <T> | Returns the last element of the input list as well as a list with all but that element. |
TensorListPushBack | Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`. |
TensorListPushBackBatch | |
TensorListReserve | List of the given size with empty elements. |
TensorListResize | Resizes the list. |
TensorListScatter | Creates a TensorList by indexing into a Tensor. |
TensorListScatterIntoExistingList | Scatters tensor at indices in an input list. |
TensorListScatterV2 | Creates a TensorList by indexing into a Tensor. |
TensorListSetItem | |
TensorListSplit | Splits a tensor into a list. |
TensorListStack <T> | Stacks all tensors in the list. |
TensorListStack.Options |
Optional attributes for
TensorListStack
|
TensorMapErase | Returns a tensor map with item from given key erased. |
TensorMapHasKey | Returns whether the given key exists in the map. |
TensorMapInsert | Returns a map that is the 'input_handle' with the given key-value pair inserted. |
TensorMapLookup <U> | Returns the value from a given key in a tensor map. |
TensorMapSize | Returns the number of tensors in the input tensor map. |
TensorMapStackKeys <T> | Returns a Tensor stack of all keys in a tensor map. |
TensorScatterAdd <T> | Adds sparse `updates` to an existing tensor according to `indices`. |
TensorScatterMax <T> | |
TensorScatterMin <T> | |
TensorScatterSub <T> | Subtracts sparse `updates` from an existing tensor according to `indices`. |
TensorScatterUpdate <T> | Scatter `updates` into an existing tensor according to `indices`. |
TensorStridedSliceUpdate <T> | Assign `value` to the sliced l-value reference of `input`. |
TensorStridedSliceUpdate.Options |
Optional attributes for
TensorStridedSliceUpdate
|
ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
ThreadPoolHandle.Options |
Optional attributes for
ThreadPoolHandle
|
Tile <T> | Constructs a tensor by tiling a given tensor. |
Timestamp | Provides the time since epoch in seconds. |
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. |
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. |
TPUPartitionedInput.Options |
Optional attributes for
TPUPartitionedInput
|
TPUPartitionedOutput <T> |
An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned
outputs outside the XLA computation. |
TPUPartitionedOutput.Options |
Optional attributes for
TPUPartitionedOutput
|
TPUReplicatedInput <T> | Connects N inputs to an N-way replicated TPU computation. |
TPUReplicatedInput.Options |
Optional attributes for
TPUReplicatedInput
|
TPUReplicatedOutput <T> | Connects N outputs from an N-way replicated TPU computation. |
TPUReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
TPUReplicateMetadata.Options |
Optional attributes for
TPUReplicateMetadata
|
TPUReshardVariables | Op that reshards on-device TPU variables to specified state. |
TridiagonalMatMul <T> | Calculate product with tridiagonal matrix. |
TridiagonalSolve <T> | Solves tridiagonal systems of equations. |
TridiagonalSolve.Options |
Optional attributes for
TridiagonalSolve
|
Unbatch <T> | Reverses the operation of Batch for a single output Tensor. |
Unbatch.Options |
Optional attributes for
Unbatch
|
UnbatchGrad <T> | Gradient of Unbatch. |
UnbatchGrad.Options |
Optional attributes for
UnbatchGrad
|
UncompressElement | Uncompresses a compressed dataset element. |
UnicodeDecode <T extends Number> | Decodes each string in `input` into a sequence of Unicode code points. |
UnicodeDecode.Options |
Optional attributes for
UnicodeDecode
|
UnicodeEncode | Encode a tensor of ints into unicode strings. |
UnicodeEncode.Options |
Optional attributes for
UnicodeEncode
|
Unique <T, V extends Number> | Finds unique elements along an axis of a tensor. |
UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
UniqueWithCounts <T, V extends Number> | Finds unique elements along an axis of a tensor. |
UnravelIndex <T extends Number> | Converts an array of flat indices into a tuple of coordinate arrays. |
UnsortedSegmentJoin | Joins the elements of `inputs` based on `segment_ids`. |
UnsortedSegmentJoin.Options |
Optional attributes for
UnsortedSegmentJoin
|
Unstack <T> | Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors. |
Unstack.Options |
Optional attributes for
Unstack
|
Unstage | Op is similar to a lightweight Dequeue. |
Unstage.Options |
Optional attributes for
Unstage
|
UnwrapDatasetVariant | |
UpperBound <U extends Number> | Applies upper_bound(sorted_search_values, values) along each row. |
VarHandleOp | Creates a handle to a Variable resource. |
VarHandleOp.Options |
Optional attributes for
VarHandleOp
|
Variable <T> | Holds state in the form of a tensor that persists across steps. |
Variable.Options |
Optional attributes for
Variable
|
VariableShape <T extends Number> | Returns the shape of the variable pointed to by `resource`. |
VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
Where | Returns locations of nonzero / true values in a tensor. |
Where3 <T> | Selects elements from `x` or `y`, depending on `condition`. |
Window | |
WorkerHeartbeat | Worker heartbeat op. |
WrapDatasetVariant | |
WriteRawProtoSummary | Writes a serialized proto summary. |
XlaRecvFromHost <T> | An op to receive a tensor from the host. |
XlaSendToHost | An op to send a tensor to the host. |
Xlog1py <T> | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
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. |