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. |
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. |
AnonymousMutableDenseHashTable.Options | Optional attributes for AnonymousMutableDenseHashTable
|
AnonymousMutableHashTable | Creates an empty anonymous mutable hash table. |
AnonymousMutableHashTableOfTensors | Creates an empty anonymous mutable hash table of vector values. |
AnonymousMutableHashTableOfTensors.Options | Optional attributes for AnonymousMutableHashTableOfTensors
|
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
|
ApproxTopK<T extends Number> | Returns min/max k values and their indices of the input operand in an approximate manner. |
ApproxTopK.Options | Optional attributes for ApproxTopK
|
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. |
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. |
AssignVariableOp.Options | Optional attributes for AssignVariableOp
|
AssignVariableXlaConcatND | Concats input tensor across all dimensions. |
AssignVariableXlaConcatND.Options | Optional attributes for AssignVariableXlaConcatND
|
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 | |
CacheDatasetV2.Options | Optional attributes for 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. |
CollectiveAllToAllV2.Options | Optional attributes for CollectiveAllToAllV2
|
CollectiveAllToAllV3<T extends Number> | Mutually exchanges multiple tensors of identical type and shape. |
CollectiveAllToAllV3.Options | Optional attributes for CollectiveAllToAllV3
|
CollectiveAssignGroupV2 | Assign group keys based on group assignment. |
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
|
CollectiveInitializeCommunicator | Initializes a group for collective operations. |
CollectiveInitializeCommunicator.Options | Optional attributes for CollectiveInitializeCommunicator
|
CollectivePermute<T> | An Op to permute tensors across replicated TPU instances. |
CollectiveReduceScatterV2<T extends Number> | Mutually reduces multiple tensors of identical type and shape and scatters the result. |
CollectiveReduceScatterV2.Options | Optional attributes for CollectiveReduceScatterV2
|
CollectiveReduceV2<T extends Number> | Mutually reduces multiple tensors of identical type and shape. |
CollectiveReduceV2.Options | Optional attributes for CollectiveReduceV2
|
CollectiveReduceV3<T extends Number> | Mutually reduces multiple tensors of identical type and shape. |
CollectiveReduceV3.Options | Optional attributes for CollectiveReduceV3
|
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. |
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. |
ConfigureAndInitializeGlobalTPU.Options | Optional attributes for ConfigureAndInitializeGlobalTPU
|
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. |
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. |
Conv<T extends Number> | Computes a N-D convolution given (N+1+batch_dims)-D `input` and (N+2)-D `filter` tensors. |
Conv.Options | Optional attributes for Conv
|
Conv2DBackpropFilterV2<T extends Number> | Computes the gradients of convolution with respect to the filter. |
Conv2DBackpropFilterV2.Options | Optional attributes for Conv2DBackpropFilterV2
|
Conv2DBackpropInputV2<T extends Number> | Computes the gradients of convolution with respect to the input. |
Conv2DBackpropInputV2.Options | Optional attributes for Conv2DBackpropInputV2
|
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
|
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. |
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`. |
DatasetCardinality.Options | Optional attributes for DatasetCardinality
|
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
|
DebugIdentityV3<T> | Provides an identity mapping of the non-Ref type input tensor for debugging. |
DebugIdentityV3.Options | Optional attributes for DebugIdentityV3
|
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
|
DisableCopyOnRead | Turns off the copy-on-read mode. |
DistributedSave | |
DistributedSave.Options | Optional attributes for DistributedSave
|
DrawBoundingBoxesV2<T extends Number> | Draw bounding boxes on a batch of images. |
DTensorRestoreV2 | |
DTensorSetGlobalTPUArray | An op that informs a host of the global ids of all the of TPUs in the system. |
DummyIterationCounter | |
DummyMemoryCache | |
DummySeedGenerator | |
DynamicEnqueueTPUEmbeddingArbitraryTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
DynamicEnqueueTPUEmbeddingArbitraryTensorBatch.Options | Optional attributes for DynamicEnqueueTPUEmbeddingArbitraryTensorBatch
|
DynamicEnqueueTPUEmbeddingRaggedTensorBatch | |
DynamicEnqueueTPUEmbeddingRaggedTensorBatch.Options | Optional attributes for DynamicEnqueueTPUEmbeddingRaggedTensorBatch
|
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
|
EnqueueTPUEmbeddingArbitraryTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
EnqueueTPUEmbeddingArbitraryTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingArbitraryTensorBatch
|
EnqueueTPUEmbeddingBatch | An op that enqueues a list of input batch tensors to TPUEmbedding. |
EnqueueTPUEmbeddingBatch.Options | Optional attributes for EnqueueTPUEmbeddingBatch
|
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
|
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. |
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. |
FFTND<T> | ND fast Fourier transform. |
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`. |
FinalizeDataset.Options | Optional attributes for FinalizeDataset
|
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. |
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
|
GetElementAtIndex | Gets the element at the specified index in a dataset. |
GetOptions | Returns the tf.data.Options attached to `input_dataset`. |
GetSessionHandle | Store the input tensor in the state of the current session. |
GetSessionTensor<T> | Get the value of the tensor specified by its handle. |
Gradients | Adds operations to compute the partial derivatives of sum of y s w.r.t x s,
i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2...
If |
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. |
IFFTND<T> | ND inverse fast Fourier transform. |
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'. |
IRFFTND<U extends Number> | ND inverse real fast Fourier transform. |
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. |
IsTPUEmbeddingInitialized | Whether TPU Embedding is initialized in a distributed TPU system. |
IsTPUEmbeddingInitialized.Options | Optional attributes for IsTPUEmbeddingInitialized
|
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. |
ListDataset | Creates a dataset that emits each of `tensors` once. |
ListDataset.Options | Optional attributes for ListDataset
|
LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
LoadAllTPUEmbeddingParameters | An op that loads optimization parameters into embedding memory. |
LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
LoadTPUEmbeddingAdadeltaParameters.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParameters
|
LoadTPUEmbeddingAdagradMomentumParameters | Load Adagrad Momentum embedding parameters. |
LoadTPUEmbeddingAdagradMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradMomentumParameters
|
LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
LoadTPUEmbeddingAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradParameters
|
LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
LoadTPUEmbeddingADAMParameters.Options | Optional attributes for LoadTPUEmbeddingADAMParameters
|
LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
LoadTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters
|
LoadTPUEmbeddingFrequencyEstimatorParameters | Load frequency estimator embedding parameters. |
LoadTPUEmbeddingFrequencyEstimatorParameters.Options | Optional attributes for LoadTPUEmbeddingFrequencyEstimatorParameters
|
LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
LoadTPUEmbeddingFTRLParameters.Options | Optional attributes for LoadTPUEmbeddingFTRLParameters
|
LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
LoadTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters
|
LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
LoadTPUEmbeddingMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingMomentumParameters
|
LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
LoadTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParameters
|
LoadTPUEmbeddingProximalYogiParameters | |
LoadTPUEmbeddingProximalYogiParameters.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParameters
|
LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
LoadTPUEmbeddingRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingRMSPropParameters
|
LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters
|
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`. |
MergeDedupData | An op merges elements of integer and float tensors into deduplication data as XLA tuple. |
MergeDedupData.Options | Optional attributes for MergeDedupData
|
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`. |
OptionsDataset.Options | Optional attributes for OptionsDataset
|
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. |
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. |
RandomDatasetV2.Options | Optional attributes for RandomDatasetV2
|
RandomIndexShuffle<T extends Number> | Outputs the position of `value` in a permutation of [0, ..., max_index]. |
RandomIndexShuffle.Options | Optional attributes for RandomIndexShuffle
|
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. |
ReadVariableXlaSplitND.Options | Optional attributes for ReadVariableXlaSplitND
|
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. |