Operand

public interface Operand

Known Indirect Subclasses All, AllToAll<T>, AnonymousHashTable, AnonymousIteratorV3, AnonymousMultiDeviceIteratorV3, AnonymousMutableDenseHashTable, AnonymousMutableHashTable, AnonymousMutableHashTableOfTensors, Any, ApplyAdagradV2<T>, AssertCardinalityDataset, AssertNextDataset, AssertPrevDataset, Assign<T>, AssignAdd<T>, and 475 others. All Computes the "logical and" of elements across dimensions of a tensor.  AllToAll<T> An Op to exchange data across TPU replicas.  AnonymousHashTable Creates a uninitialized anonymous hash table.  AnonymousIteratorV3 A container for an iterator resource.  AnonymousMultiDeviceIteratorV3 A container for a multi device iterator resource.  AnonymousMutableDenseHashTable Creates an empty anonymous mutable hash table that uses tensors as the backing store.  AnonymousMutableHashTable Creates an empty anonymous mutable hash table.  AnonymousMutableHashTableOfTensors Creates an empty anonymous mutable hash table of vector values.  Any Computes the "logical or" of elements across dimensions of a tensor.  ApplyAdagradV2<T> Update '*var' according to the adagrad scheme.  AssertCardinalityDataset   AssertNextDataset A transformation that asserts which transformations happen next.  AssertPrevDataset A transformation that asserts which transformations happened previously.  Assign<T> Update 'ref' by assigning 'value' to it.  AssignAdd<T> Update 'ref' by adding 'value' to it.  AssignSub<T> Update 'ref' by subtracting 'value' from it.  AutoShardDataset Creates a dataset that shards the input dataset.  BandedTriangularSolve<T>   Barrier Defines a barrier that persists across different graph executions.  BarrierIncompleteSize Computes the number of incomplete elements in the given barrier.  BarrierReadySize Computes the number of complete elements in the given barrier.  BatchMatMulV2<T> Multiplies slices of two tensors in batches.  BatchMatMulV3<V> Multiplies slices of two tensors in batches.  BatchToSpace<T> BatchToSpace for 4-D tensors of type T.  BatchToSpaceNd<T> BatchToSpace for N-D tensors of type T.  BesselI0<T extends Number>   BesselI1<T extends Number>   BesselJ0<T extends Number>   BesselJ1<T extends Number>   BesselK0<T extends Number>   BesselK0e<T extends Number>   BesselK1<T extends Number>   BesselK1e<T extends Number>   BesselY0<T extends Number>   BesselY1<T extends Number>   Bitcast<U> Bitcasts a tensor from one type to another without copying data.  BoostedTreesAggregateStats Aggregates the summary of accumulated stats for the batch.  BoostedTreesCenterBias Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior.  BoostedTreesEnsembleResourceHandleOp Creates a handle to a BoostedTreesEnsembleResource   BoostedTreesExampleDebugOutputs Debugging/model interpretability outputs for each example.  BoostedTreesMakeStatsSummary Makes the summary of accumulated stats for the batch.  BoostedTreesPredict Runs multiple additive regression ensemble predictors on input instances and computes the logits.  BoostedTreesQuantileStreamResourceHandleOp Creates a handle to a BoostedTreesQuantileStreamResource.  BroadcastDynamicShape<T extends Number> Return the shape of s0 op s1 with broadcast.  BroadcastTo<T> Broadcast an array for a compatible shape.  Bucketize Bucketizes 'input' based on 'boundaries'.  CSRSparseMatrixToDense<T> Convert a (possibly batched) CSRSparseMatrix to dense.  CSVDataset   CSVDatasetV2   CacheDatasetV2   CheckNumericsV2<T extends Number> Checks a tensor for NaN, -Inf and +Inf values.  ChooseFastestDataset   ClipByValue<T> Clips tensor values to a specified min and max.  CollateTPUEmbeddingMemory An op that merges the string-encoded memory config protos from all hosts.  CollectiveAllToAllV2<T extends Number> Mutually exchanges multiple tensors of identical type and shape.  CollectiveAllToAllV3<T extends Number> Mutually exchanges multiple tensors of identical type and shape.  CollectiveBcastRecvV2<U> Receives a tensor value broadcast from another device.  CollectiveBcastSendV2<T> Broadcasts a tensor value to one or more other devices.  CollectiveGather<T extends Number> Mutually accumulates multiple tensors of identical type and shape.  CollectiveGatherV2<T extends Number> Mutually accumulates multiple tensors of identical type and shape.  CollectiveInitializeCommunicator Initializes a group for collective operations.  CollectivePermute<T> An Op to permute tensors across replicated TPU instances.  CollectiveReduceScatterV2<T extends Number> Mutually reduces multiple tensors of identical type and shape and scatters the result.  CollectiveReduceV2<T extends Number> Mutually reduces multiple tensors of identical type and shape.  CollectiveReduceV3<T extends Number> Mutually reduces multiple tensors of identical type and shape.  CompositeTensorVariantFromComponents Encodes an `ExtensionType` value into a `variant` scalar Tensor.  CompressElement Compresses a dataset element.  ComputeBatchSize Computes the static batch size of a dataset sans partial batches.  ComputeDedupDataTupleMask An op computes tuple mask of deduplication data from embedding core.  Concat<T> Concatenates tensors along one dimension.  ConfigureAndInitializeGlobalTPU An op that sets up the centralized structures for a distributed TPU system.  ConfigureDistributedTPU Sets up the centralized structures for a distributed TPU system.  ConfigureTPUEmbeddingHost An op that configures the TPUEmbedding software on a host.  ConfigureTPUEmbeddingMemory An op that configures the TPUEmbedding software on a host.  Constant<T> An operator producing a constant value.  Conv2DBackpropFilterV2<T extends Number> Computes the gradients of convolution with respect to the filter.  Conv2DBackpropInputV2<T extends Number> Computes the gradients of convolution with respect to the input.  Copy<T> Copy a tensor from CPU-to-CPU or GPU-to-GPU.  CopyHost<T> Copy a tensor to host.  CopyToMesh<T>   CopyToMeshGrad<T>   CountUpTo<T extends Number> Increments 'ref' until it reaches 'limit'.  CrossReplicaSum<T extends Number> An Op to sum inputs across replicated TPU instances.  CudnnRNNCanonicalToParamsV2<T extends Number> Converts CudnnRNN params from canonical form to usable form.  CumulativeLogsumexp<T extends Number> Compute the cumulative product of the tensor `x` along `axis`.  DataServiceDataset Creates a dataset that reads data from the tf.data service.  DataServiceDatasetV2 Creates a dataset that reads data from the tf.data service.  DatasetCardinality Returns the cardinality of `input_dataset`.  DatasetFromGraph Creates a dataset from the given `graph_def`.  DatasetToGraphV2 Returns a serialized GraphDef representing `input_dataset`.  Dawsn<T extends Number>   DebugGradientIdentity<T> Identity op for gradient debugging.  DebugGradientRefIdentity<T> Identity op for gradient debugging.  DebugIdentity<T> Provides an identity mapping of the non-Ref type input tensor for debugging.  DebugIdentityV2<T> Debug Identity V2 Op.  DebugNanCount Debug NaN Value Counter Op.  DebugNumericSummary Debug Numeric Summary Op.  DebugNumericSummaryV2<U extends Number> Debug Numeric Summary V2 Op.  DecodeImage<T extends Number> Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.  DecodePaddedRaw<T extends Number> Reinterpret the bytes of a string as a vector of numbers.  DeepCopy<T> Makes a copy of `x`.  DenseBincount<U extends Number> Counts the number of occurrences of each value in an integer array.  DenseToCSRSparseMatrix Converts a dense tensor to a (possibly batched) CSRSparseMatrix.  DestroyTemporaryVariable<T> Destroys the temporary variable and returns its final value.  DeviceIndex Return the index of device the op runs.  DirectedInterleaveDataset A substitute for `InterleaveDataset` on a fixed list of `N` datasets.  DrawBoundingBoxesV2<T extends Number> Draw bounding boxes on a batch of images.  DummyIterationCounter   DummyMemoryCache   DummySeedGenerator   DynamicStitch<T> Interleave the values from the `data` tensors into a single tensor.  EditDistance Computes the (possibly normalized) Levenshtein Edit Distance.  Einsum<T> Tensor contraction according to Einstein summation convention.  Empty<T> Creates a tensor with the given shape.  EmptyTensorList Creates and returns an empty tensor list.  EmptyTensorMap Creates and returns an empty tensor map.  EncodeProto The op serializes protobuf messages provided in the input tensors.  EnsureShape<T> Ensures that the tensor's shape matches the expected shape.  Enter<T> Creates or finds a child frame, and makes `data` available to the child frame.  Erfinv<T extends Number>   EuclideanNorm<T> Computes the euclidean norm of elements across dimensions of a tensor.  ExecuteTPUEmbeddingPartitioner An op that executes the TPUEmbedding partitioner on the central configuration device and computes the HBM size (in bytes) required for TPUEmbedding operation.  Exit<T> Exits the current frame to its parent frame.  ExpandDims<T> Inserts a dimension of 1 into a tensor's shape.  ExperimentalAutoShardDataset Creates a dataset that shards the input dataset.  ExperimentalBytesProducedStatsDataset Records the bytes size of each element of `input_dataset` in a StatsAggregator.  ExperimentalChooseFastestDataset   ExperimentalDatasetCardinality Returns the cardinality of `input_dataset`.  ExperimentalDenseToSparseBatchDataset Creates a dataset that batches input elements into a SparseTensor.  ExperimentalLatencyStatsDataset Records the latency of producing `input_dataset` elements in a StatsAggregator.  ExperimentalMatchingFilesDataset   ExperimentalMaxIntraOpParallelismDataset Creates a dataset that overrides the maximum intra-op parallelism.  ExperimentalParseExampleDataset Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.  ExperimentalPrivateThreadPoolDataset Creates a dataset that uses a custom thread pool to compute `input_dataset`.  ExperimentalRandomDataset Creates a Dataset that returns pseudorandom numbers.  ExperimentalRebatchDataset Creates a dataset that changes the batch size.  ExperimentalSetStatsAggregatorDataset   ExperimentalSlidingWindowDataset Creates a dataset that passes a sliding window over `input_dataset`.  ExperimentalSqlDataset Creates a dataset that executes a SQL query and emits rows of the result set.  ExperimentalStatsAggregatorHandle Creates a statistics manager resource.  ExperimentalStatsAggregatorSummary Produces a summary of any statistics recorded by the given statistics manager.  ExperimentalUnbatchDataset A dataset that splits the elements of its input into multiple elements.  Expint<T extends Number>   ExtractGlimpseV2 Extracts a glimpse from the input tensor.  ExtractVolumePatches<T extends Number> Extract `patches` from `input` and put them in the `"depth"` output dimension.  Fill<U> Creates a tensor filled with a scalar value.  FinalizeDataset Creates a dataset by applying tf.data.Options to `input_dataset`.  Fingerprint Generates fingerprint values.  FresnelCos<T extends Number>   FresnelSin<T extends Number>   Gather<T> Gather slices from `params` axis `axis` according to `indices`.  GatherNd<T> Gather slices from `params` into a Tensor with shape specified by `indices`.  GetOptions Returns the tf.data.Options attached to `input_dataset`.  GetSessionHandle Store the input tensor in the state of the current session.  GetSessionTensor<T> Get the value of the tensor specified by its handle.  GuaranteeConst<T> Gives a guarantee to the TF runtime that the input tensor is a constant.  HashTable Creates a non-initialized hash table.  HistogramFixedWidth<U extends Number> Return histogram of values.  Identity<T> Return a tensor with the same shape and contents as the input tensor or value.  IgnoreErrorsDataset Creates a dataset that contains the elements of `input_dataset` ignoring errors.  ImageProjectiveTransformV2<T extends Number> Applies the given transform to each of the images.  ImageProjectiveTransformV3<T extends Number> Applies the given transform to each of the images.  ImmutableConst<T> Returns immutable tensor from memory region.  InfeedDequeue<T> A placeholder op for a value that will be fed into the computation.  InplaceAdd<T> Adds v into specified rows of x.  InplaceSub<T> Subtracts `v` into specified rows of `x`.  InplaceUpdate<T> Updates specified rows 'i' with values 'v'.  IsBoostedTreesEnsembleInitialized Checks whether a tree ensemble has been initialized.  IsBoostedTreesQuantileStreamResourceInitialized Checks whether a quantile stream has been initialized.  IsTPUEmbeddingInitialized Whether TPU Embedding is initialized in a distributed TPU system.  IsVariableInitialized Checks whether a tensor has been initialized.  IteratorGetDevice Returns the name of the device on which `resource` has been placed.  KMC2ChainInitialization Returns the index of a data point that should be added to the seed set.  KmeansPlusPlusInitialization Selects num_to_sample rows of input using the KMeans++ criterion.  KthOrderStatistic Computes the Kth order statistic of a data set.  LMDBDataset Creates a dataset that emits the key-value pairs in one or more LMDB files.  LinSpace<T extends Number> Generates values in an interval.  ListDataset Creates a dataset that emits each of `tensors` once.  LookupTableFind<U> Looks up keys in a table, outputs the corresponding values.  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.  MakeUnique Make all elements in the non-Batch dimension unique, but \"close\" to their initial value.  MapIncompleteSize Op returns the number of incomplete elements in the underlying container.  MapSize Op returns the number of elements in the underlying container.  MatrixDiagPartV2<T> Returns the batched diagonal part of a batched tensor.  MatrixDiagPartV3<T> Returns the batched diagonal part of a batched tensor.  MatrixDiagV2<T> Returns a batched diagonal tensor with given batched diagonal values.  MatrixDiagV3<T> Returns a batched diagonal tensor with given batched diagonal values.  MatrixSetDiagV2<T> Returns a batched matrix tensor with new batched diagonal values.  MatrixSetDiagV3<T> Returns a batched matrix tensor with new batched diagonal values.  Max<T> Computes the maximum of elements across dimensions of a tensor.  MaxIntraOpParallelismDataset Creates a dataset that overrides the maximum intra-op parallelism.  MergeDedupData An op merges elements of integer and float tensors into deduplication data as XLA tuple.  Min<T> Computes the minimum of elements across dimensions of a tensor.  MirrorPad<T> Pads a tensor with mirrored values.  MirrorPadGrad<T> Gradient op for `MirrorPad` op.  MulNoNan<T> Returns x * y element-wise.  MutableDenseHashTable Creates an empty hash table that uses tensors as the backing store.  MutableHashTable Creates an empty hash table.  MutableHashTableOfTensors Creates an empty hash table.  Mutex Creates a Mutex resource that can be locked by `MutexLock`.  MutexLock Locks a mutex resource.  NcclAllReduce<T extends Number> Outputs a tensor containing the reduction across all input tensors.  NcclBroadcast<T extends Number> Sends `input` to all devices that are connected to the output.  NcclReduce<T extends Number> Reduces `input` from `num_devices` using `reduction` to a single device.  Ndtri<T extends Number>   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.  NonSerializableDataset   OneHot<U> Returns a one-hot tensor.  OnesLike<T> Returns a tensor of ones with the same shape and type as x.  OptimizeDatasetV2 Creates a dataset by applying related optimizations to `input_dataset`.  OptionsDataset Creates a dataset by attaching tf.data.Options to `input_dataset`.  OrderedMapIncompleteSize Op returns the number of incomplete elements in the underlying container.  OrderedMapSize Op returns the number of elements in the underlying container.  OutfeedDequeue<T> Retrieves a single tensor from the computation outfeed.  OutfeedDequeueV2<T> Retrieves a single tensor from the computation outfeed.  Output<T> A symbolic handle to a tensor produced by an Operation.  Pad<T> Pads a tensor.  ParallelBatchDataset   ParallelConcat<T> Concatenates a list of `N` tensors along the first dimension.  ParallelDynamicStitch<T> Interleave the values from the `data` tensors into a single tensor.  ParseExampleDatasetV2 Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.  Placeholder<T> A placeholder op for a value that will be fed into the computation.  PlaceholderWithDefault<T> A placeholder op that passes through `input` when its output is not fed.  Prelinearize An op which linearizes one Tensor value to an opaque variant tensor.  PrelinearizeTuple An op which linearizes multiple Tensor values to an opaque variant tensor.  PrivateThreadPoolDataset Creates a dataset that uses a custom thread pool to compute `input_dataset`.  Prod<T> Computes the product of elements across dimensions of a tensor.  QuantizeAndDequantizeV4<T extends Number> Quantizes then dequantizes a tensor.  QuantizedMatMulWithBiasAndDequantize<W extends Number>   RaggedBincount<U extends Number> Counts the number of occurrences of each value in an integer array.  RaggedTensorToTensor<U> Create a dense tensor from a ragged tensor, possibly altering its shape.  RaggedTensorToVariant Encodes a `RaggedTensor` into a `variant` Tensor.  RaggedTensorToVariantGradient<U> Helper used to compute the gradient for `RaggedTensorToVariant`.  RandomDatasetV2 Creates a Dataset that returns pseudorandom numbers.  RandomIndexShuffle<T extends Number> Outputs the position of `value` in a permutation of [0, ..., max_index].  Range<T extends Number> Creates a sequence of numbers.  Rank Returns the rank of a tensor.  ReadVariableOp<T> Reads the value of a variable.  RebatchDataset Creates a dataset that changes the batch size.  RebatchDatasetV2 Creates a dataset that changes the batch size.  Recv<T> Receives the named tensor from send_device on recv_device.  ReduceAll Computes the "logical and" of elements across dimensions of a tensor.  ReduceAny Computes the "logical or" of elements across dimensions of a tensor.  ReduceMax<T> Computes the maximum of elements across dimensions of a tensor.  ReduceMin<T> Computes the minimum of elements across dimensions of a tensor.  ReduceProd<T> Computes the product of elements across dimensions of a tensor.  ReduceSum<T> Computes the sum of elements across dimensions of a tensor.  RefEnter<T> Creates or finds a child frame, and makes `data` available to the child frame.  RefExit<T> Exits the current frame to its parent frame.  RefIdentity<T> Return the same ref tensor as the input ref tensor.  RefNextIteration<T> Makes its input available to the next iteration.  RefSelect<T> Forwards the `index`th element of `inputs` to `output`.  RegisterDataset Registers a dataset with the tf.data service.  RegisterDatasetV2 Registers a dataset with the tf.data service.  Relayout<T>   RelayoutGrad<T>   Reshape<T> Reshapes a tensor.  ResourceAccumulatorNumAccumulated Returns the number of gradients aggregated in the given accumulators.  ResourceAccumulatorTakeGradient<T> Extracts the average gradient in the given ConditionalAccumulator.  ResourceConditionalAccumulator A conditional accumulator for aggregating gradients.  ResourceCountUpTo<T extends Number> Increments variable pointed to by 'resource' until it reaches 'limit'.  ResourceGather<U> Gather slices from the variable pointed to by `resource` according to `indices`.  ResourceGatherNd<U>   RetrieveTPUEmbeddingStochasticGradientDescentParameters Retrieve SGD embedding parameters.  Reverse<T> Reverses specific dimensions of a tensor.  ReverseSequence<T> Reverses variable length slices.  RewriteDataset   RiscAbs<T extends Number>   RiscAdd<T extends Number> Returns x + y element-wise.  RiscBinaryArithmetic<T extends Number>   RiscBinaryComparison   RiscBitcast<U>   RiscBroadcast<T>   RiscCast<U>   RiscCeil<T extends Number>   RiscCholesky<T extends Number>   RiscConcat<T>   RiscConv<T extends Number>   RiscCos<T extends Number>   RiscDiv<T extends Number>   RiscDot<T extends Number>   RiscExp<T extends Number>   RiscFft<T>   RiscFloor<T extends Number>   RiscGather<T>   RiscImag<U extends Number>   RiscIsFinite   RiscLog<T extends Number>   RiscLogicalAnd   RiscLogicalNot   RiscLogicalOr   RiscMax<T extends Number> Returns max(x, y) element-wise.  RiscMin<T extends Number>   RiscMul<T extends Number>   RiscNeg<T extends Number>   RiscPad<T extends Number>   RiscPool<T extends Number>   RiscPow<T extends Number>   RiscRandomUniform   RiscReal<U extends Number>   RiscReduce<T extends Number>   RiscRem<T extends Number>   RiscReshape<T extends Number>   RiscReverse<T extends Number>   RiscScatter<U extends Number>   RiscShape<U extends Number>   RiscSign<T extends Number>   RiscSlice<T extends Number>   RiscSort<T extends Number>   RiscSqueeze<T>   RiscSub<T extends Number>   RiscTranspose<T>   RiscTriangularSolve<T extends Number>   RiscUnary<T extends Number>   RngReadAndSkip Advance the counter of a counter-based RNG.  Roll<T> Rolls the elements of a tensor along an axis.  SamplingDataset Creates a dataset that takes a Bernoulli sample of the contents of another dataset.  ScaleAndTranslate   ScaleAndTranslateGrad<T extends Number>   ScatterAdd<T> Adds sparse updates to a variable reference.  ScatterDiv<T> Divides a variable reference by sparse updates.  ScatterMax<T extends Number> Reduces sparse updates into a variable reference using the `max` operation.  ScatterMin<T extends Number> Reduces sparse updates into a variable reference using the `min` operation.  ScatterMul<T> Multiplies sparse updates into a variable reference.  ScatterNd<U> Scatters `updates` into a tensor of shape `shape` according to `indices`.  ScatterNdAdd<T> Applies sparse addition to individual values or slices in a Variable.  ScatterNdMax<T> Computes element-wise maximum.  ScatterNdMin<T> Computes element-wise minimum.  ScatterNdNonAliasingAdd<T> Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`.  ScatterNdSub<T> Applies sparse subtraction to individual values or slices in a Variable.  ScatterNdUpdate<T> Applies sparse `updates` to individual values or slices within a given variable according to `indices`.  ScatterSub<T> Subtracts sparse updates to a variable reference.  ScatterUpdate<T> Applies sparse updates to a variable reference.  SegmentMaxV2<T extends Number> Computes the maximum along segments of a tensor.  SegmentMinV2<T extends Number> Computes the minimum along segments of a tensor.  SegmentProdV2<T> Computes the product along segments of a tensor.  SegmentSumV2<T> Computes the sum along segments of a tensor.  SelectV2<T>   SetSize Number of unique elements along last dimension of input `set`.  Shape<U extends Number> Returns the shape of a tensor.  ShardDataset Creates a `Dataset` that includes only 1/`num_shards` of this dataset.  ShuffleAndRepeatDatasetV2   ShuffleDatasetV2   ShuffleDatasetV3   ShutdownTPUSystem An op that shuts down the TPU system.  Size<U extends Number> Returns the size of a tensor.  SleepDataset   Slice<T> Return a slice from 'input'.  SlidingWindowDataset Creates a dataset that passes a sliding window over `input_dataset`.  Snapshot<T> Returns a copy of the input tensor.  SnapshotDataset Creates a dataset that will write to / read from a snapshot.  SnapshotDatasetReader   SnapshotNestedDatasetReader   SobolSample<T extends Number> Generates points from the Sobol sequence.  SpaceToBatchNd<T> SpaceToBatch for N-D tensors of type T.  SparseApplyAdagradV2<T> Update relevant entries in '*var' and '*accum' according to the adagrad scheme.  SparseBincount<U extends Number> Counts the number of occurrences of each value in an integer array.  SparseMatrixAdd Sparse addition of two CSR matrices, C = alpha * A + beta * B.  SparseMatrixMatMul<T> Matrix-multiplies a sparse matrix with a dense matrix.  SparseMatrixMul Element-wise multiplication of a sparse matrix with a dense tensor.  SparseMatrixNNZ Returns the number of nonzeroes of `sparse_matrix`.  SparseMatrixOrderingAMD Computes the Approximate Minimum Degree (AMD) ordering of `input`.  SparseMatrixSoftmax Calculates the softmax of a CSRSparseMatrix.  SparseMatrixSoftmaxGrad Calculates the gradient of the SparseMatrixSoftmax op.  SparseMatrixSparseCholesky Computes the sparse Cholesky decomposition of `input`.  SparseMatrixSparseMatMul Sparse-matrix-multiplies two CSR matrices `a` and `b`.  SparseMatrixTranspose Transposes the inner (matrix) dimensions of a CSRSparseMatrix.  SparseMatrixZeros Creates an all-zeros CSRSparseMatrix with shape `dense_shape`.  SparseSegmentSumGrad<T extends Number> Computes gradients for SparseSegmentSum.  SparseTensorToCSRSparseMatrix Converts a SparseTensor to a (possibly batched) CSRSparseMatrix.  Spence<T extends Number>   Squeeze<T> Removes dimensions of size 1 from the shape of a tensor.  Stack<T> Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.  StageSize Op returns the number of elements in the underlying container.  StatefulRandomBinomial<V extends Number>   StatefulStandardNormal<U> Outputs random values from a normal distribution.  StatefulStandardNormalV2<U> Outputs random values from a normal distribution.  StatefulTruncatedNormal<U> Outputs random values from a truncated normal distribution.  StatefulUniform<U> Outputs random values from a uniform distribution.  StatefulUniformFullInt<U> Outputs random integers from a uniform distribution.  StatefulUniformInt<U> Outputs random integers from a uniform distribution.  StatelessParameterizedTruncatedNormal<V extends Number>   StatelessRandomBinomial<W extends Number> Outputs deterministic pseudorandom random numbers from a binomial distribution.  StatelessRandomGammaV2<V extends Number> Outputs deterministic pseudorandom random numbers from a gamma distribution.  StatelessRandomGammaV3<U extends Number> Outputs deterministic pseudorandom random numbers from a gamma distribution.  StatelessRandomGetAlg Picks the best counter-based RNG algorithm based on device.  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.  StatelessShuffle<T> Randomly and deterministically shuffles a tensor along its first dimension.  StatelessTruncatedNormalV2<U extends Number> Outputs deterministic pseudorandom values from a truncated normal distribution.  StatsAggregatorHandleV2   StopGradient<T> Stops gradient computation.  StridedSlice<T> Return a strided slice from `input`.  StridedSliceAssign<T> Assign `value` to the sliced l-value reference of `ref`.  StridedSliceGrad<U> Returns the gradient of `StridedSlice`.  StringLower Converts all uppercase characters into their respective lowercase replacements.  StringUpper Converts all lowercase characters into their respective uppercase replacements.  Sum<T> Computes the sum of elements across dimensions of a tensor.  TPUCompilationResult Returns the result of a TPU compilation.  TPUEmbeddingActivations An op enabling differentiation of TPU Embeddings.  TPUOrdinalSelector A TPU core selector Op.  TPUPartitionedInput<T> An op that groups a list of partitioned inputs together.  TPUPartitionedInputV2<T> An op that groups a list of partitioned inputs together.  TPUReplicatedInput<T> Connects N inputs to an N-way replicated TPU computation.  TPURoundRobin Round-robin load balancing on TPU cores.  TemporaryVariable<T> Returns a tensor that may be mutated, but only persists within a single step.  TensorArrayGather<T> Gather specific elements from the TensorArray into output `value`.  TensorArrayPack<T>   TensorArrayRead<T> Read an element from the TensorArray into output `value`.  TensorArrayScatter Scatter the data from the input value into specific TensorArray elements.  TensorArraySize Get the current size of the TensorArray.  TensorArraySplit Split the data from the input value into TensorArray elements.  TensorArrayUnpack   TensorArrayWrite Push an element onto the tensor_array.  TensorListConcatLists   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.  TensorListPushBack Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`.  TensorListPushBackBatch   TensorListReserve List of the given size with empty elements.  TensorListResize Resizes the list.  TensorListScatter Creates a TensorList by indexing into a Tensor.  TensorListScatterIntoExistingList Scatters tensor at indices in an input list.  TensorListScatterV2 Creates a TensorList by indexing into a Tensor.  TensorListSetItem   TensorListSplit Splits a tensor into a list.  TensorListStack<T> Stacks all tensors in the list.  TensorMapErase Returns a tensor map with item from given key erased.  TensorMapHasKey Returns whether the given key exists in the map.  TensorMapInsert Returns a map that is the 'input_handle' with the given key-value pair inserted.  TensorMapLookup<U> Returns the value from a given key in a tensor map.  TensorMapSize Returns the number of tensors in the input tensor map.  TensorMapStackKeys<T> Returns a Tensor stack of all keys in a tensor map.  TensorScatterAdd<T> Adds sparse `updates` to an existing tensor according to `indices`.  TensorScatterMax<T> Apply a sparse update to a tensor taking the element-wise maximum.  TensorScatterMin<T>   TensorScatterSub<T> Subtracts sparse `updates` from an existing tensor according to `indices`.  TensorScatterUpdate<T> Scatter `updates` into an existing tensor according to `indices`.  TensorStridedSliceUpdate<T> Assign `value` to the sliced l-value reference of `input`.  ThreadPoolDataset Creates a dataset that uses a custom thread pool to compute `input_dataset`.  ThreadPoolHandle Creates a dataset that uses a custom thread pool to compute `input_dataset`.  Tile<T> Constructs a tensor by tiling a given tensor.  Timestamp Provides the time since epoch in seconds.  ToBool Converts a tensor to a scalar predicate.  TpuHandleToProtoKey Converts XRT's uid handles to TensorFlow-friendly input format.  TridiagonalMatMul<T> Calculate product with tridiagonal matrix.  TridiagonalSolve<T> Solves tridiagonal systems of equations.  Unbatch<T> Reverses the operation of Batch for a single output Tensor.  UnbatchGrad<T> Gradient of Unbatch.  UnicodeEncode Encode a tensor of ints into unicode strings.  UniformDequantize<U extends Number> Perform dequantization on the quantized Tensor `input`.  UniformQuantize<U> Perform quantization on Tensor `input`.  UniformQuantizedAdd<T> Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.  UniformQuantizedClipByValue<T> Perform clip by value on the quantized Tensor `operand`.  UniformQuantizedConvolution<U> Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`.  UniformQuantizedConvolutionHybrid<V extends Number> Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`.  UniformQuantizedDot<U> Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.  UniformQuantizedDotHybrid<V extends Number> Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`.  UniformRequantize<U> Given quantized tensor `input`, requantize it with new quantization parameters.  UniqueDataset Creates a dataset that contains the unique elements of `input_dataset`.  UnravelIndex<T extends Number> Converts an array of flat indices into a tuple of coordinate arrays.  UnsortedSegmentJoin   UnwrapDatasetVariant   UpperBound<U extends Number> Applies upper_bound(sorted_search_values, values) along each row.  VarHandleOp Creates a handle to a Variable resource.  VarIsInitializedOp Checks whether a resource handle-based variable has been initialized.  Variable<T> Holds state in the form of a tensor that persists across steps.  VariableShape<T extends Number> Returns the shape of the variable pointed to by `resource`.  Where Returns locations of nonzero / true values in a tensor.  Where3<T> Selects elements from `x` or `y`, depending on `condition`.  WindowOp   WorkerHeartbeat Worker heartbeat op.  WrapDatasetVariant   XlaConcatND<T> Concats input tensor across all dimensions.  XlaRecvFromHost<T> An op to receive a tensor from the host.  XlaRecvTPUEmbeddingDeduplicationData Receives deduplication data (indices and weights) from the embedding core.  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.

Interface implemented by operands of a TensorFlow operation.

Example usage:

// The "decodeJpeg" operation can be used as an operand to the "cast" operation
 Operand<UInt8> decodeJpeg = ops.image().decodeJpeg(...);
 ops.math().cast(decodeJpeg, DataType.FLOAT);

 // The output "y" of the "unique" operation can be used as an operand to the "cast" operation
 Output<Integer> y = ops.array().unique(...).y();
 ops.math().cast(y, Float.class);

 // The "split" operation can be used as operand list to the "concat" operation
 Iterable<? extends Operand<Float>> split = ops.array().split(...);
 ops.array().concat(0, split);
 

Public Methods

abstract Output<T>

asOutput() Returns the symbolic handle of a tensor.

Public Methods

public abstract Output<T> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

See Also

• OperationBuilder.addInput(Output)