Operand

public interface Operand

Known Indirect Subclasses

All, AllToAll<T>, Any, ApplyAdagradV2<T>, AssertCardinalityDataset, AssertNextDataset, Assign<T>, AssignAdd<T>, AssignSub<T>, AutoShardDataset, BandedTriangularSolve<T>, Barrier, BarrierIncompleteSize, BarrierReadySize, BatchMatMulV2<T>, and 355 others.

All	Computes the "logical and" of elements across dimensions of a tensor.
AllToAll<T>	An Op to exchange data across TPU replicas.
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.
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.
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.
CollectiveGather<T extends Number>	Mutually accumulates multiple tensors of identical type and shape.
CollectivePermute<T>	An Op to permute tensors across replicated TPU instances.
CollectiveReduceV2<T extends Number>	Mutually reduces multiple tensors of identical type and shape.
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.
Constant<T>	An operator producing a constant value.
Copy<T>	Copy a tensor from CPU-to-CPU or GPU-to-GPU.
CopyHost<T>	Copy a tensor to host.
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
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.
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.
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`.
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.
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.
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.
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.
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`.
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.
Output<T>	A symbolic handle to a tensor produced by an `Operation`.
Pad<T>	Pads a tensor.
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.
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.
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.
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.
Roll<T>	Rolls the elements of a tensor along an axis.
Rpc	Perform batches of RPC requests.
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>	Scatter `updates` into a new tensor 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.
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
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.
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`.
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.
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.
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.
TPUReplicatedInput<T>	Connects N inputs to an N-way replicated TPU computation.
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.
TensorForestTreeIsInitializedOp	Checks whether a tree has been initialized.
TensorForestTreePredict	Output the logits for the given input data
TensorForestTreeResourceHandleOp	Creates a handle to a TensorForestTreeResource
TensorForestTreeSerialize	Serializes the tree handle to a proto
TensorForestTreeSize	Get the number of nodes in a tree
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.
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.
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`.
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.
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.
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	Joins the elements of `inputs` based on `segment_ids`.
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`.
WorkerHeartbeat	Worker heartbeat op.
WrapDatasetVariant
XlaRecvFromHost<T>	An op to receive a tensor from 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.

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.

Operand

Public Methods

Public Methods

public abstract Output<T> asOutput ()

See Also