Operand

public interface Operand

Known Indirect Subclasses

Abs<T extends TNumber>, AccumulateN<T extends TType>, AccumulatorNumAccumulated, AccumulatorTakeGradient<T extends TType>, Acos<T extends TType>, Acosh<T extends TType>, Add<T extends TType>, AddManySparseToTensorsMap, AddN<T extends TType>, AddSparseToTensorsMap, AdjustContrast<T extends TNumber>, AdjustHue<T extends TNumber>, AdjustSaturation<T extends TNumber>, All, AllReduce<T extends TNumber>, and 774 others.

Abs<T extends TNumber>	Computes the absolute value of a tensor.
AccumulateN<T extends TType>	Returns the element-wise sum of a list of tensors.
AccumulatorNumAccumulated	Returns the number of gradients aggregated in the given accumulators.
AccumulatorTakeGradient<T extends TType>	Extracts the average gradient in the given ConditionalAccumulator.
Acos<T extends TType>	Computes acos of x element-wise.
Acosh<T extends TType>	Computes inverse hyperbolic cosine of x element-wise.
Add<T extends TType>	Returns x + y element-wise.
AddManySparseToTensorsMap	Add an `N`-minibatch `SparseTensor` to a `SparseTensorsMap`, return `N` handles.
AddN<T extends TType>	Add all input tensors element wise.
AddSparseToTensorsMap	Add a `SparseTensor` to a `SparseTensorsMap` return its handle.
AdjustContrast<T extends TNumber>	Adjust the contrast of one or more images.
AdjustHue<T extends TNumber>	Adjust the hue of one or more images.
AdjustSaturation<T extends TNumber>	Adjust the saturation of one or more images.
All	Computes the "logical and" of elements across dimensions of a tensor.
AllReduce<T extends TNumber>	Mutually reduces multiple tensors of identical type and shape.
AllToAll<T extends TType>	An Op to exchange data across TPU replicas.
Angle<U extends TNumber>	Returns the argument of a complex number.
Any	Computes the "logical or" of elements across dimensions of a tensor.
ApplyAdaMax<T extends TType>	Update '*var' according to the AdaMax algorithm.
ApplyAdadelta<T extends TType>	Update '*var' according to the adadelta scheme.
ApplyAdagrad<T extends TType>	Update '*var' according to the adagrad scheme.
ApplyAdagradDa<T extends TType>	Update '*var' according to the proximal adagrad scheme.
ApplyAdagradV2<T extends TType>	Update '*var' according to the adagrad scheme.
ApplyAdam<T extends TType>	Update '*var' according to the Adam algorithm.
ApplyAddSign<T extends TType>	Update '*var' according to the AddSign update.
ApplyCenteredRmsProp<T extends TType>	Update '*var' according to the centered RMSProp algorithm.
ApplyFtrl<T extends TType>	Update '*var' according to the Ftrl-proximal scheme.
ApplyGradientDescent<T extends TType>	Update 'var' by subtracting 'alpha' 'delta' from it.
ApplyMomentum<T extends TType>	Update '*var' according to the momentum scheme.
ApplyPowerSign<T extends TType>	Update '*var' according to the AddSign update.
ApplyProximalAdagrad<T extends TType>	Update 'var' and 'accum' according to FOBOS with Adagrad learning rate.
ApplyProximalGradientDescent<T extends TType>	Update '*var' as FOBOS algorithm with fixed learning rate.
ApplyRmsProp<T extends TType>	Update '*var' according to the RMSProp algorithm.
ApproximateEqual	Returns the truth value of abs(x-y) < tolerance element-wise.
ArgMax<V extends TNumber>	Returns the index with the largest value across dimensions of a tensor.
ArgMin<V extends TNumber>	Returns the index with the smallest value across dimensions of a tensor.
AsString	Converts each entry in the given tensor to strings.
Asin<T extends TType>	Computes the trignometric inverse sine of x element-wise.
Asinh<T extends TType>	Computes inverse hyperbolic sine of x element-wise.
AssertCardinalityDataset
AssertNextDataset
Assign<T extends TType>	Update 'ref' by assigning 'value' to it.
AssignAdd<T extends TType>	Update 'ref' by adding 'value' to it.
AssignSub<T extends TType>	Update 'ref' by subtracting 'value' from it.
Atan<T extends TType>	Computes the trignometric inverse tangent of x element-wise.
Atan2<T extends TNumber>	Computes arctangent of `y/x` element-wise, respecting signs of the arguments.
Atanh<T extends TType>	Computes inverse hyperbolic tangent of x element-wise.
AudioSpectrogram	Produces a visualization of audio data over time.
AudioSummary	Outputs a `Summary` protocol buffer with audio.
AutoShardDataset	Creates a dataset that shards the input dataset.
AvgPool<T extends TNumber>	Performs average pooling on the input.
AvgPool3d<T extends TNumber>	Performs 3D average pooling on the input.
AvgPool3dGrad<T extends TNumber>	Computes gradients of average pooling function.
AvgPoolGrad<T extends TNumber>	Computes gradients of the average pooling function.
BandPart<T extends TType>	Copy a tensor setting everything outside a central band in each innermost matrix to zero.
BandedTriangularSolve<T extends TType>
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.
BatchCholesky<T extends TNumber>
BatchCholeskyGrad<T extends TNumber>
BatchDataset	Creates a dataset that batches `batch_size` elements from `input_dataset`.
BatchFft
BatchFft2d
BatchFft3d
BatchIfft
BatchIfft2d
BatchIfft3d
BatchMatMul<T extends TType>	Multiplies slices of two tensors in batches.
BatchMatrixBandPart<T extends TType>
BatchMatrixDeterminant<T extends TType>
BatchMatrixDiag<T extends TType>
BatchMatrixDiagPart<T extends TType>
BatchMatrixInverse<T extends TNumber>
BatchMatrixSetDiag<T extends TType>
BatchMatrixSolve<T extends TNumber>
BatchMatrixSolveLs<T extends TNumber>
BatchMatrixTriangularSolve<T extends TNumber>
BatchNormWithGlobalNormalization<T extends TType>	Batch normalization.
BatchToSpace<T extends TType>	BatchToSpace for 4-D tensors of type T.
BatchToSpaceNd<T extends TType>	BatchToSpace for N-D tensors of type T.
BesselI0<T extends TNumber>
BesselI0e<T extends TNumber>
BesselI1<T extends TNumber>
BesselI1e<T extends TNumber>
BesselJ0<T extends TNumber>
BesselJ1<T extends TNumber>
BesselK0<T extends TNumber>
BesselK0e<T extends TNumber>
BesselK1<T extends TNumber>
BesselK1e<T extends TNumber>
BesselY0<T extends TNumber>
BesselY1<T extends TNumber>
Betainc<T extends TNumber>	Compute the regularized incomplete beta integral \\(I_x(a, b)\\).
BiasAdd<T extends TType>	Adds `bias` to `value`.
BiasAddGrad<T extends TType>	The backward operation for "BiasAdd" on the "bias" tensor.
Bincount<T extends TNumber>	Counts the number of occurrences of each value in an integer array.
Bitcast<U extends TType>	Bitcasts a tensor from one type to another without copying data.
BitwiseAnd<T extends TNumber>	Elementwise computes the bitwise AND of `x` and `y`.
BitwiseOr<T extends TNumber>	Elementwise computes the bitwise OR of `x` and `y`.
BitwiseXor<T extends TNumber>	Elementwise computes the bitwise XOR of `x` and `y`.
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 TNumber>	Return the shape of s0 op s1 with broadcast.
BroadcastRecv<T extends TType>	Receives a tensor value broadcast from another device.
BroadcastSend<T extends TType>	Broadcasts a tensor value to one or more other devices.
BroadcastTo<T extends TType>	Broadcast an array for a compatible shape.
Bucketize	Bucketizes 'input' based on 'boundaries'.
BytesProducedStatsDataset	Records the bytes size of each element of `input_dataset` in a StatsAggregator.
CSRSparseMatrixToDense<T extends TType>	Convert a (possibly batched) CSRSparseMatrix to dense.
CSVDataset
CSVDatasetV2
CacheDataset	Creates a dataset that caches elements from `input_dataset`.
CacheDatasetV2
Cast<U extends TType>	Cast x of type SrcT to y of DstT.
Ceil<T extends TNumber>	Returns element-wise smallest integer not less than x.
CheckNumerics<T extends TNumber>	Checks a tensor for NaN, -Inf and +Inf values.
Cholesky<T extends TType>	Computes the Cholesky decomposition of one or more square matrices.
CholeskyGrad<T extends TNumber>	Computes the reverse mode backpropagated gradient of the Cholesky algorithm.
ChooseFastestDataset
ClipByValue<T extends TType>	Clips tensor values to a specified min and max.
ClusterOutput<T extends TType>	Operator that connects the output of an XLA computation to other consumer graph nodes.
CollectiveGather<T extends TNumber>	Mutually accumulates multiple tensors of identical type and shape.
CollectivePermute<T extends TType>	An Op to permute tensors across replicated TPU instances.
CompareAndBitpack	Compare values of `input` to `threshold` and pack resulting bits into a `uint8`.
CompilationResult	Returns the result of a TPU compilation.
Complex<U extends TType>	Converts two real numbers to a complex number.
ComplexAbs<U extends TNumber>	Computes the complex absolute value of a tensor.
CompressElement	Compresses a dataset element.
ComputeBatchSize	Computes the static batch size of a dataset sans partial batches.
Concat<T extends TType>	Concatenates tensors along one dimension.
ConcatenateDataset	Creates a dataset that concatenates `input_dataset` with `another_dataset`.
ConditionalAccumulator	A conditional accumulator for aggregating gradients.
ConfigureDistributedTPU	Sets up the centralized structures for a distributed TPU system.
Conj<T extends TType>	Returns the complex conjugate of a complex number.
ConjugateTranspose<T extends TType>	Shuffle dimensions of x according to a permutation and conjugate the result.
Constant<T extends TType>	An operator producing a constant value.
Conv<T extends TType>	Wraps the XLA ConvGeneralDilated operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#conv_convolution .
Conv2d<T extends TNumber>	Computes a 2-D convolution given 4-D `input` and `filter` tensors.
Conv2dBackpropFilter<T extends TNumber>	Computes the gradients of convolution with respect to the filter.
Conv2dBackpropInput<T extends TNumber>	Computes the gradients of convolution with respect to the input.
Conv3d<T extends TNumber>	Computes a 3-D convolution given 5-D `input` and `filter` tensors.
Conv3dBackpropFilter<T extends TNumber>	Computes the gradients of 3-D convolution with respect to the filter.
Conv3dBackpropInput<U extends TNumber>	Computes the gradients of 3-D convolution with respect to the input.
Copy<T extends TType>	Copy a tensor from CPU-to-CPU or GPU-to-GPU.
CopyHost<T extends TType>	Copy a tensor to host.
Cos<T extends TType>	Computes cos of x element-wise.
Cosh<T extends TType>	Computes hyperbolic cosine of x element-wise.
CountUpTo<T extends TNumber>	Increments 'ref' until it reaches 'limit'.
CropAndResize	Extracts crops from the input image tensor and resizes them.
CropAndResizeGradBoxes	Computes the gradient of the crop_and_resize op wrt the input boxes tensor.
CropAndResizeGradImage<T extends TNumber>	Computes the gradient of the crop_and_resize op wrt the input image tensor.
Cross<T extends TNumber>	Compute the pairwise cross product.
CrossReplicaSum<T extends TNumber>	An Op to sum inputs across replicated TPU instances.
CudnnRNNCanonicalToParams<T extends TNumber>	Converts CudnnRNN params from canonical form to usable form.
CudnnRnnParamsSize<U extends TNumber>	Computes size of weights that can be used by a Cudnn RNN model.
Cumprod<T extends TType>	Compute the cumulative product of the tensor `x` along `axis`.
Cumsum<T extends TType>	Compute the cumulative sum of the tensor `x` along `axis`.
CumulativeLogsumexp<T extends TNumber>	Compute the cumulative product of the tensor `x` along `axis`.
DataFormatDimMap<T extends TNumber>	Returns the dimension index in the destination data format given the one in the source data format.
DataFormatVecPermute<T extends TNumber>	Permute input tensor from `src_format` to `dst_format`.
DataServiceDataset
DatasetCardinality	Returns the cardinality of `input_dataset`.
DatasetFromGraph	Creates a dataset from the given `graph_def`.
DatasetToGraph	Returns a serialized GraphDef representing `input_dataset`.
Dawsn<T extends TNumber>
DebugGradientIdentity<T extends TType>	Identity op for gradient debugging.
DebugGradientRefIdentity<T extends TType>	Identity op for gradient debugging.
DebugIdentity<T extends TType>	Debug Identity V2 Op.
DebugNanCount	Debug NaN Value Counter Op.
DebugNumericsSummary<U extends TNumber>	Debug Numeric Summary V2 Op.
DecodeAndCropJpeg	Decode and Crop a JPEG-encoded image to a uint8 tensor.
DecodeBase64	Decode web-safe base64-encoded strings.
DecodeBmp	Decode the first frame of a BMP-encoded image to a uint8 tensor.
DecodeCompressed	Decompress strings.
DecodeGif	Decode the frame(s) of a GIF-encoded image to a uint8 tensor.
DecodeImage<T extends TNumber>	Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
DecodeJpeg	Decode a JPEG-encoded image to a uint8 tensor.
DecodeJsonExample	Convert JSON-encoded Example records to binary protocol buffer strings.
DecodePaddedRaw<T extends TNumber>	Reinterpret the bytes of a string as a vector of numbers.
DecodePng<T extends TNumber>	Decode a PNG-encoded image to a uint8 or uint16 tensor.
DecodeRaw<T extends TType>	Reinterpret the bytes of a string as a vector of numbers.
DeepCopy<T extends TType>	Makes a copy of `x`.
DenseBincount<U extends TNumber>	Counts the number of occurrences of each value in an integer array.
DenseToCSRSparseMatrix	Converts a dense tensor to a (possibly batched) CSRSparseMatrix.
DenseToSparseBatchDataset	Creates a dataset that batches input elements into a SparseTensor.
DepthToSpace<T extends TType>	DepthToSpace for tensors of type T.
DepthwiseConv2dNative<T extends TNumber>	Computes a 2-D depthwise convolution given 4-D `input` and `filter` tensors.
DepthwiseConv2dNativeBackpropFilter<T extends TNumber>	Computes the gradients of depthwise convolution with respect to the filter.
DepthwiseConv2dNativeBackpropInput<T extends TNumber>	Computes the gradients of depthwise convolution with respect to the input.
Dequantize	Takes the packed uint32 input and unpacks the input to uint8 to do Dequantization on device.
DestroyTemporaryVariable<T extends TType>	Destroys the temporary variable and returns its final value.
Det<T extends TType>	Computes the determinant of one or more square matrices.
DeviceIndex	Return the index of device the op runs.
Digamma<T extends TNumber>	Computes Psi, the derivative of Lgamma (the log of the absolute value of `Gamma(x)`), element-wise.
Dilation2d<T extends TNumber>	Computes the grayscale dilation of 4-D `input` and 3-D `filter` tensors.
Dilation2dBackpropFilter<T extends TNumber>	Computes the gradient of morphological 2-D dilation with respect to the filter.
Dilation2dBackpropInput<T extends TNumber>	Computes the gradient of morphological 2-D dilation with respect to the input.
DirectedInterleaveDataset	A substitute for `InterleaveDataset` on a fixed list of `N` datasets.
Div<T extends TType>	Returns x / y element-wise.
DivNoNan<T extends TType>	Returns 0 if the denominator is zero.
Dot<T extends TType>	Wraps the XLA DotGeneral operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#dotgeneral .
DrawBoundingBoxes<T extends TNumber>	Draw bounding boxes on a batch of images.
DummyIterationCounter
DummyMemoryCache
DummySeedGenerator
DynamicSlice<T extends TType>	Wraps the XLA DynamicSlice operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice .
DynamicStitch<T extends TType>	Interleave the values from the `data` tensors into a single tensor.
DynamicUpdateSlice<T extends TType>	Wraps the XLA DynamicUpdateSlice operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#dynamicupdateslice .
EditDistance	Computes the (possibly normalized) Levenshtein Edit Distance.
Einsum<T extends TType>	An op which supports basic einsum op with 2 inputs and 1 output.
Elu<T extends TNumber>	Computes exponential linear: `exp(features) - 1` if < 0, `features` otherwise.
EluGrad<T extends TNumber>	Computes gradients for the exponential linear (Elu) operation.
EmbeddingActivations	An op enabling differentiation of TPU Embeddings.
Empty<T extends TType>	Creates a tensor with the given shape.
EmptyTensorList	Creates and returns an empty tensor list.
EmptyTensorMap	Creates and returns an empty tensor map.
EncodeBase64	Encode strings into web-safe base64 format.
EncodeJpeg	JPEG-encode an image.
EncodeJpegVariableQuality	JPEG encode input image with provided compression quality.
EncodePng	PNG-encode an image.
EncodeProto	The op serializes protobuf messages provided in the input tensors.
EncodeWav	Encode audio data using the WAV file format.
EnsureShape<T extends TType>	Ensures that the tensor's shape matches the expected shape.
Enter<T extends TType>	Creates or finds a child frame, and makes `data` available to the child frame.
Equal	Returns the truth value of (x == y) element-wise.
Erf<T extends TNumber>	Computes the Gauss error function of `x` element-wise.
Erfc<T extends TNumber>	Computes the complementary error function of `x` element-wise.
EuclideanNorm<T extends TType>	Computes the euclidean norm of elements across dimensions of a tensor.
Exit<T extends TType>	Exits the current frame to its parent frame.
Exp<T extends TType>	Computes exponential of x element-wise.
ExpandDims<T extends TType>	Inserts a dimension of 1 into a tensor's shape.
Expint<T extends TNumber>
Expm1<T extends TType>	Computes `exp(x) - 1` element-wise.
ExtractGlimpse	Extracts a glimpse from the input tensor.
ExtractImagePatches<T extends TType>	Extract `patches` from `images` and put them in the "depth" output dimension.
ExtractJpegShape<T extends TNumber>	Extract the shape information of a JPEG-encoded image.
ExtractVolumePatches<T extends TNumber>	Extract `patches` from `input` and put them in the `"depth"` output dimension.
Fact	Output a fact about factorials.
FakeQuantWithMinMaxArgs	Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type.
FakeQuantWithMinMaxArgsGradient	Compute gradients for a FakeQuantWithMinMaxArgs operation.
FakeQuantWithMinMaxVars	Fake-quantize the 'inputs' tensor of type float via global float scalars Fake-quantize the `inputs` tensor of type float via global float scalars `min` and `max` to `outputs` tensor of same shape as `inputs`.
FakeQuantWithMinMaxVarsPerChannel	Fake-quantize the 'inputs' tensor of type float via per-channel floats Fake-quantize the `inputs` tensor of type float per-channel and one of the shapes: `[d]`, `[b, d]` `[b, h, w, d]` via per-channel floats `min` and `max` of shape `[d]` to `outputs` tensor of same shape as `inputs`.
Fft<T extends TType>	Fast Fourier transform.
Fft2d<T extends TType>	2D fast Fourier transform.
Fft3d<T extends TType>	3D fast Fourier transform.
FifoQueue	A queue that produces elements in first-in first-out order.
Fill<U extends TType>	Creates a tensor filled with a scalar value.
FilterByLastComponentDataset	Creates a dataset containing elements of first component of `input_dataset` having true in the last component.
Fingerprint	Generates fingerprint values.
FixedLengthRecordDataset
FixedLengthRecordReader	A Reader that outputs fixed-length records from a file.
Floor<T extends TNumber>	Returns element-wise largest integer not greater than x.
FloorDiv<T extends TType>	Returns x // y element-wise.
FloorMod<T extends TNumber>	Returns element-wise remainder of division.
FractionalAvgPoolGrad<T extends TNumber>	Computes gradient of the FractionalAvgPool function.
FractionalMaxPoolGrad<T extends TNumber>	Computes gradient of the FractionalMaxPool function.
FresnelCos<T extends TNumber>
FresnelSin<T extends TNumber>
FusedPadConv2d<T extends TNumber>	Performs a padding as a preprocess during a convolution.
FusedResizeAndPadConv2d<T extends TNumber>	Performs a resize and padding as a preprocess during a convolution.
Gather<T extends TType>	Wraps the XLA Gather operator documented at https://www.tensorflow.org/xla/operation_semantics#gather
GatherNd<T extends TType>	Gather slices from `params` into a Tensor with shape specified by `indices`.
GatherV2<T extends TNumber>	Mutually accumulates multiple tensors of identical type and shape.
GetSessionHandle	Store the input tensor in the state of the current session.
GetSessionTensor<T extends TType>	Get the value of the tensor specified by its handle.
Greater	Returns the truth value of (x > y) element-wise.
GreaterEqual	Returns the truth value of (x >= y) element-wise.
GuaranteeConst<T extends TType>	Gives a guarantee to the TF runtime that the input tensor is a constant.
HashTable	Creates a non-initialized hash table.
HistogramFixedWidth<U extends TNumber>	Return histogram of values.
HistogramSummary	Outputs a `Summary` protocol buffer with a histogram.
HsvToRgb<T extends TNumber>	Convert one or more images from HSV to RGB.
Identity<T extends TType>	Return a tensor with the same shape and contents as the input tensor or value.
IdentityReader	A Reader that outputs the queued work as both the key and value.
Ifft<T extends TType>	Inverse fast Fourier transform.
Ifft2d<T extends TType>	Inverse 2D fast Fourier transform.
Ifft3d<T extends TType>	Inverse 3D fast Fourier transform.
Igamma<T extends TNumber>	Compute the lower regularized incomplete Gamma function `P(a, x)`.
IgammaGradA<T extends TNumber>	Computes the gradient of `igamma(a, x)` wrt `a`.
Igammac<T extends TNumber>	Compute the upper regularized incomplete Gamma function `Q(a, x)`.
IgnoreErrorsDataset	Creates a dataset that contains the elements of `input_dataset` ignoring errors.
Imag<U extends TNumber>	Returns the imaginary part of a complex number.
ImageProjectiveTransformV2<T extends TNumber>	Applies the given transform to each of the images.
ImageProjectiveTransformV3<T extends TNumber>	Applies the given transform to each of the images.
ImageSummary	Outputs a `Summary` protocol buffer with images.
ImmutableConst<T extends TType>	Returns immutable tensor from memory region.
InTopK	Says whether the targets are in the top `K` predictions.
InfeedDequeue<T extends TType>	A placeholder op for a value that will be fed into the computation.
InplaceAdd<T extends TType>	Adds v into specified rows of x.
InplaceSub<T extends TType>	Subtracts `v` into specified rows of `x`.
InplaceUpdate<T extends TType>	Updates specified rows 'i' with values 'v'.
Inv<T extends TType>	Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes).
InvGrad<T extends TType>	Computes the gradient for the inverse of `x` wrt its input.
Invert<T extends TNumber>	Invert (flip) each bit of supported types; for example, type `uint8` value 01010101 becomes 10101010.
InvertPermutation<T extends TNumber>	Computes the inverse permutation of a tensor.
Irfft<U extends TNumber>	Inverse real-valued fast Fourier transform.
Irfft2d<U extends TNumber>	Inverse 2D real-valued fast Fourier transform.
Irfft3d<U extends TNumber>	Inverse 3D real-valued fast Fourier transform.
IsBoostedTreesEnsembleInitialized	Checks whether a tree ensemble has been initialized.
IsBoostedTreesQuantileStreamResourceInitialized	Checks whether a quantile stream has been initialized.
IsFinite	Returns which elements of x are finite.
IsInf	Returns which elements of x are Inf.
IsNan	Returns which elements of x are NaN.
IsVariableInitialized	Checks whether a tensor has been initialized.
Iterator
IteratorFromStringHandle
IteratorGetDevice	Returns the name of the device on which `resource` has been placed.
IteratorGetNextAsOptional	Gets the next output from the given iterator as an Optional variant.
IteratorToStringHandle	Converts the given `resource_handle` representing an iterator to a string.
Join	Joins the strings in the given list of string tensors into one tensor; with the given separator (default is an empty separator).
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.
L2Loss<T extends TNumber>	L2 Loss.
LMDBDataset	Creates a dataset that emits the key-value pairs in one or more LMDB files.
LatencyStatsDataset	Records the latency of producing `input_dataset` elements in a StatsAggregator.
LeakyRelu<T extends TNumber>	Computes rectified linear: `max(features, features * alpha)`.
LeakyReluGrad<T extends TNumber>	Computes rectified linear gradients for a LeakyRelu operation.
LeftShift<T extends TNumber>	Elementwise computes the bitwise left-shift of `x` and `y`.
Less	Returns the truth value of (x < y) element-wise.
LessEqual	Returns the truth value of (x <= y) element-wise.
Lgamma<T extends TNumber>	Computes the log of the absolute value of `Gamma(x)` element-wise.
LinSpace<T extends TNumber>	Generates values in an interval.
LmdbDataset
LmdbReader	A Reader that outputs the records from a LMDB file.
LoadAndRemapMatrix	Loads a 2-D (matrix) `Tensor` with name `old_tensor_name` from the checkpoint at `ckpt_path` and potentially reorders its rows and columns using the specified remappings.
LocalResponseNormalization<T extends TNumber>	Local Response Normalization.
LocalResponseNormalizationGrad<T extends TNumber>	Gradients for Local Response Normalization.
Log<T extends TType>	Computes natural logarithm of x element-wise.
Log1p<T extends TType>	Computes natural logarithm of (1 + x) element-wise.
LogSoftmax<T extends TNumber>	Computes log softmax activations.
LogicalAnd	Returns the truth value of x AND y element-wise.
LogicalNot	Returns the truth value of `NOT x` element-wise.
LogicalOr	Returns the truth value of x OR y element-wise.
LookupTableFind<U extends TType>	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.
Lower	Converts all uppercase characters into their respective lowercase replacements.
LowerBound<U extends TNumber>	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.
MatMul<T extends TType>	Multiply the matrix "a" by the matrix "b".
MatchingFiles	Returns the set of files matching one or more glob patterns.
MatchingFilesDataset
MatrixDiag<T extends TType>	Returns a batched diagonal tensor with given batched diagonal values.
MatrixDiagPart<T extends TType>	Returns the batched diagonal part of a batched tensor.
MatrixDiagPartV3<T extends TType>	Returns the batched diagonal part of a batched tensor.
MatrixDiagV3<T extends TType>	Returns a batched diagonal tensor with given batched diagonal values.
MatrixLogarithm<T extends TType>	Computes the matrix logarithm of one or more square matrices: \\(log(exp(A)) = A\\) This op is only defined for complex matrices.
MatrixSetDiag<T extends TType>	Returns a batched matrix tensor with new batched diagonal values.
MatrixSolveLs<T extends TType>	Solves one or more linear least-squares problems.
Max<T extends TType>	Computes the maximum of elements across dimensions of a tensor.
MaxIntraOpParallelismDataset	Creates a dataset that overrides the maximum intra-op parallelism.
MaxPool<T extends TType>	Performs max pooling on the input.
MaxPool3d<T extends TNumber>	Performs 3D max pooling on the input.
MaxPool3dGrad<U extends TNumber>	Computes gradients of 3D max pooling function.
MaxPool3dGradGrad<T extends TNumber>	Computes second-order gradients of the maxpooling function.
MaxPoolGrad<T extends TNumber>	Computes gradients of the maxpooling function.
MaxPoolGradGrad<T extends TNumber>	Computes second-order gradients of the maxpooling function.
MaxPoolGradGradWithArgmax<T extends TNumber>	Computes second-order gradients of the maxpooling function.
MaxPoolGradWithArgmax<T extends TNumber>	Computes gradients of the maxpooling function.
Maximum<T extends TNumber>	Returns the max of x and y (i.e.
Mean<T extends TType>	Computes the mean of elements across dimensions of a tensor.
MergeSummary	Merges summaries.
Mfcc	Transforms a spectrogram into a form that's useful for speech recognition.
Min<T extends TType>	Computes the minimum of elements across dimensions of a tensor.
Minimum<T extends TNumber>	Returns the min of x and y (i.e.
MirrorPad<T extends TType>	Pads a tensor with mirrored values.
MirrorPadGrad<T extends TType>	Gradient op for `MirrorPad` op.
Mod<T extends TNumber>	Returns element-wise remainder of division.
ModelDataset	Identity transformation that models performance.
Mul<T extends TType>	Returns x * y element-wise.
MulNoNan<T extends TType>	Returns x * y element-wise.
MultiDeviceIterator	Creates a MultiDeviceIterator resource.
MultiDeviceIteratorFromStringHandle	Generates a MultiDeviceIterator resource from its provided string handle.
MultiDeviceIteratorInit	Initializes the multi device iterator with the given dataset.
MultiDeviceIteratorToStringHandle	Produces a string handle for the given MultiDeviceIterator.
Multinomial<U extends TNumber>	Draws samples from a multinomial distribution.
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 TNumber>	Outputs a tensor containing the reduction across all input tensors.
NcclBroadcast<T extends TNumber>	Sends `input` to all devices that are connected to the output.
NcclReduce<T extends TNumber>	Reduces `input` from `num_devices` using `reduction` to a single device.
Ndtri<T extends TNumber>
Neg<T extends TType>	Computes numerical negative value element-wise.
NextAfter<T extends TNumber>	Returns the next representable value of `x1` in the direction of `x2`, element-wise.
NextIteration<T extends TType>	Makes its input available to the next iteration.
NonDeterministicInts<U extends TType>	Non-deterministically generates some integers.
NonMaxSuppressionWithOverlaps	Greedily selects a subset of bounding boxes in descending order of score, pruning away boxes that have high overlaps with previously selected boxes.
NonSerializableDataset
NotEqual	Returns the truth value of (x != y) element-wise.
NthElement<T extends TNumber>	Finds values of the `n`-th order statistic for the last dimension.
OneHot<U extends TType>	Returns a one-hot tensor.
Ones<T extends TType>	An operator creating a constant initialized with ones of the shape given by `dims`.
OnesLike<T extends TType>	Returns a tensor of ones with the same shape and type as x.
OptimizeDataset	Creates a dataset by applying optimizations to `input_dataset`.
OptimizeDatasetV2	Creates a dataset by applying related optimizations to `input_dataset`.
OptionalFromValue	Constructs an Optional variant from a tuple of tensors.
OptionalHasValue	Returns true if and only if the given Optional variant has a value.
OptionalNone	Creates an Optional variant with no value.
OrderedMapIncompleteSize	Op returns the number of incomplete elements in the underlying container.
OrderedMapSize	Op returns the number of elements in the underlying container.
OrdinalSelector	A TPU core selector Op.
OutfeedDequeue<T extends TType>	Retrieves a single tensor from the computation outfeed.
OutfeedDequeueV2<T extends TType>	Retrieves a single tensor from the computation outfeed.
Output<T extends TType>	A symbolic handle to a tensor produced by an `Operation`.
Pad<T extends TType>	Wraps the XLA Pad operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#pad .
PaddedBatchDataset	Creates a dataset that batches and pads `batch_size` elements from the input.
PaddingFifoQueue	A queue that produces elements in first-in first-out order.
ParallelConcat<T extends TType>	Concatenates a list of `N` tensors along the first dimension.
ParallelDynamicStitch<T extends TType>	Interleave the values from the `data` tensors into a single tensor.
ParameterizedTruncatedNormal<U extends TNumber>	Outputs random values from a normal distribution.
ParseExampleDataset	Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.
ParseTensor<T extends TType>	Transforms a serialized tensorflow.TensorProto proto into a Tensor.
PartitionedInput<T extends TType>	An op that groups a list of partitioned inputs together.
Placeholder<T extends TType>	A placeholder op for a value that will be fed into the computation.
PlaceholderWithDefault<T extends TType>	A placeholder op that passes through `input` when its output is not fed.
Polygamma<T extends TNumber>	Compute the polygamma function \\(\psi^{(n)}(x)\\).
PopulationCount	Computes element-wise population count (a.k.a.
Pow<T extends TType>	Computes the power of one value to another.
PrefetchDataset	Creates a dataset that asynchronously prefetches elements from `input_dataset`.
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.
PreventGradient<T extends TType>	An identity op that triggers an error if a gradient is requested.
PriorityQueue	A queue that produces elements sorted by the first component value.
PrivateThreadPoolDataset	Creates a dataset that uses a custom thread pool to compute `input_dataset`.
Prod<T extends TType>	Computes the product of elements across dimensions of a tensor.
QuantizeAndDequantize<T extends TNumber>	Quantizes then dequantizes a tensor.
QuantizeAndDequantizeV3<T extends TNumber>	Quantizes then dequantizes a tensor.
QuantizeAndDequantizeV4<T extends TNumber>	Returns the gradient of `quantization.QuantizeAndDequantizeV4`.
QuantizedMatMulWithBiasAndDequantize<W extends TNumber>
QueueIsClosed	Returns true if queue is closed.
QueueSize	Computes the number of elements in the given queue.
RaggedBincount<U extends TNumber>	Counts the number of occurrences of each value in an integer array.
RaggedTensorToTensor<U extends TType>	Create a dense tensor from a ragged tensor, possibly altering its shape.
RaggedTensorToVariant	Encodes a `RaggedTensor` into a `variant` Tensor.
RaggedTensorToVariantGradient<U extends TType>	Helper used to compute the gradient for `RaggedTensorToVariant`.
RandomCrop<T extends TNumber>	Randomly crop `image`.
RandomDataset	Creates a Dataset that returns pseudorandom numbers.
RandomGamma<U extends TNumber>	Outputs random values from the Gamma distribution(s) described by alpha.
RandomGammaGrad<T extends TNumber>	Computes the derivative of a Gamma random sample w.r.t.
RandomPoisson<V extends TNumber>	Outputs random values from the Poisson distribution(s) described by rate.
RandomShuffle<T extends TType>	Randomly shuffles a tensor along its first dimension.
RandomShuffleQueue	A queue that randomizes the order of elements.
RandomStandardNormal<U extends TNumber>	Outputs random values from a normal distribution.
RandomUniform<U extends TNumber>	Outputs random values from a uniform distribution.
RandomUniformInt<U extends TNumber>	Outputs random integers from a uniform distribution.
Range<T extends TNumber>	Creates a sequence of numbers.
RangeDataset	Creates a dataset with a range of values.
Rank	Returns the rank of a tensor.
ReadFile	Reads and outputs the entire contents of the input filename.
ReadVariableOp<T extends TType>	Reads the value of a variable.
ReaderNumRecordsProduced	Returns the number of records this Reader has produced.
ReaderNumWorkUnitsCompleted	Returns the number of work units this Reader has finished processing.
ReaderSerializeState	Produce a string tensor that encodes the state of a Reader.
Real<U extends TNumber>	Returns the real part of a complex number.
RealDiv<T extends TType>	Returns x / y element-wise for real types.
RebatchDataset	Creates a dataset that changes the batch size.
RebatchDatasetV2	Creates a dataset that changes the batch size.
Reciprocal<T extends TType>	Computes the reciprocal of x element-wise.
ReciprocalGrad<T extends TType>	Computes the gradient for the inverse of `x` wrt its input.
RecordInput	Emits randomized records.
Recv<T extends TType>	Receives the named tensor from another XLA computation.
Reduce<T extends TNumber>	Mutually reduces multiple tensors of identical type and shape.
ReduceAll	Computes the "logical and" of elements across dimensions of a tensor.
ReduceAny	Computes the "logical or" of elements across dimensions of a tensor.
ReduceJoin	Joins a string Tensor across the given dimensions.
ReduceMax<T extends TType>	Computes the maximum of elements across dimensions of a tensor.
ReduceMin<T extends TType>	Computes the minimum of elements across dimensions of a tensor.
ReduceProd<T extends TType>	Computes the product of elements across dimensions of a tensor.
ReduceSum<T extends TType>	Computes the sum of elements across dimensions of a tensor.
ReduceV2<T extends TNumber>	Mutually reduces multiple tensors of identical type and shape.
RefEnter<T extends TType>	Creates or finds a child frame, and makes `data` available to the child frame.
RefExit<T extends TType>	Exits the current frame to its parent frame.
RefIdentity<T extends TType>	Return the same ref tensor as the input ref tensor.
RefNextIteration<T extends TType>	Makes its input available to the next iteration.
RefSelect<T extends TType>	Forwards the `index`th element of `inputs` to `output`.
RegexFullMatch	Check if the input matches the regex pattern.
RegexReplace	Replaces matches of the `pattern` regular expression in `input` with the replacement string provided in `rewrite`.
RegisterDataset	Registers a dataset with the tf.data service.
Relu<T extends TType>	Computes rectified linear: `max(features, 0)`.
Relu6<T extends TNumber>	Computes rectified linear 6: `min(max(features, 0), 6)`.
Relu6Grad<T extends TNumber>	Computes rectified linear 6 gradients for a Relu6 operation.
ReluGrad<T extends TNumber>	Computes rectified linear gradients for a Relu operation.
RepeatDataset	Creates a dataset that emits the outputs of `input_dataset` `count` times.
ReplicaId	Replica ID.
ReplicatedInput<T extends TType>	Connects N inputs to an N-way replicated TPU computation.
Reshape<T extends TType>	Reshapes a tensor.
ResizeArea	Resize `images` to `size` using area interpolation.
ResizeBicubic	Resize `images` to `size` using bicubic interpolation.
ResizeBicubicGrad<T extends TNumber>	Computes the gradient of bicubic interpolation.
ResizeBilinear	Resize `images` to `size` using bilinear interpolation.
ResizeBilinearGrad<T extends TNumber>	Computes the gradient of bilinear interpolation.
ResizeNearestNeighbor<T extends TNumber>	Resize `images` to `size` using nearest neighbor interpolation.
ResizeNearestNeighborGrad<T extends TNumber>	Computes the gradient of nearest neighbor interpolation.
ResourceAccumulatorNumAccumulated	Returns the number of gradients aggregated in the given accumulators.
ResourceAccumulatorTakeGradient<T extends TType>	Extracts the average gradient in the given ConditionalAccumulator.
ResourceConditionalAccumulator	A conditional accumulator for aggregating gradients.
ResourceCountUpTo<T extends TNumber>	Increments variable pointed to by 'resource' until it reaches 'limit'.
ResourceGather<U extends TType>	Gather slices from the variable pointed to by `resource` according to `indices`.
ResourceGatherNd<U extends TType>
RestoreSlice<T extends TType>	Restores a tensor from checkpoint files.
RetrieveTPUEmbeddingStochasticGradientDescentParameters	Retrieve SGD embedding parameters.
Reverse<T extends TType>	Reverses specific dimensions of a tensor.
ReverseSequence<T extends TType>	Reverses variable length slices.
Rfft<U extends TType>	Real-valued fast Fourier transform.
Rfft2d<U extends TType>	2D real-valued fast Fourier transform.
Rfft3d<U extends TType>	3D real-valued fast Fourier transform.
RgbToHsv<T extends TNumber>	Converts one or more images from RGB to HSV.
RightShift<T extends TNumber>	Elementwise computes the bitwise right-shift of `x` and `y`.
Rint<T extends TNumber>	Returns element-wise integer closest to x.
RngReadAndSkip	Advance the counter of a counter-based RNG.
Roll<T extends TType>	Rolls the elements of a tensor along an axis.
Round<T extends TType>	Rounds the values of a tensor to the nearest integer, element-wise.
Rpc	Perform batches of RPC requests.
Rsqrt<T extends TType>	Computes reciprocal of square root of x element-wise.
RsqrtGrad<T extends TType>	Computes the gradient for the rsqrt of `x` wrt its input.
SamplingDataset	Creates a dataset that takes a Bernoulli sample of the contents of another dataset.
ScalarSummary	Outputs a `Summary` protocol buffer with scalar values.
ScaleAndTranslate
ScaleAndTranslateGrad<T extends TNumber>
ScatterAdd<T extends TType>	Adds sparse updates to a variable reference.
ScatterDiv<T extends TType>	Divides a variable reference by sparse updates.
ScatterMax<T extends TNumber>	Reduces sparse updates into a variable reference using the `max` operation.
ScatterMin<T extends TNumber>	Reduces sparse updates into a variable reference using the `min` operation.
ScatterMul<T extends TType>	Multiplies sparse updates into a variable reference.
ScatterNd<U extends TType>	Scatter `updates` into a new tensor according to `indices`.
ScatterNdAdd<T extends TType>	Applies sparse addition to individual values or slices in a Variable.
ScatterNdMax<T extends TType>	Computes element-wise maximum.
ScatterNdMin<T extends TType>	Computes element-wise minimum.
ScatterNdNonAliasingAdd<T extends TType>	Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`.
ScatterNdSub<T extends TType>	Applies sparse subtraction to individual values or slices in a Variable.
ScatterNdUpdate<T extends TType>	Applies sparse `updates` to individual values or slices within a given variable according to `indices`.
ScatterSub<T extends TType>	Subtracts sparse updates to a variable reference.
ScatterUpdate<T extends TType>	Applies sparse updates to a variable reference.
SdcaFprint	Computes fingerprints of the input strings.
SegmentMax<T extends TNumber>	Computes the maximum along segments of a tensor.
SegmentMean<T extends TType>	Computes the mean along segments of a tensor.
SegmentMin<T extends TNumber>	Computes the minimum along segments of a tensor.
SegmentProd<T extends TType>	Computes the product along segments of a tensor.
SegmentSum<T extends TType>	Computes the sum along segments of a tensor.
Select<T extends TType>
Selu<T extends TNumber>	Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)` if < 0, `scale * features` otherwise.
SeluGrad<T extends TNumber>	Computes gradients for the scaled exponential linear (Selu) operation.
SerializeIterator	Converts the given `resource_handle` representing an iterator to a variant tensor.
SerializeManySparse<U extends TType>	Serialize an `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor` object.
SerializeSparse<U extends TType>	Serialize a `SparseTensor` into a `[3]` `Tensor` object.
SerializeTensor	Transforms a Tensor into a serialized TensorProto proto.
SetSize	Number of unique elements along last dimension of input `set`.
SetStatsAggregatorDataset
Shape<U extends TNumber>	Returns the shape of a tensor.
ShardDataset	Creates a `Dataset` that includes only 1/`num_shards` of this dataset.
ShardedFilename	Generate a sharded filename.
ShardedFilespec	Generate a glob pattern matching all sharded file names.
Sharding<T extends TType>	An op which shards the input based on the given sharding attribute.
ShuffleAndRepeatDataset
ShuffleDataset
Sigmoid<T extends TType>	Computes sigmoid of `x` element-wise.
SigmoidGrad<T extends TType>	Computes the gradient of the sigmoid of `x` wrt its input.
Sign<T extends TType>	Returns an element-wise indication of the sign of a number.
Sin<T extends TType>	Computes sine of x element-wise.
Sinh<T extends TType>	Computes hyperbolic sine of x element-wise.
Size<U extends TNumber>	Returns the size of a tensor.
SkipDataset	Creates a dataset that skips `count` elements from the `input_dataset`.
SleepDataset
Slice<T extends TType>	Return a slice from 'input'.
SlidingWindowDataset	Creates a dataset that passes a sliding window over `input_dataset`.
Snapshot<T extends TType>	Returns a copy of the input tensor.
SobolSample<T extends TNumber>	Generates points from the Sobol sequence.
Softmax<T extends TNumber>	Computes softmax activations.
Softplus<T extends TNumber>	Computes softplus: `log(exp(features) + 1)`.
SoftplusGrad<T extends TNumber>	Computes softplus gradients for a softplus operation.
Softsign<T extends TNumber>	Computes softsign: `features / (abs(features) + 1)`.
SoftsignGrad<T extends TNumber>	Computes softsign gradients for a softsign operation.
Solve<T extends TType>	Solves systems of linear equations.
Sort<T extends TType>	Wraps the XLA Sort operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#sort .
SpaceToBatch<T extends TType>	SpaceToBatch for 4-D tensors of type T.
SpaceToBatchNd<T extends TType>	SpaceToBatch for N-D tensors of type T.
SpaceToDepth<T extends TType>	SpaceToDepth for tensors of type T.
SparseApplyAdadelta<T extends TType>	var: Should be from a Variable().
SparseApplyAdagrad<T extends TType>	Update relevant entries in 'var' and 'accum' according to the adagrad scheme.
SparseApplyAdagradDa<T extends TType>	Update entries in 'var' and 'accum' according to the proximal adagrad scheme.
SparseApplyCenteredRmsProp<T extends TType>	Update '*var' according to the centered RMSProp algorithm.
SparseApplyFtrl<T extends TType>	Update relevant entries in '*var' according to the Ftrl-proximal scheme.
SparseApplyMomentum<T extends TType>	Update relevant entries in 'var' and 'accum' according to the momentum scheme.
SparseApplyProximalAdagrad<T extends TType>	Sparse update entries in 'var' and 'accum' according to FOBOS algorithm.
SparseApplyProximalGradientDescent<T extends TType>	Sparse update '*var' as FOBOS algorithm with fixed learning rate.
SparseApplyRmsProp<T extends TType>	Update '*var' according to the RMSProp algorithm.
SparseBincount<U extends TNumber>	Counts the number of occurrences of each value in an integer array.
SparseConditionalAccumulator	A conditional accumulator for aggregating sparse gradients.
SparseDenseCwiseAdd<T extends TType>	Adds up a SparseTensor and a dense Tensor, using these special rules: (1) Broadcasts the dense side to have the same shape as the sparse side, if eligible; (2) Then, only the dense values pointed to by the indices of the SparseTensor participate in the cwise addition.
SparseDenseCwiseDiv<T extends TType>	Component-wise divides a SparseTensor by a dense Tensor.
SparseDenseCwiseMul<T extends TType>	Component-wise multiplies a SparseTensor by a dense Tensor.
SparseMatMul	Multiply matrix "a" by matrix "b".
SparseMatrixAdd	Sparse addition of two CSR matrices, C = alpha * A + beta * B.
SparseMatrixMatMul<T extends TType>	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`.
SparseReduceMax<T extends TNumber>	Computes the max of elements across dimensions of a SparseTensor.
SparseReduceSum<T extends TType>	Computes the sum of elements across dimensions of a SparseTensor.
SparseSegmentMean<T extends TNumber>	Computes the mean along sparse segments of a tensor.
SparseSegmentMeanGrad<T extends TNumber>	Computes gradients for SparseSegmentMean.
SparseSegmentMeanWithNumSegments<T extends TNumber>	Computes the mean along sparse segments of a tensor.
SparseSegmentSqrtN<T extends TNumber>	Computes the sum along sparse segments of a tensor divided by the sqrt of N.
SparseSegmentSqrtNGrad<T extends TNumber>	Computes gradients for SparseSegmentSqrtN.
SparseSegmentSqrtNWithNumSegments<T extends TNumber>	Computes the sum along sparse segments of a tensor divided by the sqrt of N.
SparseSegmentSum<T extends TNumber>	Computes the sum along sparse segments of a tensor.
SparseSegmentSumWithNumSegments<T extends TNumber>	Computes the sum along sparse segments of a tensor.
SparseSliceGrad<T extends TType>	The gradient operator for the SparseSlice op.
SparseSoftmax<T extends TNumber>	Applies softmax to a batched N-D `SparseTensor`.
SparseTensorDenseAdd<U extends TType>	Adds up a `SparseTensor` and a dense `Tensor`, producing a dense `Tensor`.
SparseTensorDenseMatMul<U extends TType>	Multiply SparseTensor (of rank 2) "A" by dense matrix "B".
SparseTensorSliceDataset	Creates a dataset that splits a SparseTensor into elements row-wise.
SparseTensorToCSRSparseMatrix	Converts a SparseTensor to a (possibly batched) CSRSparseMatrix.
SparseToDense<U extends TType>	Converts a sparse representation into a dense tensor.
Spence<T extends TNumber>
SqlDataset	Creates a dataset that executes a SQL query and emits rows of the result set.
Sqrt<T extends TType>	Computes square root of x element-wise.
SqrtGrad<T extends TType>	Computes the gradient for the sqrt of `x` wrt its input.
Sqrtm<T extends TType>	Computes the matrix square root of one or more square matrices: matmul(sqrtm(A), sqrtm(A)) = A The input matrix should be invertible.
Square<T extends TType>	Computes square of x element-wise.
SquaredDifference<T extends TType>	Returns conj(x - y)(x - y) element-wise.
Squeeze<T extends TType>	Removes dimensions of size 1 from the shape of a tensor.
Stack<T extends TType>	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 TNumber>
StatefulStandardNormal<U extends TType>	Outputs random values from a normal distribution.
StatefulTruncatedNormal<U extends TType>	Outputs random values from a truncated normal distribution.
StatefulUniform<U extends TType>	Outputs random values from a uniform distribution.
StatefulUniformFullInt<U extends TType>	Outputs random integers from a uniform distribution.
StatefulUniformInt<U extends TType>	Outputs random integers from a uniform distribution.
StatelessMultinomial<V extends TNumber>	Draws samples from a multinomial distribution.
StatelessParameterizedTruncatedNormal<V extends TNumber>
StatelessRandomBinomial<W extends TNumber>	Outputs deterministic pseudorandom random numbers from a binomial distribution.
StatelessRandomGamma<V extends TNumber>	Outputs deterministic pseudorandom random numbers from a gamma distribution.
StatelessRandomNormal<V extends TNumber>	Outputs deterministic pseudorandom values from a normal distribution.
StatelessRandomNormalV2<U extends TNumber>	Outputs deterministic pseudorandom values from a normal distribution.
StatelessRandomPoisson<W extends TNumber>	Outputs deterministic pseudorandom random numbers from a Poisson distribution.
StatelessRandomUniform<V extends TNumber>	Outputs deterministic pseudorandom random values from a uniform distribution.
StatelessRandomUniformFullInt<V extends TNumber>	Outputs deterministic pseudorandom random integers from a uniform distribution.
StatelessRandomUniformFullIntV2<U extends TNumber>	Outputs deterministic pseudorandom random integers from a uniform distribution.
StatelessRandomUniformInt<V extends TNumber>	Outputs deterministic pseudorandom random integers from a uniform distribution.
StatelessRandomUniformIntV2<U extends TNumber>	Outputs deterministic pseudorandom random integers from a uniform distribution.
StatelessRandomUniformV2<U extends TNumber>	Outputs deterministic pseudorandom random values from a uniform distribution.
StatelessTruncatedNormal<V extends TNumber>	Outputs deterministic pseudorandom values from a truncated normal distribution.
StatelessTruncatedNormalV2<U extends TNumber>	Outputs deterministic pseudorandom values from a truncated normal distribution.
StaticRegexFullMatch	Check if the input matches the regex pattern.
StaticRegexReplace	Replaces the match of pattern in input with rewrite.
StatsAggregatorHandle
StatsAggregatorSummary	Produces a summary of any statistics recorded by the given statistics manager.
StopGradient<T extends TType>	Stops gradient computation.
StridedSlice<T extends TType>	Return a strided slice from `input`.
StridedSliceAssign<T extends TType>	Assign `value` to the sliced l-value reference of `ref`.
StridedSliceGrad<U extends TType>	Returns the gradient of `StridedSlice`.
StringFormat	Formats a string template using a list of tensors.
StringLength	String lengths of `input`.
Strip	Strip leading and trailing whitespaces from the Tensor.
Sub<T extends TType>	Returns x - y element-wise.
Substr	Return substrings from `Tensor` of strings.
Sum<T extends TType>	Computes the sum of elements across dimensions of a tensor.
SummaryWriter
TPUCompilationResult	Returns the result of a TPU compilation.
TPUEmbeddingActivations	An op enabling differentiation of TPU Embeddings.
TPUReplicatedInput<T extends TType>	Connects N inputs to an N-way replicated TPU computation.
TakeDataset	Creates a dataset that contains `count` elements from the `input_dataset`.
Tan<T extends TType>	Computes tan of x element-wise.
Tanh<T extends TType>	Computes hyperbolic tangent of `x` element-wise.
TanhGrad<T extends TType>	Computes the gradient for the tanh of `x` wrt its input.
TemporaryVariable<T extends TType>	Returns a tensor that may be mutated, but only persists within a single step.
TensorArrayGather<T extends TType>	Gather specific elements from the TensorArray into output `value`.
TensorArrayPack<T extends TType>
TensorArrayRead<T extends TType>	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.
TensorDataset	Creates a dataset that emits `components` as a tuple of tensors once.
TensorDiag<T extends TType>	Returns a diagonal tensor with a given diagonal values.
TensorDiagPart<T extends TType>	Returns the diagonal part of the tensor.
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 TNumber>	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 extends TType>	Creates a Tensor by indexing into the TensorList.
TensorListGetItem<T extends TType>
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.
TensorListSetItem
TensorListSplit	Splits a tensor into a list.
TensorListStack<T extends TType>	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 extends TType>	Returns the value from a given key in a tensor map.
TensorMapSize	Returns the number of tensors in the input tensor map.
TensorMapStackKeys<T extends TType>	Returns a Tensor stack of all keys in a tensor map.
TensorScatterNdAdd<T extends TType>	Adds sparse `updates` to an existing tensor according to `indices`.
TensorScatterNdMax<T extends TType>
TensorScatterNdMin<T extends TType>
TensorScatterNdSub<T extends TType>	Subtracts sparse `updates` from an existing tensor according to `indices`.
TensorScatterNdUpdate<T extends TType>	Scatter `updates` into an existing tensor according to `indices`.
TensorSliceDataset	Creates a dataset that emits each dim-0 slice of `components` once.
TensorStridedSliceUpdate<T extends TType>	Assign `value` to the sliced l-value reference of `input`.
TensorSummary	Outputs a `Summary` protocol buffer with a tensor and per-plugin data.
TextLineDataset	Creates a dataset that emits the lines of one or more text files.
TextLineReader	A Reader that outputs the lines of a file delimited by '\n'.
TfRecordDataset	Creates a dataset that emits the records from one or more TFRecord files.
TfRecordReader	A Reader that outputs the records from a TensorFlow Records file.
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 extends TType>	Constructs a tensor by tiling a given tensor.
TileGrad<T extends TType>	Returns the gradient of `Tile`.
Timestamp	Provides the time since epoch in seconds.
ToBool	Converts a tensor to a scalar predicate.
ToHashBucket	Converts each string in the input Tensor to its hash mod by a number of buckets.
ToHashBucketFast	Converts each string in the input Tensor to its hash mod by a number of buckets.
ToHashBucketStrong	Converts each string in the input Tensor to its hash mod by a number of buckets.
ToNumber<T extends TNumber>	Converts each string in the input Tensor to the specified numeric type.
Transpose<T extends TType>	Shuffle dimensions of x according to a permutation.
TriangularSolve<T extends TType>	Solves systems of linear equations with upper or lower triangular matrices by backsubstitution.
TridiagonalMatMul<T extends TType>	Calculate product with tridiagonal matrix.
TridiagonalSolve<T extends TType>	Solves tridiagonal systems of equations.
TruncateDiv<T extends TType>	Returns x / y element-wise for integer types.
TruncateMod<T extends TNumber>	Returns element-wise remainder of division.
TruncatedNormal<U extends TNumber>	Outputs random values from a truncated normal distribution.
Unbatch<T extends TType>	Reverses the operation of Batch for a single output Tensor.
UnbatchDataset	A dataset that splits the elements of its input into multiple elements.
UnbatchGrad<T extends TType>	Gradient of Unbatch.
UnicodeEncode	Encode a tensor of ints into unicode strings.
UnicodeScript	Determine the script codes of a given tensor of Unicode integer code points.
UnicodeTranscode	Transcode the input text from a source encoding to a destination encoding.
UniqueDataset	Creates a dataset that contains the unique elements of `input_dataset`.
UnravelIndex<T extends TNumber>	Converts an array of flat indices into a tuple of coordinate arrays.
UnsortedSegmentJoin	Joins the elements of `inputs` based on `segment_ids`.
UnsortedSegmentMax<T extends TNumber>	Computes the maximum along segments of a tensor.
UnsortedSegmentMin<T extends TNumber>	Computes the minimum along segments of a tensor.
UnsortedSegmentProd<T extends TType>	Computes the product along segments of a tensor.
UnsortedSegmentSum<T extends TType>	Computes the sum along segments of a tensor.
UnwrapDatasetVariant
Upper	Converts all lowercase characters into their respective uppercase replacements.
UpperBound<U extends TNumber>	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 extends TType>	Holds state in the form of a tensor that persists across steps.
VariableShape<T extends TNumber>	Returns the shape of the variable pointed to by `resource`.
Where	Returns locations of nonzero / true values in a tensor.
WholeFileReader	A Reader that outputs the entire contents of a file as a value.
WindowDataset	Combines (nests of) input elements into a dataset of (nests of) windows.
WorkerHeartbeat	Worker heartbeat op.
WrapDatasetVariant
Xdivy<T extends TType>	Returns 0 if x == 0, and x / y otherwise, elementwise.
XlaRecvFromHost<T extends TType>	An op to receive a tensor from the host.
XlaSetBound	Set a bound for the given input value as a hint to Xla compiler, returns the same value.
XlaSpmdFullToShardShape<T extends TType>	An op used by XLA SPMD partitioner to switch from automatic partitioning to manual partitioning.
XlaSpmdShardToFullShape<T extends TType>	An op used by XLA SPMD partitioner to switch from manual partitioning to automatic partitioning.
Xlog1py<T extends TType>	Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise.
Xlogy<T extends TType>	Returns 0 if x == 0, and x * log(y) otherwise, elementwise.
Zeros<T extends TType>	An operator creating a constant initialized with zeros of the shape given by `dims`.
ZerosLike<T extends TType>	Returns a tensor of zeros with the same shape and type as x.
Zeta<T extends TNumber>	Compute the Hurwitz zeta function \\(\zeta(x, q)\\).
ZipDataset	Creates a dataset that zips together `input_datasets`.
erfinv<T extends TNumber>

Interface implemented by operands of a TensorFlow operation.

Example usage:

Ops tf = Ops.create();

 // The "decodeJpeg" operation can be used as an operand to the "cast" operation
 Operand<TUint8> decodeJpeg = tf.image.decodeJpeg(...);
 tf.dtypes.cast(decodeJpeg, TFloat32.class);

 // The output "y" of the "unique" operation can be used as an operand to the "cast" operation
 Output<TInt32> y = tf.unique(...).y();
 tf.dtypes.cast(y, TFloat32.class);

 // The "split" operation can be used as operand list to the "concat" operation
 Iterable<? extends Operand<TFloat32>> split = tf.split(...);
 tf.concat(split, tf.constant(0));

Public Methods

abstract Output<T>	asOutput() Returns the symbolic handle of the tensor.
abstract T	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the `Output` of this operand.
abstract Class<T>	type() Returns the tensor type of this operand

Inherited Methods

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Public Methods

public abstract Output<T> asOutput ()

Returns the symbolic handle of the 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.

public abstract T asTensor ()

Returns the tensor at this operand. Only works when running in an eager execution

Returns

the tensor

Throws

IllegalStateException	if this is an operand of a graph

public abstract Shape shape ()

Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.

public abstract Class<T> type ()

Returns the tensor type of this operand

Operand

Public Methods

Inherited Methods

Public Methods

public abstract Output<T> asOutput ()

See Also

public abstract T asTensor ()

Returns

Throws

public abstract Shape shape ()

public abstract Class<T> type ()