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TensorFlow C++ Reference

array_ops

Members
tensorflow::ops::BatchToSpace BatchToSpace for 4-D tensors of type T.
tensorflow::ops::BatchToSpaceND BatchToSpace for N-D tensors of type T.
tensorflow::ops::Bitcast Bitcasts a tensor from one type to another without copying data.
tensorflow::ops::BroadcastDynamicShape Return the shape of s0 op s1 with broadcast.
tensorflow::ops::CheckNumerics Checks a tensor for NaN and Inf values.
tensorflow::ops::Concat Concatenates tensors along one dimension.
tensorflow::ops::DepthToSpace DepthToSpace for tensors of type T.
tensorflow::ops::Dequantize Dequantize the 'input' tensor into a float Tensor.
tensorflow::ops::Diag Returns a diagonal tensor with a given diagonal values.
tensorflow::ops::DiagPart Returns the diagonal part of the tensor.
tensorflow::ops::EditDistance Computes the (possibly normalized) Levenshtein Edit Distance.
tensorflow::ops::ExpandDims Inserts a dimension of 1 into a tensor's shape.
tensorflow::ops::ExtractImagePatches Extract patches from images and put them in the "depth" output dimension.
tensorflow::ops::FakeQuantWithMinMaxArgs Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type.
tensorflow::ops::FakeQuantWithMinMaxArgsGradient Compute gradients for a FakeQuantWithMinMaxArgs operation.
tensorflow::ops::FakeQuantWithMinMaxVars Fake-quantize the 'inputs' tensor of type float via global float scalars min
tensorflow::ops::FakeQuantWithMinMaxVarsGradient Compute gradients for a FakeQuantWithMinMaxVars operation.
tensorflow::ops::FakeQuantWithMinMaxVarsPerChannel Fake-quantize the 'inputs' tensor of type float and one of the shapes: [d],.
tensorflow::ops::FakeQuantWithMinMaxVarsPerChannelGradient Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.
tensorflow::ops::Fill Creates a tensor filled with a scalar value.
tensorflow::ops::Gather Gather slices from params according to indices.
tensorflow::ops::GatherNd Gather values or slices from params according to indices.
tensorflow::ops::Identity Return a tensor with the same shape and contents as the input tensor or value.
tensorflow::ops::ImmutableConst Returns immutable tensor from memory region.
tensorflow::ops::InvertPermutation Computes the inverse permutation of a tensor.
tensorflow::ops::MatrixBandPart Copy a tensor setting everything outside a central band in each innermost matrix.
tensorflow::ops::MatrixDiag Returns a batched diagonal tensor with a given batched diagonal values.
tensorflow::ops::MatrixDiagPart Returns the batched diagonal part of a batched tensor.
tensorflow::ops::MatrixSetDiag Returns a batched matrix tensor with new batched diagonal values.
tensorflow::ops::MirrorPad Pads a tensor with mirrored values.
tensorflow::ops::OneHot Returns a one-hot tensor.
tensorflow::ops::OnesLike Returns a tensor of ones with the same shape and type as x.
tensorflow::ops::Pad Pads a tensor with zeros.
tensorflow::ops::ParallelConcat Concatenates a list of N tensors along the first dimension.
tensorflow::ops::Placeholder A placeholder op for a value that will be fed into the computation.
tensorflow::ops::PlaceholderV2 A placeholder op for a value that will be fed into the computation.
tensorflow::ops::PlaceholderWithDefault A placeholder op that passes through input when its output is not fed.
tensorflow::ops::PreventGradient An identity op that triggers an error if a gradient is requested.
tensorflow::ops::QuantizeAndDequantizeV2 Quantizes then dequantizes a tensor.
tensorflow::ops::QuantizeV2 Quantize the 'input' tensor of type float to 'output' tensor of type 'T'.
tensorflow::ops::QuantizedConcat Concatenates quantized tensors along one dimension.
tensorflow::ops::QuantizedInstanceNorm Quantized Instance normalization.
tensorflow::ops::QuantizedReshape Reshapes a quantized tensor as per the Reshape op.
tensorflow::ops::Rank Returns the rank of a tensor.
tensorflow::ops::Reshape Reshapes a tensor.
tensorflow::ops::ResourceStridedSliceAssign Assignvalue to the sliced l-value reference of ref.
tensorflow::ops::Reverse Reverses specific dimensions of a tensor.
tensorflow::ops::ReverseSequence Reverses variable length slices.
tensorflow::ops::ScatterNd Scatter updates into a new (initially zero) tensor according to indices.
tensorflow::ops::SetDiff1D Computes the difference between two lists of numbers or strings.
tensorflow::ops::Shape Returns the shape of a tensor.
tensorflow::ops::ShapeN Returns shape of tensors.
tensorflow::ops::Size Returns the size of a tensor.
tensorflow::ops::Slice Return a slice from 'input'.
tensorflow::ops::SpaceToBatch SpaceToBatch for 4-D tensors of type T.
tensorflow::ops::SpaceToBatchND SpaceToBatch for N-D tensors of type T.
tensorflow::ops::SpaceToDepth SpaceToDepth for tensors of type T.
tensorflow::ops::Split Splits a tensor into num_split tensors along one dimension.
tensorflow::ops::SplitV Splits a tensor into num_split tensors along one dimension.
tensorflow::ops::Squeeze Removes dimensions of size 1 from the shape of a tensor.
tensorflow::ops::Stack Packs a list of N rank-R tensors into one rank-(R+1) tensor.
tensorflow::ops::StopGradient Stops gradient computation.
tensorflow::ops::StridedSlice Return a strided slice from input.
tensorflow::ops::StridedSliceAssign Assignvalue to the sliced l-value reference of ref.
tensorflow::ops::StridedSliceGrad Returns the gradient of StridedSlice.
tensorflow::ops::Tile Constructs a tensor by tiling a given tensor.
tensorflow::ops::Transpose Shuffle dimensions of x according to a permutation.
tensorflow::ops::Unique Finds unique elements in a 1-D tensor.
tensorflow::ops::UniqueWithCounts Finds unique elements in a 1-D tensor.
tensorflow::ops::Unstack Unpacks a given dimension of a rank-R tensor into num rank-(R-1) tensors.
tensorflow::ops::Where Returns locations of true values in a boolean tensor.
tensorflow::ops::ZerosLike Returns a tensor of zeros with the same shape and type as x.

candidate_sampling_ops

Members
tensorflow::ops::AllCandidateSampler Generates labels for candidate sampling with a learned unigram distribution.
tensorflow::ops::ComputeAccidentalHits Computes the ids of the positions in sampled_candidates that match true_labels.
tensorflow::ops::FixedUnigramCandidateSampler Generates labels for candidate sampling with a learned unigram distribution.
tensorflow::ops::LearnedUnigramCandidateSampler Generates labels for candidate sampling with a learned unigram distribution.
tensorflow::ops::LogUniformCandidateSampler Generates labels for candidate sampling with a log-uniform distribution.
tensorflow::ops::UniformCandidateSampler Generates labels for candidate sampling with a uniform distribution.

control_flow_ops

Members
tensorflow::ops::Abort Raise a exception to abort the process when called.
tensorflow::ops::ControlTrigger Does nothing.
tensorflow::ops::LoopCond Forwards the input to the output.
tensorflow::ops::Merge Forwards the value of an available tensor from inputs to output.
tensorflow::ops::NextIteration Makes its input available to the next iteration.
tensorflow::ops::RefNextIteration Makes its input available to the next iteration.
tensorflow::ops::RefSelect Forwards the indexth element of inputs to output.
tensorflow::ops::RefSwitch Forwards the ref tensor data to the output port determined by pred.
tensorflow::ops::Switch Forwards data to the output port determined by pred.

core

Members
tensorflow::ClientSession A ClientSession object lets the caller drive the evaluation of the TensorFlow graph constructed with the C++ API.
tensorflow::Input Represents a tensor value that can be used as an operand to an Operation.
tensorflow::InputList A type for representing the input to ops that require a list of tensors.
tensorflow::Operation Represents a node in the computation graph.
tensorflow::Output Represents a tensor value produced by an Operation.
tensorflow::Scope A Scope object represents a set of related TensorFlow ops that have the same properties such as a common name prefix.
tensorflow::Status Denotes success or failure of a call in Tensorflow.
tensorflow::Tensor Represents an n-dimensional array of values.

data_flow_ops

Members
tensorflow::ops::AccumulatorApplyGradient Applies a gradient to a given accumulator.
tensorflow::ops::AccumulatorNumAccumulated Returns the number of gradients aggregated in the given accumulators.
tensorflow::ops::AccumulatorSetGlobalStep Updates the accumulator with a new value for global_step.
tensorflow::ops::AccumulatorTakeGradient Extracts the average gradient in the given ConditionalAccumulator.
tensorflow::ops::Barrier Defines a barrier that persists across different graph executions.
tensorflow::ops::BarrierClose Closes the given barrier.
tensorflow::ops::BarrierIncompleteSize Computes the number of incomplete elements in the given barrier.
tensorflow::ops::BarrierInsertMany For each key, assigns the respective value to the specified component.
tensorflow::ops::BarrierReadySize Computes the number of complete elements in the given barrier.
tensorflow::ops::BarrierTakeMany Takes the given number of completed elements from a barrier.
tensorflow::ops::ConditionalAccumulator A conditional accumulator for aggregating gradients.
tensorflow::ops::DeleteSessionTensor Delete the tensor specified by its handle in the session.
tensorflow::ops::DynamicPartition Partitions data into num_partitions tensors using indices from partitions.
tensorflow::ops::DynamicStitch Interleave the values from the data tensors into a single tensor.
tensorflow::ops::FIFOQueue A queue that produces elements in first-in first-out order.
tensorflow::ops::GetSessionHandle Store the input tensor in the state of the current session.
tensorflow::ops::GetSessionHandleV2 Store the input tensor in the state of the current session.
tensorflow::ops::GetSessionTensor Get the value of the tensor specified by its handle.
tensorflow::ops::PaddingFIFOQueue A queue that produces elements in first-in first-out order.
tensorflow::ops::PriorityQueue A queue that produces elements sorted by the first component value.
tensorflow::ops::QueueClose Closes the given queue.
tensorflow::ops::QueueDequeue Dequeues a tuple of one or more tensors from the given queue.
tensorflow::ops::QueueDequeueMany Dequeues n tuples of one or more tensors from the given queue.
tensorflow::ops::QueueDequeueUpTo Dequeues n tuples of one or more tensors from the given queue.
tensorflow::ops::QueueEnqueue Enqueues a tuple of one or more tensors in the given queue.
tensorflow::ops::QueueEnqueueMany Enqueues zero or more tuples of one or more tensors in the given queue.
tensorflow::ops::QueueSize Computes the number of elements in the given queue.
tensorflow::ops::RandomShuffleQueue A queue that randomizes the order of elements.
tensorflow::ops::RecordInput Emits randomized records.
tensorflow::ops::SparseAccumulatorApplyGradient Applies a sparse gradient to a given accumulator.
tensorflow::ops::SparseAccumulatorTakeGradient Extracts the average sparse gradient in a SparseConditionalAccumulator.
tensorflow::ops::SparseConditionalAccumulator A conditional accumulator for aggregating sparse gradients.
tensorflow::ops::Stage Stage values similar to a lightweight Enqueue.
tensorflow::ops::TensorArray An array of Tensors of given size.
tensorflow::ops::TensorArrayClose Delete the TensorArray from its resource container.
tensorflow::ops::TensorArrayConcat Concat the elements from the TensorArray into value value.
tensorflow::ops::TensorArrayGather Gather specific elements from the TensorArray into output value.
tensorflow::ops::TensorArrayGrad Creates a TensorArray for storing the gradients of values in the given handle.
tensorflow::ops::TensorArrayRead Read an element from the TensorArray into output value.
tensorflow::ops::TensorArrayScatter Scatter the data from the input value into specific TensorArray elements.
tensorflow::ops::TensorArraySize Get the current size of the TensorArray.
tensorflow::ops::TensorArraySplit Split the data from the input value into TensorArray elements.
tensorflow::ops::TensorArrayWrite Push an element onto the tensor_array.
tensorflow::ops::Unstage Op is similar to a lightweight Dequeue.

image_ops

Members
tensorflow::ops::AdjustContrast Adjust the contrast of one or more images.
tensorflow::ops::AdjustHue Adjust the hue of one or more images.
tensorflow::ops::AdjustSaturation Adjust the saturation of one or more images.
tensorflow::ops::CropAndResize Extracts crops from the input image tensor and bilinearly resizes them (possibly.
tensorflow::ops::CropAndResizeGradBoxes Computes the gradient of the crop_and_resize op wrt the input boxes tensor.
tensorflow::ops::CropAndResizeGradImage Computes the gradient of the crop_and_resize op wrt the input image tensor.
tensorflow::ops::DecodeGif Decode the first frame of a GIF-encoded image to a uint8 tensor.
tensorflow::ops::DecodeJpeg Decode a JPEG-encoded image to a uint8 tensor.
tensorflow::ops::DecodePng Decode a PNG-encoded image to a uint8 or uint16 tensor.
tensorflow::ops::DrawBoundingBoxes Draw bounding boxes on a batch of images.
tensorflow::ops::EncodeJpeg JPEG-encode an image.
tensorflow::ops::EncodePng PNG-encode an image.
tensorflow::ops::ExtractGlimpse Extracts a glimpse from the input tensor.
tensorflow::ops::HSVToRGB Convert one or more images from HSV to RGB.
tensorflow::ops::NonMaxSuppression Greedily selects a subset of bounding boxes in descending order of score,.
tensorflow::ops::RGBToHSV Converts one or more images from RGB to HSV.
tensorflow::ops::ResizeArea Resize images to size using area interpolation.
tensorflow::ops::ResizeBicubic Resize images to size using bicubic interpolation.
tensorflow::ops::ResizeBilinear Resize images to size using bilinear interpolation.
tensorflow::ops::ResizeNearestNeighbor Resize images to size using nearest neighbor interpolation.
tensorflow::ops::SampleDistortedBoundingBox Generate a single randomly distorted bounding box for an image.

io_ops

Members
tensorflow::ops::FixedLengthRecordReader A Reader that outputs fixed-length records from a file.
tensorflow::ops::IdentityReader A Reader that outputs the queued work as both the key and value.
tensorflow::ops::MatchingFiles Returns the set of files matching one or more glob patterns.
tensorflow::ops::MergeV2Checkpoints V2 format specific: merges the metadata files of sharded checkpoints.
tensorflow::ops::ReadFile Reads and outputs the entire contents of the input filename.
tensorflow::ops::ReaderNumRecordsProduced Returns the number of records this Reader has produced.
tensorflow::ops::ReaderNumWorkUnitsCompleted Returns the number of work units this Reader has finished processing.
tensorflow::ops::ReaderRead Returns the next record (key, value pair) produced by a Reader.
tensorflow::ops::ReaderReadUpTo Returns up to num_records (key, value) pairs produced by a Reader.
tensorflow::ops::ReaderReset Restore a Reader to its initial clean state.
tensorflow::ops::ReaderRestoreState Restore a reader to a previously saved state.
tensorflow::ops::ReaderSerializeState Produce a string tensor that encodes the state of a Reader.
tensorflow::ops::Restore Restores a tensor from checkpoint files.
tensorflow::ops::RestoreSlice Restores a tensor from checkpoint files.
tensorflow::ops::RestoreV2 Restores tensors from a V2 checkpoint.
tensorflow::ops::Save Saves the input tensors to disk.
tensorflow::ops::SaveSlices Saves input tensors slices to disk.
tensorflow::ops::SaveV2 Saves tensors in V2 checkpoint format.
tensorflow::ops::ShardedFilename Generate a sharded filename.
tensorflow::ops::ShardedFilespec Generate a glob pattern matching all sharded file names.
tensorflow::ops::TFRecordReader A Reader that outputs the records from a TensorFlow Records file.
tensorflow::ops::TextLineReader A Reader that outputs the lines of a file delimited by '
'.
tensorflow::ops::WholeFileReader A Reader that outputs the entire contents of a file as a value.
tensorflow::ops::WriteFile Writes contents to the file at input filename.

logging_ops

Members
tensorflow::ops::Assert Asserts that the given condition is true.
tensorflow::ops::HistogramSummary Outputs a Summary protocol buffer with a histogram.
tensorflow::ops::MergeSummary Merges summaries.
tensorflow::ops::Print Prints a list of tensors.
tensorflow::ops::ScalarSummary Outputs a Summary protocol buffer with scalar values.
tensorflow::ops::TensorSummary Outputs a Summary protocol buffer with a tensor.

math_ops

Members
tensorflow::ops::Abs Computes the absolute value of a tensor.
tensorflow::ops::Acos Computes acos of x element-wise.
tensorflow::ops::Add Returns x + y element-wise.
tensorflow::ops::AddN Add all input tensors element wise.
tensorflow::ops::All Computes the "logical and" of elements across dimensions of a tensor.
tensorflow::ops::Any Computes the "logical or" of elements across dimensions of a tensor.
tensorflow::ops::ApproximateEqual Returns the truth value of abs(x-y) < tolerance element-wise.
tensorflow::ops::ArgMax Returns the index with the largest value across dimensions of a tensor.
tensorflow::ops::ArgMin Returns the index with the smallest value across dimensions of a tensor.
tensorflow::ops::Asin Computes asin of x element-wise.
tensorflow::ops::Atan Computes atan of x element-wise.
tensorflow::ops::Atan2 Computes arctangent of y/x element-wise, respecting signs of the arguments.
tensorflow::ops::BatchMatMul Multiplies slices of two tensors in batches.
tensorflow::ops::Betainc Compute the regularized incomplete beta integral \(I_x(a, b)\).
tensorflow::ops::Bincount Counts the number of occurrences of each value in an integer array.
tensorflow::ops::Bucketize Bucketizes 'input' based on 'boundaries'.
tensorflow::ops::Cast Cast x of type SrcT to y of DstT.
tensorflow::ops::Ceil Returns element-wise smallest integer in not less than x.
tensorflow::ops::Complex Converts two real numbers to a complex number.
tensorflow::ops::ComplexAbs Computes the complex absolute value of a tensor.
tensorflow::ops::Conj Returns the complex conjugate of a complex number.
tensorflow::ops::Cos Computes cos of x element-wise.
tensorflow::ops::Cross Compute the pairwise cross product.
tensorflow::ops::Cumprod Compute the cumulative product of the tensor x along axis.
tensorflow::ops::Cumsum Compute the cumulative sum of the tensor x along axis.
tensorflow::ops::Digamma Computes Psi, the derivative of Lgamma (the log of the absolute value of.
tensorflow::ops::Div Returns x / y element-wise.
tensorflow::ops::Equal Returns the truth value of (x == y) element-wise.
tensorflow::ops::Erf Computes the Gauss error function of x element-wise.
tensorflow::ops::Erfc Computes the complementary error function of x element-wise.
tensorflow::ops::Exp Computes exponential of x element-wise.
tensorflow::ops::Expm1 Computes exponential of x - 1 element-wise.
tensorflow::ops::Floor Returns element-wise largest integer not greater than x.
tensorflow::ops::FloorDiv Returns x // y element-wise.
tensorflow::ops::FloorMod Returns element-wise remainder of division.
tensorflow::ops::Greater Returns the truth value of (x > y) element-wise.
tensorflow::ops::GreaterEqual Returns the truth value of (x >= y) element-wise.
tensorflow::ops::Igamma Compute the lower regularized incomplete Gamma function Q(a, x).
tensorflow::ops::Igammac Compute the upper regularized incomplete Gamma function Q(a, x).
tensorflow::ops::Imag Returns the imaginary part of a complex number.
tensorflow::ops::IsFinite Returns which elements of x are finite.
tensorflow::ops::IsInf Returns which elements of x are Inf.
tensorflow::ops::IsNan Returns which elements of x are NaN.
tensorflow::ops::Less Returns the truth value of (x < y) element-wise.
tensorflow::ops::LessEqual Returns the truth value of (x <= y) element-wise.
tensorflow::ops::Lgamma Computes the log of the absolute value of Gamma(x) element-wise.
tensorflow::ops::LinSpace Generates values in an interval.
tensorflow::ops::Log Computes natural logarithm of x element-wise.
tensorflow::ops::Log1p Computes natural logarithm of (1 + x) element-wise.
tensorflow::ops::LogicalAnd Returns the truth value of x AND y element-wise.
tensorflow::ops::LogicalNot Returns the truth value of NOT x element-wise.
tensorflow::ops::LogicalOr Returns the truth value of x OR y element-wise.
tensorflow::ops::MatMul Multiply the matrix "a" by the matrix "b".
tensorflow::ops::Max Computes the maximum of elements across dimensions of a tensor.
tensorflow::ops::Maximum Returns the max of x and y (i.e.
tensorflow::ops::Mean Computes the mean of elements across dimensions of a tensor.
tensorflow::ops::Min Computes the minimum of elements across dimensions of a tensor.
tensorflow::ops::Minimum Returns the min of x and y (i.e.
tensorflow::ops::Mod Returns element-wise remainder of division.
tensorflow::ops::Multiply Returns x * y element-wise.
tensorflow::ops::Negate Computes numerical negative value element-wise.
tensorflow::ops::NotEqual Returns the truth value of (x != y) element-wise.
tensorflow::ops::Polygamma Compute the polygamma function \(^{(n)}(x)\).
tensorflow::ops::Pow Computes the power of one value to another.
tensorflow::ops::Prod Computes the product of elements across dimensions of a tensor.
tensorflow::ops::QuantizeDownAndShrinkRange Convert the quantized 'input' tensor into a lower-precision 'output', using the.
tensorflow::ops::QuantizedMatMul Perform a quantized matrix multiplication of a by the matrix b.
tensorflow::ops::QuantizedMul Returns x * y element-wise, working on quantized buffers.
tensorflow::ops::Range Creates a sequence of numbers.
tensorflow::ops::Real Returns the real part of a complex number.
tensorflow::ops::RealDiv Returns x / y element-wise for real types.
tensorflow::ops::Reciprocal Computes the reciprocal of x element-wise.
tensorflow::ops::RequantizationRange Given a quantized tensor described by (input, input_min, input_max), outputs a.
tensorflow::ops::Requantize Convert the quantized 'input' tensor into a lower-precision 'output', using the.
tensorflow::ops::Rint Returns element-wise integer closest to x.
tensorflow::ops::Round Rounds the values of a tensor to the nearest integer, element-wise.
tensorflow::ops::Rsqrt Computes reciprocal of square root of x element-wise.
tensorflow::ops::SegmentMax Computes the maximum along segments of a tensor.
tensorflow::ops::SegmentMean Computes the mean along segments of a tensor.
tensorflow::ops::SegmentMin Computes the minimum along segments of a tensor.
tensorflow::ops::SegmentProd Computes the product along segments of a tensor.
tensorflow::ops::SegmentSum Computes the sum along segments of a tensor.
tensorflow::ops::Sigmoid Computes sigmoid of x element-wise.
tensorflow::ops::Sign Returns an element-wise indication of the sign of a number.
tensorflow::ops::Sin Computes sin of x element-wise.
tensorflow::ops::SparseMatMul Multiply matrix "a" by matrix "b".
tensorflow::ops::SparseSegmentMean Computes the mean along sparse segments of a tensor.
tensorflow::ops::SparseSegmentMeanGrad Computes gradients for SparseSegmentMean.
tensorflow::ops::SparseSegmentSqrtN Computes the sum along sparse segments of a tensor divided by the sqrt of N.
tensorflow::ops::SparseSegmentSqrtNGrad Computes gradients for SparseSegmentSqrtN.
tensorflow::ops::SparseSegmentSum Computes the sum along sparse segments of a tensor.
tensorflow::ops::Sqrt Computes square root of x element-wise.
tensorflow::ops::Square Computes square of x element-wise.
tensorflow::ops::SquaredDifference Returns (x - y)(x - y) element-wise.
tensorflow::ops::Subtract Returns x - y element-wise.
tensorflow::ops::Sum Computes the sum of elements across dimensions of a tensor.
tensorflow::ops::Tan Computes tan of x element-wise.
tensorflow::ops::Tanh Computes hyperbolic tangent of x element-wise.
tensorflow::ops::TruncateDiv Returns x / y element-wise for integer types.
tensorflow::ops::TruncateMod Returns element-wise remainder of division.
tensorflow::ops::UnsortedSegmentMax Computes the Max along segments of a tensor.
tensorflow::ops::UnsortedSegmentSum Computes the sum along segments of a tensor.
tensorflow::ops::Where3 Selects elements from x or y, depending on condition.
tensorflow::ops::Zeta Compute the Hurwitz zeta function \((x, q)\).

nn_ops

Members
tensorflow::ops::AvgPool Performs average pooling on the input.
tensorflow::ops::AvgPool3D Performs 3D average pooling on the input.
tensorflow::ops::AvgPool3DGrad Computes gradients of average pooling function.
tensorflow::ops::BiasAdd Adds bias to value.
tensorflow::ops::BiasAddGrad The backward operation for "BiasAdd" on the "bias" tensor.
tensorflow::ops::Conv2D Computes a 2-D convolution given 4-D input and filter tensors.
tensorflow::ops::Conv2DBackpropFilter Computes the gradients of convolution with respect to the filter.
tensorflow::ops::Conv2DBackpropInput Computes the gradients of convolution with respect to the input.
tensorflow::ops::Conv3D Computes a 3-D convolution given 5-D input and filter tensors.
tensorflow::ops::Conv3DBackpropFilterV2 Computes the gradients of 3-D convolution with respect to the filter.
tensorflow::ops::Conv3DBackpropInputV2 Computes the gradients of 3-D convolution with respect to the input.
tensorflow::ops::DepthwiseConv2dNative Computes a 2-D depthwise convolution given 4-D input and filter tensors.
tensorflow::ops::DepthwiseConv2dNativeBackpropFilter Computes the gradients of depthwise convolution with respect to the filter.
tensorflow::ops::DepthwiseConv2dNativeBackpropInput Computes the gradients of depthwise convolution with respect to the input.
tensorflow::ops::Dilation2D Computes the grayscale dilation of 4-D input and 3-D filter tensors.
tensorflow::ops::Dilation2DBackpropFilter Computes the gradient of morphological 2-D dilation with respect to the filter.
tensorflow::ops::Dilation2DBackpropInput Computes the gradient of morphological 2-D dilation with respect to the input.
tensorflow::ops::Elu Computes exponential linear: exp(features) - 1 if < 0, features otherwise.
tensorflow::ops::FractionalAvgPool Performs fractional average pooling on the input.
tensorflow::ops::FractionalMaxPool Performs fractional max pooling on the input.
tensorflow::ops::FusedBatchNorm Batch normalization.
tensorflow::ops::FusedBatchNormGrad Gradient for batch normalization.
tensorflow::ops::FusedPadConv2D Performs a padding as a preprocess during a convolution.
tensorflow::ops::FusedResizeAndPadConv2D Performs a resize and padding as a preprocess during a convolution.
tensorflow::ops::InTopK Says whether the targets are in the top K predictions.
tensorflow::ops::L2Loss L2 Loss.
tensorflow::ops::LRN Local Response Normalization.
tensorflow::ops::LogSoftmax Computes log softmax activations.
tensorflow::ops::MaxPool Performs max pooling on the input.
tensorflow::ops::MaxPool3D Performs 3D max pooling on the input.
tensorflow::ops::MaxPool3DGrad Computes gradients of max pooling function.
tensorflow::ops::MaxPool3DGradGrad Computes second-order gradients of the maxpooling function.
tensorflow::ops::MaxPoolGradGrad Computes second-order gradients of the maxpooling function.
tensorflow::ops::MaxPoolGradGradWithArgmax Computes second-order gradients of the maxpooling function.
tensorflow::ops::MaxPoolWithArgmax Performs max pooling on the input and outputs both max values and indices.
tensorflow::ops::QuantizedAvgPool Produces the average pool of the input tensor for quantized types.
tensorflow::ops::QuantizedBatchNormWithGlobalNormalization Quantized Batch normalization.
tensorflow::ops::QuantizedBiasAdd Adds Tensor 'bias' to Tensor 'input' for Quantized types.
tensorflow::ops::QuantizedConv2D Computes a 2D convolution given quantized 4D input and filter tensors.
tensorflow::ops::QuantizedMaxPool Produces the max pool of the input tensor for quantized types.
tensorflow::ops::QuantizedRelu Computes Quantized Rectified Linear: max(features, 0)
tensorflow::ops::QuantizedRelu6 Computes Quantized Rectified Linear 6: min(max(features, 0), 6)
tensorflow::ops::QuantizedReluX Computes Quantized Rectified Linear X: min(max(features, 0), max_value)
tensorflow::ops::Relu Computes rectified linear: max(features, 0).
tensorflow::ops::Relu6 Computes rectified linear 6: min(max(features, 0), 6).
tensorflow::ops::Softmax Computes softmax activations.
tensorflow::ops::SoftmaxCrossEntropyWithLogits Computes softmax cross entropy cost and gradients to backpropagate.
tensorflow::ops::Softplus Computes softplus: log(exp(features) + 1).
tensorflow::ops::Softsign Computes softsign: features / (abs(features) + 1).
tensorflow::ops::SparseSoftmaxCrossEntropyWithLogits Computes softmax cross entropy cost and gradients to backpropagate.
tensorflow::ops::TopK Finds values and indices of the k largest elements for the last dimension.

no_op

Members
tensorflow::ops::NoOp Does nothing.

parsing_ops

Members
tensorflow::ops::DecodeCSV Convert CSV records to tensors.
tensorflow::ops::DecodeJSONExample Convert JSON-encoded Example records to binary protocol buffer strings.
tensorflow::ops::DecodeRaw Reinterpret the bytes of a string as a vector of numbers.
tensorflow::ops::ParseExample Transforms a vector of brain.Example protos (as strings) into typed tensors.
tensorflow::ops::ParseSingleSequenceExample Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors.
tensorflow::ops::ParseTensor Transforms a serialized tensorflow.TensorProto proto into a Tensor.
tensorflow::ops::StringToNumber Converts each string in the input Tensor to the specified numeric type.

random_ops

Members
tensorflow::ops::Multinomial Draws samples from a multinomial distribution.
tensorflow::ops::ParameterizedTruncatedNormal Outputs random values from a normal distribution.
tensorflow::ops::RandomGamma Outputs random values from the Gamma distribution(s) described by alpha.
tensorflow::ops::RandomNormal Outputs random values from a normal distribution.
tensorflow::ops::RandomPoisson Outputs random values from the Poisson distribution(s) described by rate.
tensorflow::ops::RandomShuffle Randomly shuffles a tensor along its first dimension.
tensorflow::ops::RandomUniform Outputs random values from a uniform distribution.
tensorflow::ops::RandomUniformInt Outputs random integers from a uniform distribution.
tensorflow::ops::TruncatedNormal Outputs random values from a truncated normal distribution.

sparse_ops

Members
tensorflow::ops::AddManySparseToTensorsMap Add an N-minibatch SparseTensor to a SparseTensorsMap, return N handles.
tensorflow::ops::AddSparseToTensorsMap Add a SparseTensor to a SparseTensorsMap return its handle.
tensorflow::ops::DeserializeManySparse Deserialize and concatenate SparseTensors from a serialized minibatch.
tensorflow::ops::SerializeManySparse Serialize an N-minibatch SparseTensor into an [N, 3] string Tensor.
tensorflow::ops::SerializeSparse Serialize a SparseTensor into a string 3-vector (1-D Tensor) object.
tensorflow::ops::SparseAdd Adds two SparseTensor objects to produce another SparseTensor.
tensorflow::ops::SparseAddGrad The gradient operator for the SparseAdd op.
tensorflow::ops::SparseConcat Concatenates a list of SparseTensor along the specified dimension.
tensorflow::ops::SparseCross Generates sparse cross from a list of sparse and dense tensors.
tensorflow::ops::SparseDenseCwiseAdd Adds up a SparseTensor and a dense Tensor, using these special rules:
tensorflow::ops::SparseDenseCwiseDiv Component-wise divides a SparseTensor by a dense Tensor.
tensorflow::ops::SparseDenseCwiseMul Component-wise multiplies a SparseTensor by a dense Tensor.
tensorflow::ops::SparseReduceSum Computes the sum of elements across dimensions of a SparseTensor.
tensorflow::ops::SparseReduceSumSparse Computes the sum of elements across dimensions of a SparseTensor.
tensorflow::ops::SparseReorder Reorders a SparseTensor into the canonical, row-major ordering.
tensorflow::ops::SparseReshape Reshapes a SparseTensor to represent values in a new dense shape.
tensorflow::ops::SparseSoftmax Applies softmax to a batched N-D SparseTensor.
tensorflow::ops::SparseSparseMaximum Returns the element-wise max of two SparseTensors.
tensorflow::ops::SparseSparseMinimum Returns the element-wise min of two SparseTensors.
tensorflow::ops::SparseSplit Split a SparseTensor into num_split tensors along one dimension.
tensorflow::ops::SparseTensorDenseAdd Adds up a SparseTensor and a dense Tensor, producing a dense Tensor.
tensorflow::ops::SparseTensorDenseMatMul Multiply SparseTensor (of rank 2) "A" by dense matrix "B".
tensorflow::ops::SparseToDense Converts a sparse representation into a dense tensor.
tensorflow::ops::TakeManySparseFromTensorsMap Read SparseTensors from a SparseTensorsMap and concatenate them.

state_ops

Members
tensorflow::ops::Assign Update 'ref' by assigning 'value' to it.
tensorflow::ops::AssignAdd Update 'ref' by adding 'value' to it.
tensorflow::ops::AssignSub Update 'ref' by subtracting 'value' from it.
tensorflow::ops::CountUpTo Increments 'ref' until it reaches 'limit'.
tensorflow::ops::DestroyTemporaryVariable Destroys the temporary variable and returns its final value.
tensorflow::ops::IsVariableInitialized Checks whether a tensor has been initialized.
tensorflow::ops::ScatterAdd Adds sparse updates to a variable reference.
tensorflow::ops::ScatterDiv Divides a variable reference by sparse updates.
tensorflow::ops::ScatterMul Multiplies sparse updates into a variable reference.
tensorflow::ops::ScatterNdAdd Applies sparse addition between updates and individual values or slices.
tensorflow::ops::ScatterNdSub Applies sparse subtraction between updates and individual values or slices.
tensorflow::ops::ScatterNdUpdate Applies sparse updates to individual values or slices within a given.
tensorflow::ops::ScatterSub Subtracts sparse updates to a variable reference.
tensorflow::ops::ScatterUpdate Applies sparse updates to a variable reference.
tensorflow::ops::TemporaryVariable Returns a tensor that may be mutated, but only persists within a single step.
tensorflow::ops::Variable Holds state in the form of a tensor that persists across steps.

string_ops

Members
tensorflow::ops::AsString Converts each entry in the given tensor to strings.
tensorflow::ops::DecodeBase64 Decode web-safe base64-encoded strings.
tensorflow::ops::EncodeBase64 Encode strings into web-safe base64 format.
tensorflow::ops::ReduceJoin Joins a string Tensor across the given dimensions.
tensorflow::ops::StringJoin Joins the strings in the given list of string tensors into one tensor;.
tensorflow::ops::StringSplit Split elements of input based on delimiter into a SparseTensor.
tensorflow::ops::StringToHashBucket Converts each string in the input Tensor to its hash mod by a number of buckets.
tensorflow::ops::StringToHashBucketFast Converts each string in the input Tensor to its hash mod by a number of buckets.
tensorflow::ops::StringToHashBucketStrong Converts each string in the input Tensor to its hash mod by a number of buckets.
tensorflow::ops::Substr Return substrings from Tensor of strings.

training_ops

Members
tensorflow::ops::ApplyAdadelta Update '*var' according to the adadelta scheme.
tensorflow::ops::ApplyAdagrad Update '*var' according to the adagrad scheme.
tensorflow::ops::ApplyAdagradDA Update '*var' according to the proximal adagrad scheme.
tensorflow::ops::ApplyAdam Update '*var' according to the Adam algorithm.
tensorflow::ops::ApplyCenteredRMSProp Update '*var' according to the centered RMSProp algorithm.
tensorflow::ops::ApplyFtrl Update '*var' according to the Ftrl-proximal scheme.
tensorflow::ops::ApplyGradientDescent Update '*var' by subtracting 'alpha' * 'delta' from it.
tensorflow::ops::ApplyMomentum Update '*var' according to the momentum scheme.
tensorflow::ops::ApplyProximalAdagrad Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
tensorflow::ops::ApplyProximalGradientDescent Update '*var' as FOBOS algorithm with fixed learning rate.
tensorflow::ops::ApplyRMSProp Update '*var' according to the RMSProp algorithm.
tensorflow::ops::ResourceApplyAdadelta Update '*var' according to the adadelta scheme.
tensorflow::ops::ResourceApplyAdagrad Update '*var' according to the adagrad scheme.
tensorflow::ops::ResourceApplyAdagradDA Update '*var' according to the proximal adagrad scheme.
tensorflow::ops::ResourceApplyAdam Update '*var' according to the Adam algorithm.
tensorflow::ops::ResourceApplyCenteredRMSProp Update '*var' according to the centered RMSProp algorithm.
tensorflow::ops::ResourceApplyFtrl Update '*var' according to the Ftrl-proximal scheme.
tensorflow::ops::ResourceApplyGradientDescent Update '*var' by subtracting 'alpha' * 'delta' from it.
tensorflow::ops::ResourceApplyMomentum Update '*var' according to the momentum scheme.
tensorflow::ops::ResourceApplyProximalAdagrad Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
tensorflow::ops::ResourceApplyProximalGradientDescent Update '*var' as FOBOS algorithm with fixed learning rate.
tensorflow::ops::ResourceApplyRMSProp Update '*var' according to the RMSProp algorithm.
tensorflow::ops::ResourceSparseApplyAdadelta var: Should be from a Variable().
tensorflow::ops::ResourceSparseApplyAdagrad Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
tensorflow::ops::ResourceSparseApplyAdagradDA Update entries in '*var' and '*accum' according to the proximal adagrad scheme.
tensorflow::ops::ResourceSparseApplyCenteredRMSProp Update '*var' according to the centered RMSProp algorithm.
tensorflow::ops::ResourceSparseApplyFtrl Update relevant entries in '*var' according to the Ftrl-proximal scheme.
tensorflow::ops::ResourceSparseApplyMomentum Update relevant entries in '*var' and '*accum' according to the momentum scheme.
tensorflow::ops::ResourceSparseApplyProximalAdagrad Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
tensorflow::ops::ResourceSparseApplyProximalGradientDescent Sparse update '*var' as FOBOS algorithm with fixed learning rate.
tensorflow::ops::ResourceSparseApplyRMSProp Update '*var' according to the RMSProp algorithm.
tensorflow::ops::SparseApplyAdadelta var: Should be from a Variable().
tensorflow::ops::SparseApplyAdagrad Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
tensorflow::ops::SparseApplyAdagradDA Update entries in '*var' and '*accum' according to the proximal adagrad scheme.
tensorflow::ops::SparseApplyCenteredRMSProp Update '*var' according to the centered RMSProp algorithm.
tensorflow::ops::SparseApplyFtrl Update relevant entries in '*var' according to the Ftrl-proximal scheme.
tensorflow::ops::SparseApplyMomentum Update relevant entries in '*var' and '*accum' according to the momentum scheme.
tensorflow::ops::SparseApplyProximalAdagrad Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
tensorflow::ops::SparseApplyProximalGradientDescent Sparse update '*var' as FOBOS algorithm with fixed learning rate.
tensorflow::ops::SparseApplyRMSProp Update '*var' according to the RMSProp algorithm.

user_ops

Members
tensorflow::ops::Fact Output a fact about factorials.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
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