tensorflow::ops

Summary

Typedefs

Mul typedef
Neg typedef
ReduceAll typedef
All
ReduceAny typedef
Any
ReduceMax typedef
Max
ReduceMean typedef
ReduceMin typedef
Min
ReduceProd typedef
ReduceSum typedef
Sum
Sub typedef

Functions

AsNodeOut(const Scope & scope, const Input & inp)
NodeBuilder::NodeOut
AsNodeOutList(const Scope & scope, const InputList & inp)
std::vector< NodeBuilder::NodeOut >
AudioSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, ::tensorflow::Input sample_rate)
AudioSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, ::tensorflow::Input sample_rate, const AudioSummary::Attrs & attrs)
BadColor(const TensorProto & x)
Attrs
Color to use for pixels with non-finite values.
Const(const Scope & scope, const Input::Initializer & val)
Const(const Scope & scope, const T & v, const TensorShape shape)
Const(const Scope & scope, const std::initializer_list< T > & v, const TensorShape shape)
ConstFromProto(const Scope & scope, const TensorProto & proto)
ImageSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor)
ImageSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, const ImageSummary::Attrs & attrs)
MaxImages(int64 x)
Attrs
MaxOutputs(int64 x)
Attrs
node() const
::tensorflow::Node *
range(It represents the value of a *pixel in the output image).Non-finite values in the input tensor are *replaced by this tensor in the output image.The default value is the color *red.**Arguments
image **If max_images is greater the summary value tags are *generated sequentially as *tag *tag etc **The bad_color argument is the color to use in the generated images for *non finite input values It is a unit8 D tensor of length channels *Each element must be in the
Max number of batch elements to generate images for.

Classes

tensorflow::ops::Abort

Raise a exception to abort the process when called.

tensorflow::ops::Abs

Computes the absolute value of a tensor.

tensorflow::ops::AccumulateNV2

Returns the element-wise sum of a list of tensors.

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::Acos

Computes acos of x element-wise.

tensorflow::ops::Acosh

Computes inverse hyperbolic cosine of x element-wise.

tensorflow::ops::Add

Returns x + y element-wise.

tensorflow::ops::AddManySparseToTensorsMap

Add an N-minibatch SparseTensor to a SparseTensorsMap, return N handles.

tensorflow::ops::AddN

Add all input tensors element wise.

tensorflow::ops::AddSparseToTensorsMap

Add a SparseTensor to a SparseTensorsMap return its handle.

tensorflow::ops::AddV2

Returns x + y element-wise.

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::All

Computes the "logical and" of elements across dimensions of a tensor.

tensorflow::ops::AllCandidateSampler

Generates labels for candidate sampling with a learned unigram distribution.

tensorflow::ops::Angle

Returns the argument of a complex number.

tensorflow::ops::Any

Computes the "logical or" of elements across dimensions of a tensor.

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::ApplyAddSign

Update '*var' according to the AddSign update.

tensorflow::ops::ApplyCenteredRMSProp

Update '*var' according to the centered RMSProp algorithm.

tensorflow::ops::ApplyFtrl

Update '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ApplyFtrlV2

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::ApplyPowerSign

Update '*var' according to the AddSign update.

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::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::AsString

Converts each entry in the given tensor to strings.

tensorflow::ops::Asin

Computes asin of x element-wise.

tensorflow::ops::Asinh

Computes inverse hyperbolic sine of x element-wise.

tensorflow::ops::Assert

Asserts that the given condition is true.

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::Atan

Computes atan of x element-wise.

tensorflow::ops::Atan2

Computes arctangent of y/x element-wise, respecting signs of the arguments.

tensorflow::ops::Atanh

Computes inverse hyperbolic tangent of x element-wise.

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::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::BatchMatMul

Multiplies slices of two tensors in batches.

tensorflow::ops::BatchToSpace

BatchToSpace for 4-D tensors of type T.

tensorflow::ops::BatchToSpaceND

BatchToSpace for N-D tensors of type T.

tensorflow::ops::Betainc

Compute the regularized incomplete beta integral \(I_x(a, b)\).

tensorflow::ops::BiasAdd

Adds bias to value.

tensorflow::ops::BiasAddGrad

The backward operation for "BiasAdd" on the "bias" tensor.

tensorflow::ops::Bincount

Counts the number of occurrences of each value in an integer array.

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::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::CheckNumerics

Checks a tensor for NaN and Inf values.

tensorflow::ops::CompareAndBitpack

Compare values of input to threshold and pack resulting bits into a uint8.

tensorflow::ops::Complex

Converts two real numbers to a complex number.

tensorflow::ops::ComplexAbs

Computes the complex absolute value of a tensor.

tensorflow::ops::ComputeAccidentalHits

Computes the ids of the positions in sampled_candidates that match true_labels.

tensorflow::ops::Concat

Concatenates tensors along one dimension.

tensorflow::ops::ConditionalAccumulator

A conditional accumulator for aggregating gradients.

tensorflow::ops::Conj

Returns the complex conjugate of a complex number.

tensorflow::ops::ConjugateTranspose

Shuffle dimensions of x according to a permutation and conjugate the result.

tensorflow::ops::ControlTrigger

Does nothing.

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::Cos

Computes cos of x element-wise.

tensorflow::ops::Cosh

Computes hyperbolic cosine of x element-wise.

tensorflow::ops::CountUpTo

Increments 'ref' until it reaches 'limit'.

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::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::DataFormatDimMap

Returns the dimension index in the destination data format given the one in.

tensorflow::ops::DataFormatVecPermute

Returns the permuted vector/tensor in the destination data format given the.

tensorflow::ops::DebugGradientIdentity

Identity op for gradient debugging.

tensorflow::ops::DebugGradientRefIdentity

Identity op for gradient debugging.

tensorflow::ops::DecodeAndCropJpeg

Decode and Crop a JPEG-encoded image to a uint8 tensor.

tensorflow::ops::DecodeBase64

Decode web-safe base64-encoded strings.

tensorflow::ops::DecodeBmp

Decode the first frame of a BMP-encoded image to a uint8 tensor.

tensorflow::ops::DecodeCSV

Convert CSV records to tensors.

tensorflow::ops::DecodeCompressed

Decompress strings.

tensorflow::ops::DecodeGif

Decode the first frame of a GIF-encoded image to a uint8 tensor.

tensorflow::ops::DecodeJSONExample

Convert JSON-encoded Example records to binary protocol buffer strings.

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::DecodeRaw

Reinterpret the bytes of a string as a vector of numbers.

tensorflow::ops::DeleteSessionTensor

Delete the tensor specified by its handle in the session.

tensorflow::ops::DepthToSpace

DepthToSpace for tensors of type T.

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::Dequantize

Dequantize the 'input' tensor into a float Tensor.

tensorflow::ops::DeserializeManySparse

Deserialize and concatenate SparseTensors from a serialized minibatch.

tensorflow::ops::DeserializeSparse

Deserialize SparseTensor objects.

tensorflow::ops::DestroyTemporaryVariable

Destroys the temporary variable and returns its final value.

tensorflow::ops::Diag

Returns a diagonal tensor with a given diagonal values.

tensorflow::ops::DiagPart

Returns the diagonal part of the tensor.

tensorflow::ops::Digamma

Computes Psi, the derivative of Lgamma (the log of the absolute value of.

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::Div

Returns x / y element-wise.

tensorflow::ops::DrawBoundingBoxes

Draw bounding boxes on a batch of images.

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::EditDistance

Computes the (possibly normalized) Levenshtein Edit Distance.

tensorflow::ops::Elu

Computes exponential linear: exp(features) - 1 if < 0, features otherwise.

tensorflow::ops::EncodeBase64

Encode strings into web-safe base64 format.

tensorflow::ops::EncodeJpeg

JPEG-encode an image.

tensorflow::ops::EncodePng

PNG-encode an image.

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::ExpandDims

Inserts a dimension of 1 into a tensor's shape.

tensorflow::ops::Expm1

Computes exponential of x - 1 element-wise.

tensorflow::ops::ExtractGlimpse

Extracts a glimpse from the input tensor.

tensorflow::ops::ExtractImagePatches

Extract patches from images and put them in the "depth" output dimension.

tensorflow::ops::ExtractJpegShape

Extract the shape information of a JPEG-encoded image.

tensorflow::ops::FIFOQueue

A queue that produces elements in first-in first-out order.

tensorflow::ops::Fact

Output a fact about factorials.

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::FixedLengthRecordReader

A Reader that outputs fixed-length records from a file.

tensorflow::ops::FixedUnigramCandidateSampler

Generates labels for candidate sampling with a learned unigram distribution.

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::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::FusedBatchNormGradV2

Gradient for batch normalization.

tensorflow::ops::FusedBatchNormV2

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::Gather

Gather slices from params according to indices.

tensorflow::ops::GatherNd

Gather slices from params into a Tensor with shape specified by indices.

tensorflow::ops::GatherV2

Gather slices from params axis axis according to indices.

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::Greater

Returns the truth value of (x > y) element-wise.

tensorflow::ops::GreaterEqual

Returns the truth value of (x >= y) element-wise.

tensorflow::ops::GuaranteeConst

Gives a guarantee to the TF runtime that the input tensor is a constant.

tensorflow::ops::HSVToRGB

Convert one or more images from HSV to RGB.

tensorflow::ops::HistogramFixedWidth

Return histogram of values.

tensorflow::ops::HistogramSummary

Outputs a Summary protocol buffer with a histogram.

tensorflow::ops::Identity

Return a tensor with the same shape and contents as the input tensor or value.

tensorflow::ops::IdentityN

Returns a list of tensors with the same shapes and contents as the input.

tensorflow::ops::IdentityReader

A Reader that outputs the queued work as both the key and value.

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::ImmutableConst

Returns immutable tensor from memory region.

tensorflow::ops::InTopK

Says whether the targets are in the top K predictions.

tensorflow::ops::InTopKV2

Says whether the targets are in the top K predictions.

tensorflow::ops::Inv

Computes the reciprocal of x element-wise.

tensorflow::ops::InvertPermutation

Computes the inverse permutation of a tensor.

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::IsVariableInitialized

Checks whether a tensor has been initialized.

tensorflow::ops::L2Loss

L2 Loss.

tensorflow::ops::LMDBReader

A Reader that outputs the records from a LMDB file.

tensorflow::ops::LRN

Local Response Normalization.

tensorflow::ops::LearnedUnigramCandidateSampler

Generates labels for candidate sampling with a learned unigram distribution.

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::LogSoftmax

Computes log softmax activations.

tensorflow::ops::LogUniformCandidateSampler

Generates labels for candidate sampling with a log-uniform distribution.

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::LoopCond

Forwards the input to the output.

tensorflow::ops::MapClear

Op removes all elements in the underlying container.

tensorflow::ops::MapIncompleteSize

Op returns the number of incomplete elements in the underlying container.

tensorflow::ops::MapPeek

Op peeks at the values at the specified key.

tensorflow::ops::MapSize

Op returns the number of elements in the underlying container.

tensorflow::ops::MapStage

Stage (key, values) in the underlying container which behaves like a hashtable.

tensorflow::ops::MapUnstage

Op removes and returns the values associated with the key.

tensorflow::ops::MapUnstageNoKey

Op removes and returns a random (key, value)

tensorflow::ops::MatMul

Multiply the matrix "a" by the matrix "b".

tensorflow::ops::MatchingFiles

Returns the set of files matching one or more glob patterns.

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::Max

Computes the maximum of elements across dimensions of a tensor.

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::MaxPoolGradGradV2

Computes second-order gradients of the maxpooling function.

tensorflow::ops::MaxPoolGradGradWithArgmax

Computes second-order gradients of the maxpooling function.

tensorflow::ops::MaxPoolGradV2

Computes gradients of the maxpooling function.

tensorflow::ops::MaxPoolV2

Performs max pooling on the input.

tensorflow::ops::MaxPoolWithArgmax

Performs max pooling on the input and outputs both max values and indices.

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::Merge

Forwards the value of an available tensor from inputs to output.

tensorflow::ops::MergeSummary

Merges summaries.

tensorflow::ops::MergeV2Checkpoints

V2 format specific: merges the metadata files of sharded checkpoints.

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::MirrorPad

Pads a tensor with mirrored values.

tensorflow::ops::Mod

Returns element-wise remainder of division.

tensorflow::ops::Multinomial

Draws samples from a multinomial distribution.

tensorflow::ops::Multiply

Returns x * y element-wise.

tensorflow::ops::Negate

Computes numerical negative value element-wise.

tensorflow::ops::NextIteration

Makes its input available to the next iteration.

tensorflow::ops::NoOp

Does nothing.

tensorflow::ops::NonMaxSuppression

Greedily selects a subset of bounding boxes in descending order of score,.

tensorflow::ops::NonMaxSuppressionV2

Greedily selects a subset of bounding boxes in descending order of score,.

tensorflow::ops::NotEqual

Returns the truth value of (x != y) element-wise.

tensorflow::ops::NthElement

Finds values of the n-th order statistic for the last dimension.

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::OrderedMapClear

Op removes all elements in the underlying container.

tensorflow::ops::OrderedMapIncompleteSize

Op returns the number of incomplete elements in the underlying container.

tensorflow::ops::OrderedMapPeek

Op peeks at the values at the specified key.

tensorflow::ops::OrderedMapSize

Op returns the number of elements in the underlying container.

tensorflow::ops::OrderedMapStage

Stage (key, values) in the underlying container which behaves like a ordered.

tensorflow::ops::OrderedMapUnstage

Op removes and returns the values associated with the key.

tensorflow::ops::OrderedMapUnstageNoKey

Op removes and returns the (key, value) element with the smallest.

tensorflow::ops::Pad

Pads a tensor with zeros.

tensorflow::ops::PadV2

Pads a tensor.

tensorflow::ops::PaddingFIFOQueue

A queue that produces elements in first-in first-out order.

tensorflow::ops::ParallelConcat

Concatenates a list of N tensors along the first dimension.

tensorflow::ops::ParallelDynamicStitch

Interleave the values from the data tensors into a single tensor.

tensorflow::ops::ParameterizedTruncatedNormal

Outputs random values from a normal distribution.

tensorflow::ops::ParseExample

Transforms a vector of brain.Example protos (as strings) into typed tensors.

tensorflow::ops::ParseSingleExample

Transforms a tf.Example proto (as a string) 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::Placeholder

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::Polygamma

Compute the polygamma function \(^{(n)}(x)\).

tensorflow::ops::Pow

Computes the power of one value to another.

tensorflow::ops::PreventGradient

An identity op that triggers an error if a gradient is requested.

tensorflow::ops::Print

Prints a list of tensors.

tensorflow::ops::PriorityQueue

A queue that produces elements sorted by the first component value.

tensorflow::ops::Prod

Computes the product of elements across dimensions of a tensor.

tensorflow::ops::QuantizeAndDequantizeV2

Quantizes then dequantizes a tensor.

tensorflow::ops::QuantizeAndDequantizeV3

Quantizes then dequantizes a tensor.

tensorflow::ops::QuantizeDownAndShrinkRange

Convert the quantized 'input' tensor into a lower-precision 'output', using the.

tensorflow::ops::QuantizeV2

Quantize the 'input' tensor of type float to 'output' tensor of type 'T'.

tensorflow::ops::QuantizedAdd

Returns x + y element-wise, working on quantized buffers.

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::QuantizedConcat

Concatenates quantized tensors along one dimension.

tensorflow::ops::QuantizedConv2D

Computes a 2D convolution given quantized 4D input and filter tensors.

tensorflow::ops::QuantizedInstanceNorm

Quantized Instance normalization.

tensorflow::ops::QuantizedMatMul

Perform a quantized matrix multiplication of a by the matrix b.

tensorflow::ops::QuantizedMaxPool

Produces the max pool of the input tensor for quantized types.

tensorflow::ops::QuantizedMul

Returns x * y element-wise, working on quantized buffers.

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::QuantizedReshape

Reshapes a quantized tensor as per the Reshape op.

tensorflow::ops::QuantizedResizeBilinear

Resize quantized images to size using quantized bilinear interpolation.

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::QueueIsClosed

Returns true if queue is closed.

tensorflow::ops::QueueIsClosedV2

Returns true if queue is closed.

tensorflow::ops::QueueSize

Computes the number of elements in the given queue.

tensorflow::ops::RGBToHSV

Converts one or more images from RGB to HSV.

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::RandomPoissonV2

Outputs random values from the Poisson distribution(s) described by rate.

tensorflow::ops::RandomShuffle

Randomly shuffles a tensor along its first dimension.

tensorflow::ops::RandomShuffleQueue

A queue that randomizes the order of elements.

tensorflow::ops::RandomUniform

Outputs random values from a uniform distribution.

tensorflow::ops::RandomUniformInt

Outputs random integers from a uniform distribution.

tensorflow::ops::Range

Creates a sequence of numbers.

tensorflow::ops::Rank

Returns the rank of a tensor.

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::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::RecordInput

Emits randomized records.

tensorflow::ops::ReduceJoin

Joins a string Tensor across the given dimensions.

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::Relu

Computes rectified linear: max(features, 0).

tensorflow::ops::Relu6

Computes rectified linear 6: min(max(features, 0), 6).

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::Reshape

Reshapes a tensor.

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::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::ResourceApplyAddSign

Update '*var' according to the AddSign update.

tensorflow::ops::ResourceApplyCenteredRMSProp

Update '*var' according to the centered RMSProp algorithm.

tensorflow::ops::ResourceApplyFtrl

Update '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ResourceApplyFtrlV2

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::ResourceApplyPowerSign

Update '*var' according to the AddSign update.

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::ResourceCountUpTo

Increments variable pointed to by 'resource' until it reaches 'limit'.

tensorflow::ops::ResourceScatterNdUpdate

Applies sparse updates to individual values or slices within a given.

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::ResourceSparseApplyFtrlV2

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::ResourceStridedSliceAssign

Assignvalue to the sliced l-value reference of ref.

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::Reverse

Reverses specific dimensions of a tensor.

tensorflow::ops::ReverseSequence

Reverses variable length slices.

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::SampleDistortedBoundingBox

Generate a single randomly distorted bounding box for an image.

tensorflow::ops::SampleDistortedBoundingBoxV2

Generate a single randomly distorted bounding box for an image.

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::ScalarSummary

Outputs a Summary protocol buffer with scalar values.

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::ScatterNd

Scatter updates into a new (initially zero) tensor according to indices.

tensorflow::ops::ScatterNdAdd

Applies sparse addition between updates and individual values or slices.

tensorflow::ops::ScatterNdNonAliasingAdd

Applies sparse addition to input using 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::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::Selu

Computes scaled exponential linear: scale * alpha * (exp(features) - 1)

tensorflow::ops::SerializeManySparse

Serialize an N-minibatch SparseTensor into an [N, 3]Tensor object.

tensorflow::ops::SerializeSparse

Serialize a SparseTensor into a [3]Tensor object.

tensorflow::ops::SerializeTensor

Transforms a Tensor into a serialized TensorProto proto.

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::ShardedFilename

Generate a sharded filename.

tensorflow::ops::ShardedFilespec

Generate a glob pattern matching all sharded file names.

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::Sinh

Computes hyperbolic sine of x element-wise.

tensorflow::ops::Size

Returns the size of a tensor.

tensorflow::ops::Slice

Return a slice from 'input'.

tensorflow::ops::Snapshot

Returns a copy of the input tensor.

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::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::SparseAccumulatorApplyGradient

Applies a sparse gradient to a given accumulator.

tensorflow::ops::SparseAccumulatorTakeGradient

Extracts the average sparse gradient in a SparseConditionalAccumulator.

tensorflow::ops::SparseAdd

Adds two SparseTensor objects to produce another SparseTensor.

tensorflow::ops::SparseAddGrad

The gradient operator for the SparseAdd op.

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::SparseApplyFtrlV2

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.

tensorflow::ops::SparseConcat

Concatenates a list of SparseTensor along the specified dimension.

tensorflow::ops::SparseConditionalAccumulator

A conditional accumulator for aggregating sparse gradients.

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::SparseFillEmptyRows

Fills empty rows in the input 2-D SparseTensor with a default value.

tensorflow::ops::SparseFillEmptyRowsGrad

The gradient of SparseFillEmptyRows.

tensorflow::ops::SparseMatMul

Multiply matrix "a" by matrix "b".

tensorflow::ops::SparseReduceMax

Computes the max of elements across dimensions of a SparseTensor.

tensorflow::ops::SparseReduceMaxSparse

Computes the max of elements across dimensions of a SparseTensor.

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::SparseSegmentMean

Computes the mean along sparse segments of a tensor.

tensorflow::ops::SparseSegmentMeanGrad

Computes gradients for SparseSegmentMean.

tensorflow::ops::SparseSegmentMeanWithNumSegments

Computes the mean along sparse segments of a tensor.

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::SparseSegmentSqrtNWithNumSegments

Computes the sum along sparse segments of a tensor divided by the sqrt of N.

tensorflow::ops::SparseSegmentSum

Computes the sum along sparse segments of a tensor.

tensorflow::ops::SparseSegmentSumWithNumSegments

Computes the sum along sparse segments of a tensor.

tensorflow::ops::SparseSlice

Slice a SparseTensor based on the start and size.

tensorflow::ops::SparseSoftmax

Applies softmax to a batched N-D SparseTensor.

tensorflow::ops::SparseSoftmaxCrossEntropyWithLogits

Computes softmax cross entropy cost and gradients to backpropagate.

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::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::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::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::Stage

Stage values similar to a lightweight Enqueue.

tensorflow::ops::StageClear

Op removes all elements in the underlying container.

tensorflow::ops::StagePeek

Op peeks at the values at the specified index.

tensorflow::ops::StageSize

Op returns the number of elements in the underlying container.

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::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::StringToNumber

Converts each string in the input Tensor to the specified numeric type.

tensorflow::ops::Substr

Return substrings from Tensor of strings.

tensorflow::ops::Subtract

Returns x - y element-wise.

tensorflow::ops::Sum

Computes the sum of elements across dimensions of a tensor.

tensorflow::ops::Switch

Forwards data to the output port determined by pred.

tensorflow::ops::TFRecordReader

A Reader that outputs the records from a TensorFlow Records file.

tensorflow::ops::TakeManySparseFromTensorsMap

Read SparseTensors from a SparseTensorsMap and concatenate them.

tensorflow::ops::Tan

Computes tan of x element-wise.

tensorflow::ops::Tanh

Computes hyperbolic tangent of x element-wise.

tensorflow::ops::TemporaryVariable

Returns a tensor that may be mutated, but only persists within a single step.

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::TensorSummary

Outputs a Summary protocol buffer with a tensor.

tensorflow::ops::TensorSummaryV2

Outputs a Summary protocol buffer with a tensor and per-plugin data.

tensorflow::ops::TextLineReader

A Reader that outputs the lines of a file delimited by '
'.

tensorflow::ops::Tile

Constructs a tensor by tiling a given tensor.

tensorflow::ops::TopK

Finds values and indices of the k largest elements for the last dimension.

tensorflow::ops::Transpose

Shuffle dimensions of x according to a permutation.

tensorflow::ops::TruncateDiv

Returns x / y element-wise for integer types.

tensorflow::ops::TruncateMod

Returns element-wise remainder of division.

tensorflow::ops::TruncatedNormal

Outputs random values from a truncated normal distribution.

tensorflow::ops::UniformCandidateSampler

Generates labels for candidate sampling with a uniform distribution.

tensorflow::ops::Unique

Finds unique elements in a 1-D tensor.

tensorflow::ops::UniqueV2

Finds unique elements along an axis of a tensor.

tensorflow::ops::UniqueWithCounts

Finds unique elements in a 1-D tensor.

tensorflow::ops::UnravelIndex

Converts a flat index or array of flat indices into a tuple of.

tensorflow::ops::UnsortedSegmentMax

Computes the Max along segments of a tensor.

tensorflow::ops::UnsortedSegmentSum

Computes the sum along segments of a tensor.

tensorflow::ops::Unstack

Unpacks a given dimension of a rank-R tensor into num rank-(R-1) tensors.

tensorflow::ops::Unstage

Op is similar to a lightweight Dequeue.

tensorflow::ops::Variable

Holds state in the form of a tensor that persists across steps.

tensorflow::ops::Where

Returns locations of nonzero / true values in a tensor.

tensorflow::ops::Where3

Selects elements from x or y, depending on condition.

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.

tensorflow::ops::ZerosLike

Returns a tensor of zeros with the same shape and type as x.

tensorflow::ops::Zeta

Compute the Hurwitz zeta function \((x, q)\).

Typedefs

Mul

Multiply Mul

Neg

Negate Neg

ReduceAll

All ReduceAll

ReduceAny

Any ReduceAny

ReduceMax

Max ReduceMax

ReduceMean

Mean ReduceMean

ReduceMin

Min ReduceMin

ReduceProd

Prod ReduceProd

ReduceSum

Sum ReduceSum

Sub

Subtract Sub

Functions

AsNodeOut

NodeBuilder::NodeOut AsNodeOut(
  const Scope & scope,
  const Input & inp
)

AsNodeOutList

std::vector< NodeBuilder::NodeOut > AsNodeOutList(
  const Scope & scope,
  const InputList & inp
)

AudioSummary

 AudioSummary(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input tag,
  ::tensorflow::Input tensor,
  ::tensorflow::Input sample_rate
)

AudioSummary

 AudioSummary(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input tag,
  ::tensorflow::Input tensor,
  ::tensorflow::Input sample_rate,
  const AudioSummary::Attrs & attrs
)

BadColor

Attrs BadColor(
  const TensorProto & x
)

Color to use for pixels with non-finite values.

Defaults to Tensor

Const

Output Const(
  const Scope & scope,
  const Input::Initializer & val
)

Const

Output Const(
  const Scope & scope,
  const T & v,
  const TensorShape shape
)

Const

Output Const(
  const Scope & scope,
  const std::initializer_list< T > & v,
  const TensorShape shape
)

ConstFromProto

Output ConstFromProto(
  const Scope & scope,
  const TensorProto & proto
)

ImageSummary

 ImageSummary(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input tag,
  ::tensorflow::Input tensor
)

ImageSummary

 ImageSummary(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input tag,
  ::tensorflow::Input tensor,
  const ImageSummary::Attrs & attrs
)

MaxImages

Attrs MaxImages(
  int64 x
)

MaxOutputs

Attrs MaxOutputs(
  int64 x
)

node

::tensorflow::Node * node() const 

range

image **If max_images is greater the summary value tags are *generated sequentially as *tag *tag etc **The bad_color argument is the color to use in the generated images for *non finite input values It is a unit8 D tensor of length channels *Each element must be in the range(
  It represents the value of a *pixel in the output image
).Non-finite values in the input tensor are *replaced by this tensor in the output image.The default value is the color *red.**Arguments

Max number of batch elements to generate images for.

Defaults to 3