Stay organized with collections Save and categorize content based on your preferences.

# tensorflow::ops

## Summary

### Typedefs

Mul typedef
Neg typedef
ReduceAll typedef
ReduceAny typedef
ReduceMax typedef
ReduceMean typedef
ReduceMin typedef
ReduceProd typedef
ReduceSum typedef
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)
TF_MUST_USE_RESULT 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 uint8 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.

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.

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.

Returns x + y element-wise.

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

Add all input tensors element wise.

Add a SparseTensor to a SparseTensorsMap return its handle.

Returns x + y element-wise.

Adjust the contrast of one or more images.

Adjust the hue of one or more images.

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.

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::ApplyFtrlV2

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

Update '*var' by subtracting 'alpha' * 'delta' from it.

tensorflow::ops::ApplyMomentum

Update '*var' according to the momentum scheme.

tensorflow::ops::ApplyPowerSign

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 the trignometric inverse sine 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.

Update 'ref' by adding 'value' to it.

tensorflow::ops::AssignSub

Update 'ref' by subtracting 'value' from it.

tensorflow::ops::Atan

Computes the trignometric inverse tangent 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.

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.

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::BatchMatMulV2

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 $$I_x(a, b)$$.

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.

Return the shape of s0 op s1 with broadcast.

Broadcast an array for a compatible shape.

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 not less than x.

tensorflow::ops::CheckNumerics

Checks a tensor for NaN and Inf values.

tensorflow::ops::ClipByValue

Clips tensor values to a specified min and max.

tensorflow::ops::CombinedNonMaxSuppression

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

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 resizes them.

Computes the gradient of the crop_and_resize op wrt the input boxes tensor.

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::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 frame(s) 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.

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

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::DeepCopy

Makes a copy of x.

tensorflow::ops::DeleteSessionTensor

Delete the tensor specified by its handle in the session.

tensorflow::ops::DenseBincount

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

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 or bfloat16 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::DivNoNan

Returns 0 if the denominator is zero.

tensorflow::ops::DrawBoundingBoxes

Draw bounding boxes on a batch of images.

tensorflow::ops::DrawBoundingBoxesV2

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::Empty

Creates a tensor with the given shape.

tensorflow::ops::EncodeBase64

Encode strings into web-safe base64 format.

tensorflow::ops::EncodeJpeg

JPEG-encode an image.

tensorflow::ops::EncodeJpegVariableQuality

JPEG encode input image with provided compression quality.

tensorflow::ops::EncodePng

PNG-encode an image.

tensorflow::ops::EnsureShape

Ensures that the tensor's shape matches the expected shape.

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::Erfinv

tensorflow::ops::EuclideanNorm

Computes the euclidean norm of elements across dimensions of a tensor.

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 exp(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::ExtractVolumePatches

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

tensorflow::ops::FIFOQueue

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

tensorflow::ops::Fact

tensorflow::ops::FakeQuantWithMinMaxArgs

Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type.

Compute gradients for a FakeQuantWithMinMaxArgs operation.

tensorflow::ops::FakeQuantWithMinMaxVars

Fake-quantize the 'inputs' tensor of type float via global float scalars.

Compute gradients for a FakeQuantWithMinMaxVars operation.

tensorflow::ops::FakeQuantWithMinMaxVarsPerChannel

Fake-quantize the 'inputs' tensor of type float via per-channel floats.

Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.

tensorflow::ops::Fill

Creates a tensor filled with a scalar value.

tensorflow::ops::Fingerprint

Generates fingerprint values.

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::FusedBatchNormV2

Batch normalization.

tensorflow::ops::FusedBatchNormV3

Batch normalization.

Performs a padding as a preprocess during a convolution.

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.

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

tensorflow::ops::Igamma

Compute the lower regularized incomplete Gamma function P(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.

Adds v into specified rows of x.

tensorflow::ops::InplaceSub

Subtracts v into specified rows of x.

tensorflow::ops::InplaceUpdate

Updates specified rows 'i' with values 'v'.

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.

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::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 to zero.

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::MatrixDiagPartV2

Returns the batched diagonal part of a batched tensor.

tensorflow::ops::MatrixDiagPartV3

Returns the batched diagonal part of a batched tensor.

tensorflow::ops::MatrixDiagV2

Returns a batched diagonal tensor with given batched diagonal values.

tensorflow::ops::MatrixDiagV3

Returns a batched diagonal tensor with given batched diagonal values.

tensorflow::ops::MatrixSetDiag

Returns a batched matrix tensor with new batched diagonal values.

tensorflow::ops::MatrixSetDiagV2

Returns a batched matrix tensor with new batched diagonal values.

tensorflow::ops::MatrixSetDiagV3

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.

Computes gradients of 3D max pooling function.

Computes second-order gradients of the maxpooling function.

Computes second-order gradients of the maxpooling function.

Computes second-order gradients of the maxpooling function.

Computes second-order gradients of the maxpooling function.

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.

Pads a tensor with mirrored values.

tensorflow::ops::Mod

Returns element-wise remainder of division.

tensorflow::ops::MulNoNan

Returns x * y element-wise.

tensorflow::ops::Multinomial

Draws samples from a multinomial distribution.

tensorflow::ops::Multiply

Returns x * y element-wise.

tensorflow::ops::Ndtri

tensorflow::ops::Negate

Computes numerical negative value element-wise.

tensorflow::ops::NextAfter

Returns the next representable value of x1 in the direction of x2, 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::NonMaxSuppressionV3

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

tensorflow::ops::NonMaxSuppressionV4

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

tensorflow::ops::NonMaxSuppressionV5

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

tensorflow::ops::NonMaxSuppressionWithOverlaps

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.

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::ParseExampleV2

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

tensorflow::ops::ParseSequenceExample

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

tensorflow::ops::ParseSequenceExampleV2

Transforms a vector of tf.io.SequenceExample 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.

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

tensorflow::ops::Print

Prints a list of tensors.

tensorflow::ops::PrintV2

Prints a string scalar.

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'.

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.

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::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::RaggedBincount

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

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.

Reads and outputs the entire contents of the input filename.

Returns the number of records this Reader has produced.

Returns the number of work units this Reader has finished processing.

Returns the next record (key, value pair) produced by a Reader.

Returns up to num_records (key, value) pairs produced by a Reader.

Restore a Reader to its initial clean state.

Restore a reader to a previously saved state.

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::RegexFullMatch

Check if the input matches the regex pattern.

tensorflow::ops::RegexReplace

Replaces matches of the pattern regular expression in input with the replacement string provided in rewrite.

tensorflow::ops::Relu

Computes rectified linear: max(features, 0).

tensorflow::ops::Relu6

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

tensorflow::ops::RequantizationRange

Computes a range that covers the actual values present in a quantized tensor.

tensorflow::ops::Requantize

Converts the quantized input tensor into a lower-precision output.

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.

Update '*var' according to the Adam algorithm.

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::ResourceApplyFtrlV2

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

Update '*var' by subtracting 'alpha' * 'delta' from it.

tensorflow::ops::ResourceApplyKerasMomentum

Update '*var' according to the momentum scheme.

tensorflow::ops::ResourceApplyMomentum

Update '*var' according to the momentum scheme.

tensorflow::ops::ResourceApplyPowerSign

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'.

Applies sparse addition to individual values or slices in a Variable.

tensorflow::ops::ResourceScatterNdMax

tensorflow::ops::ResourceScatterNdMin

tensorflow::ops::ResourceScatterNdSub

Applies sparse subtraction to individual values or slices in a Variable.

tensorflow::ops::ResourceScatterNdUpdate

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

var: Should be from a Variable().

Update relevant entries in '*var' and '*accum' according to the adagrad scheme.

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::ResourceSparseApplyKerasMomentum

Update relevant entries in '*var' and '*accum' according to the momentum scheme.

tensorflow::ops::ResourceSparseApplyMomentum

Update relevant entries in '*var' and '*accum' according to the momentum scheme.

Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.

Sparse update '*var' as FOBOS algorithm with fixed learning rate.

tensorflow::ops::ResourceSparseApplyRMSProp

Update '*var' according to the RMSProp algorithm.

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::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::ScaleAndTranslate

tensorflow::ops::ScatterDiv

Divides a variable reference by sparse updates.

tensorflow::ops::ScatterMax

Reduces sparse updates into a variable reference using the max operation.

tensorflow::ops::ScatterMin

Reduces sparse updates into a variable reference using the min operation.

tensorflow::ops::ScatterMul

Multiplies sparse updates into a variable reference.

Applies sparse addition to individual values or slices in a Variable.

tensorflow::ops::ScatterNdSub

Applies sparse subtraction to individual values or slices in a Variable.

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::SelectV2

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::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 sine of x element-wise.

tensorflow::ops::Sinh

Computes hyperbolic sine of x element-wise.

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).

Applies a sparse gradient to a given accumulator.

Extracts the average sparse gradient in a SparseConditionalAccumulator.

Adds two SparseTensor objects to produce another SparseTensor.

var: Should be from a Variable().

Update relevant entries in '*var' and '*accum' according to the adagrad scheme.

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.

Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.

Sparse update '*var' as FOBOS algorithm with fixed learning rate.

tensorflow::ops::SparseApplyRMSProp

Update '*var' according to the RMSProp algorithm.

tensorflow::ops::SparseBincount

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

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::SparseCrossHashed

Generates sparse cross from a list of sparse and dense tensors.

tensorflow::ops::SparseCrossV2

Generates sparse cross from a list of sparse and dense tensors.

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::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::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::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.

The gradient operator for the SparseSlice op.

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.

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::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::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::StringFormat

Formats a string template using a list of tensors.

tensorflow::ops::StringJoin

Joins the strings in the given list of string tensors into one tensor;.

tensorflow::ops::StringLength

String lengths of input.

tensorflow::ops::StringLower

Converts all uppercase characters into their respective lowercase replacements.

tensorflow::ops::StringNGrams

Creates ngrams from ragged string data.

tensorflow::ops::StringSplit

Split elements of input based on delimiter into a SparseTensor.

tensorflow::ops::StringSplitV2

Split elements of source based on sep into a SparseTensor.

tensorflow::ops::StringStrip

Strip leading and trailing whitespaces from the Tensor.

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::StringUpper

Converts all lowercase characters into their respective uppercase replacements.

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.

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

tensorflow::ops::TakeManySparseFromTensorsMap

Converts a sparse representation into a dense tensor.

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.

Creates a TensorArray for storing the gradients of values in the given handle.

Creates a TensorArray for storing multiple gradients of values in the given handle.

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.

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

tensorflow::ops::Timestamp

Provides the time since epoch in seconds.

tensorflow::ops::TopK

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

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::UnicodeScript

Determine the script codes of a given tensor of Unicode integer code points.

tensorflow::ops::UnicodeTranscode

Transcode the input text from a source encoding to a destination encoding.

tensorflow::ops::UniformCandidateSampler

Generates labels for candidate sampling with a uniform distribution.

tensorflow::ops::UnsortedSegmentJoin

Joins the elements of inputs based on segment_ids.

tensorflow::ops::UnsortedSegmentMax

Computes the maximum along segments of a tensor.

tensorflow::ops::UnsortedSegmentMin

Computes the minimum along segments of a tensor.

tensorflow::ops::UnsortedSegmentProd

Computes the product along segments of a tensor.

tensorflow::ops::UnsortedSegmentSum

Computes the sum along segments of a tensor.

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

Reshapes a quantized tensor as per the Reshape op.

tensorflow::ops::Where3

Selects elements from x or y, depending on condition.

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::Xdivy

Returns 0 if x == 0, and x / y otherwise, elementwise.

tensorflow::ops::Xlog1py

Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise.

tensorflow::ops::Xlogy

Returns 0 if x == 0, and x * log(y) otherwise, elementwise.

tensorflow::ops::ZerosLike

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

tensorflow::ops::Zeta

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

Multiply Mul

Negate Neg

All ReduceAll

Any ReduceAny

Max ReduceMax

Mean ReduceMean

Min ReduceMin

Prod ReduceProd

Sum ReduceSum

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
)

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
)

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 uint8 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

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]