Array Ops

Summary

Classes
tensorflow::ops::BatchToSpace	BatchToSpace for 4-D tensors of type T.
tensorflow::ops::BatchToSpaceND	BatchToSpace for N-D tensors of type T.
tensorflow::ops::Bitcast	Bitcasts a tensor from one type to another without copying data.
tensorflow::ops::BroadcastDynamicShape	Return the shape of s0 op s1 with broadcast.
tensorflow::ops::BroadcastTo	Broadcast an array for a compatible shape.
tensorflow::ops::CheckNumerics	Checks a tensor for NaN and Inf values.
tensorflow::ops::Concat	Concatenates tensors along one dimension.
tensorflow::ops::ConjugateTranspose	Shuffle dimensions of x according to a permutation and conjugate the result.
tensorflow::ops::DebugGradientIdentity	Identity op for gradient debugging.
tensorflow::ops::DebugGradientRefIdentity	Identity op for gradient debugging.
tensorflow::ops::DeepCopy	Makes a copy of x.
tensorflow::ops::DepthToSpace	DepthToSpace for tensors of type T.
tensorflow::ops::Dequantize	Dequantize the 'input' tensor into a float or bfloat16 Tensor.
tensorflow::ops::Diag	Returns a diagonal tensor with a given diagonal values.
tensorflow::ops::DiagPart	Returns the diagonal part of the tensor.
tensorflow::ops::EditDistance	Computes the (possibly normalized) Levenshtein Edit Distance.
tensorflow::ops::Empty	Creates a tensor with the given shape.
tensorflow::ops::EnsureShape	Ensures that the tensor's shape matches the expected shape.
tensorflow::ops::ExpandDims	Inserts a dimension of 1 into a tensor's shape.
tensorflow::ops::ExtractImagePatches	Extract patches from images and put them in the "depth" output dimension.
tensorflow::ops::ExtractVolumePatches	Extract patches from input and put them in the "depth" output dimension.
tensorflow::ops::FakeQuantWithMinMaxArgs	Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type.
tensorflow::ops::FakeQuantWithMinMaxArgsGradient	Compute gradients for a FakeQuantWithMinMaxArgs operation.
tensorflow::ops::FakeQuantWithMinMaxVars	Fake-quantize the 'inputs' tensor of type float via global float scalars.
tensorflow::ops::FakeQuantWithMinMaxVarsGradient	Compute gradients for a FakeQuantWithMinMaxVars operation.
tensorflow::ops::FakeQuantWithMinMaxVarsPerChannel	Fake-quantize the 'inputs' tensor of type float via per-channel floats.
tensorflow::ops::FakeQuantWithMinMaxVarsPerChannelGradient	Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.
tensorflow::ops::Fill	Creates a tensor filled with a scalar value.
tensorflow::ops::Fingerprint	Generates fingerprint values.
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::GuaranteeConst	Gives a guarantee to the TF runtime that the input tensor is a constant.
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::ImmutableConst	Returns immutable tensor from memory region.
tensorflow::ops::InplaceAdd	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::InvertPermutation	Computes the inverse permutation of a tensor.
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::MirrorPad	Pads a tensor with mirrored values.
tensorflow::ops::OneHot	Returns a one-hot tensor.
tensorflow::ops::OnesLike	Returns a tensor of ones with the same shape and type as x.
tensorflow::ops::Pad	Pads a tensor with zeros.
tensorflow::ops::PadV2	Pads a tensor.
tensorflow::ops::ParallelConcat	Concatenates a list of N tensors along the first dimension.
tensorflow::ops::Placeholder	A placeholder op for a value that will be fed into the computation.
tensorflow::ops::PlaceholderWithDefault	A placeholder op that passes through input when its output is not fed.
tensorflow::ops::PreventGradient	An identity op that triggers an error if a gradient is requested.
tensorflow::ops::QuantizeAndDequantizeV2	Quantizes then dequantizes a tensor.
tensorflow::ops::QuantizeAndDequantizeV3	Quantizes then dequantizes a tensor.
tensorflow::ops::QuantizeV2	Quantize the 'input' tensor of type float to 'output' tensor of type 'T'.
tensorflow::ops::QuantizedConcat	Concatenates quantized tensors along one dimension.
tensorflow::ops::QuantizedInstanceNorm	Quantized Instance normalization.
tensorflow::ops::SetDiff1D	Computes the difference between two lists of numbers or strings.
tensorflow::ops::Stack	Packs a list of N rank-R tensors into one rank-(R+1) tensor.
tensorflow::ops::Where	Reshapes a quantized tensor as per the Reshape op.
tensorflow::ops::ZerosLike	Returns a tensor of zeros with the same shape and type as x.