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tensorflow::ops::Conv::Attrs

#include <nn_ops.h>

Optional attribute setters for Conv.

Summary

Public attributes
`batch_dims_ = 1`	`int64`
`data_format_ = "CHANNELS_LAST"`	`StringPiece`
`dilations_ = {}`	`gtl::ArraySlice< int >`
`explicit_paddings_ = {}`	`gtl::ArraySlice< int >`
`groups_ = 1`	`int64`

Public functions
`BatchDims(int64 x)`	`TF_MUST_USE_RESULT Attrs` A positive integer specifying the number of batch dimensions for the input tensor.
`DataFormat(StringPiece x)`	`TF_MUST_USE_RESULT Attrs` Used to set the data format.
`Dilations(const gtl::ArraySlice< int > & x)`	`TF_MUST_USE_RESULT Attrs` 1-D tensor of length `N+2`.
`ExplicitPaddings(const gtl::ArraySlice< int > & x)`	`TF_MUST_USE_RESULT Attrs` If `padding` is `"EXPLICIT"`, the list of explicit padding amounts.
`Groups(int64 x)`	`TF_MUST_USE_RESULT Attrs` A positive integer specifying the number of groups in which the input is split along the channel axis.

Public attributes

batch_dims_

int64 tensorflow::ops::Conv::Attrs::batch_dims_ = 1

data_format_

StringPiece tensorflow::ops::Conv::Attrs::data_format_ = "CHANNELS_LAST"

dilations_

gtl::ArraySlice< int > tensorflow::ops::Conv::Attrs::dilations_ = {}

explicit_paddings_

gtl::ArraySlice< int > tensorflow::ops::Conv::Attrs::explicit_paddings_ = {}

groups_

int64 tensorflow::ops::Conv::Attrs::groups_ = 1

Public functions

BatchDims

TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::BatchDims(
  int64 x
)

A positive integer specifying the number of batch dimensions for the input tensor.

Should be less than the rank of the input tensor.

Defaults to 1

DataFormat

TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::DataFormat(
  StringPiece x
)

Used to set the data format.

By default CHANNELS_FIRST, uses NHWC (2D) / NDHWC (3D) or if CHANNELS_LAST, uses NCHW (2D) / NCDHW (3D).

Defaults to "CHANNELS_LAST"

Dilations

TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::Dilations(
  const gtl::ArraySlice< int > & x
)

1-D tensor of length N+2.

The dilation factor for each dimension of input. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of channels_last_format, see above for details. Dilations in the batch and depth dimensions must be 1.

Defaults to []

ExplicitPaddings

TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::ExplicitPaddings(
  const gtl::ArraySlice< int > & x
)

If padding is "EXPLICIT", the list of explicit padding amounts.

For the ith dimension, the amount of padding inserted before and after the dimension is explicit_paddings[2 * i] and explicit_paddings[2 * i + 1], respectively. If padding is not "EXPLICIT", explicit_paddings must be empty.

Defaults to []

Groups

TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::Groups(
  int64 x
)

A positive integer specifying the number of groups in which the input is split along the channel axis.

Each group is convolved separately with filters / groups filters. The output is the concatenation of all the groups results along the channel axis. Input channels and filters must both be divisible by groups.

Defaults to 1

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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/cc/struct/tensorflow/ops/conv/attrs