tensorflow::ops::Conv3DBackpropInputV2::Attrs

#include <nn_ops.h>

Optional attribute setters for Conv3DBackpropInputV2.

Summary

Public attributes
data_format_ = "NDHWC"	StringPiece
dilations_ = Default_dilations()	gtl::ArraySlice< int >

Public functions
DataFormat(StringPiece x)	TF_MUST_USE_RESULT Attrs The data format of the input and output data.
Dilations(const gtl::ArraySlice< int > & x)	TF_MUST_USE_RESULT Attrs 1-D tensor of length 5.

Public attributes

data_format_

StringPiece tensorflow::ops::Conv3DBackpropInputV2::Attrs::data_format_ = "NDHWC"

dilations_

gtl::ArraySlice< int > tensorflow::ops::Conv3DBackpropInputV2::Attrs::dilations_ = Default_dilations()

Public functions

DataFormat

TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv3DBackpropInputV2::Attrs::DataFormat(
  StringPiece x
)

The data format of the input and output data.

With the default format "NDHWC", the data is stored in the order of: [batch, in_depth, in_height, in_width, in_channels]. Alternatively, the format could be "NCDHW", the data storage order is: [batch, in_channels, in_depth, in_height, in_width].

Defaults to "NDHWC"

Dilations

TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv3DBackpropInputV2::Attrs::Dilations(
  const gtl::ArraySlice< int > & x
)

1-D tensor of length 5.

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 data_format, see above for details. Dilations in the batch and depth dimensions must be 1.

Defaults to [1, 1, 1, 1, 1]