tensorflow::ops::Conv3DBackpropInputV2

#include <nn_ops.h>

Computes the gradients of 3-D convolution with respect to the input.

Summary

Arguments:

• scope: A Scope object
• input_sizes: An integer vector representing the tensor shape of input, where input is a 5-D [batch, depth, rows, cols, in_channels] tensor.
• filter: Shape[depth, rows, cols, in_channels, out_channels]. in_channels must match between input and filter.
• out_backprop: Backprop signal of shape [batch, out_depth, out_rows, out_cols, out_channels].
• strides: 1-D tensor of length 5. The stride of the sliding window for each dimension of input. Must have strides[0] = strides[4] = 1.
• padding: The type of padding algorithm to use.

Optional attributes (see Attrs):

• data_format: 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].

Returns:

• Output: The output tensor.

Public attributes

::tensorflow::Output output

Public functions

 Conv3DBackpropInputV2(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input_sizes,
  ::tensorflow::Input filter,
  ::tensorflow::Input out_backprop,
  const gtl::ArraySlice< int > & strides,
  StringPiece padding
)

 Conv3DBackpropInputV2(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input_sizes,
  ::tensorflow::Input filter,
  ::tensorflow::Input out_backprop,
  const gtl::ArraySlice< int > & strides,
  StringPiece padding,
  const Conv3DBackpropInputV2::Attrs & attrs
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs DataFormat(
  StringPiece x
)