tensorflow:: ops:: Conv2DBackpropInputV2
#include <nn_ops.h>
Computes the gradients of convolution with respect to the input.
Summary
Args:
- scope: A Scope object
- input: 4-D with shape
[batch, in_height, in_width, in_channels]
. Only shape of tensor is used. - filter: 4-D with shape
[filter_height, filter_width, in_channels, out_channels]
. - out_backprop: 4-D with shape
[batch, out_height, out_width, out_channels]
. Gradients w.r.t. the output of the convolution. - strides: The stride of the sliding window for each dimension of the input of the convolution. Must be in the same order as the dimension specified with format.
- padding: The type of padding algorithm to use.
Optional attributes (see Attrs
):
- explicit_paddings: If
padding
is"EXPLICIT"
, the list of explicit padding amounts. For the ith dimension, the amount of padding inserted before and after the dimension isexplicit_paddings[2 * i]
andexplicit_paddings[2 * i + 1]
, respectively. Ifpadding
is not"EXPLICIT"
,explicit_paddings
must be empty. - data_format: Specify the data format of the input and output data. With the default format "NHWC", the data is stored in the order of: [batch, in_height, in_width, in_channels]. Alternatively, the format could be "NCHW", the data storage order of: [batch, in_channels, in_height, in_width].
- dilations: 1-D tensor of length 4. 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 ofdata_format
, see above for details. Dilations in the batch and depth dimensions must be 1.
Returns:
Output
: 4-D with shape[batch, in_height, in_width, in_channels]
. Gradient w.r.t. the input of the convolution.
Constructors and Destructors |
|
---|---|
Conv2DBackpropInputV2(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding)
|
|
Conv2DBackpropInputV2(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding, const Conv2DBackpropInputV2::Attrs & attrs)
|
Public attributes |
|
---|---|
operation
|
|
output
|
Public functions |
|
---|---|
node() const
|
::tensorflow::Node *
|
operator::tensorflow::Input() const
|
|
operator::tensorflow::Output() const
|
|
Public static functions |
|
---|---|
DataFormat(StringPiece x)
|
|
Dilations(const gtl::ArraySlice< int > & x)
|
|
ExplicitPaddings(const gtl::ArraySlice< int > & x)
|
|
UseCudnnOnGpu(bool x)
|
Structs |
|
---|---|
tensorflow:: |
Optional attribute setters for Conv2DBackpropInputV2. |
Public attributes
operation
Operation operation
output
::tensorflow::Output output
Public functions
Conv2DBackpropInputV2
Conv2DBackpropInputV2( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding )
Conv2DBackpropInputV2
Conv2DBackpropInputV2( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding, const Conv2DBackpropInputV2::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
DataFormat
Attrs DataFormat( StringPiece x )
Dilations
Attrs Dilations( const gtl::ArraySlice< int > & x )
ExplicitPaddings
Attrs ExplicitPaddings( const gtl::ArraySlice< int > & x )
UseCudnnOnGpu
Attrs UseCudnnOnGpu( bool x )