Definition and implementation of the Channel Shuffle Layer. More...
Public Member Functions | |
| ChannelShuffle () | |
| Create the Channel Shuffle object. More... | |
| ChannelShuffle (const size_t inRowSize, const size_t inColSize, const size_t depth, const size_t groupCount) | |
| The constructor for the Channel Shuffle. More... | |
template < typename eT > | |
| void | Backward (const arma::Mat< eT > &, const arma::Mat< eT > &gradient, arma::Mat< eT > &output) |
| Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through f. More... | |
| OutputDataType const & | Delta () const |
| Get the delta. More... | |
| OutputDataType & | Delta () |
| Modify the delta. More... | |
template < typename eT > | |
| void | Forward (const arma::Mat< eT > &input, arma::Mat< eT > &output) |
| Forward pass through the layer. More... | |
| size_t const & | InColSize () const |
| Get the column size of the input. More... | |
| size_t & | InColSize () |
| Modify the column size of the input. More... | |
| size_t const & | InDepth () const |
| Get the depth of the input. More... | |
| size_t & | InDepth () |
| Modify the depth of the input. More... | |
| size_t const & | InGroupCount () const |
| Get the number of groups the channels is divided into. More... | |
| size_t & | InGroupCount () |
| Modify the number of groups the channels is divided into. More... | |
| size_t | InputShape () const |
| Get the shape of the input. More... | |
| size_t const & | InRowSize () const |
| Get the row size of the input. More... | |
| size_t & | InRowSize () |
| Modify the row size of the input. More... | |
| OutputDataType const & | OutputParameter () const |
| Get the output parameter. More... | |
| OutputDataType & | OutputParameter () |
| Modify the output parameter. More... | |
template < typename Archive > | |
| void | serialize (Archive &ar, const uint32_t) |
| Serialize the layer. More... | |
Detailed Description
template<typenameInputDataType=arma::mat,typenameOutputDataType=arma::mat>
class mlpack::ann::ChannelShuffle< InputDataType, OutputDataType >
Definition and implementation of the Channel Shuffle Layer.
Channel Shuffle divides the channels/units in a tensor into groups and rearrange while keeping the original tensor shape.
For more information, refer to the following paper,
- Template Parameters
-
InputDataType Type of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube). OutputDataType Type of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
Definition at line 46 of file channel_shuffle.hpp.
Constructor & Destructor Documentation
◆ ChannelShuffle() [1/2]
| ChannelShuffle | ( | ) |
Create the Channel Shuffle object.
◆ ChannelShuffle() [2/2]
| ChannelShuffle | ( | const size_t | inRowSize, |
| const size_t | inColSize, | ||
| const size_t | depth, | ||
| const size_t | groupCount | ||
| ) |
The constructor for the Channel Shuffle.
- Parameters
-
inRowSize Number of input rows. inColSize Number of input columns. depth Number of input slices. group Number of groups for shuffling channels.
Member Function Documentation
◆ Backward()
| void Backward | ( | const arma::Mat< eT > & | , |
| const arma::Mat< eT > & | gradient, | ||
| arma::Mat< eT > & | output | ||
| ) |
Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through f.
Using the results from the feed forward pass. Since the layer does not have any learn-able parameters, we just have to down-sample the gradient to make its size compatible with the input size.
- Parameters
-
* (input) The input matrix. gradient The computed backward gradient. output The resulting down-sampled output.
◆ Delta() [1/2]
|
inline |
Get the delta.
Definition at line 96 of file channel_shuffle.hpp.
◆ Delta() [2/2]
|
inline |
Modify the delta.
Definition at line 98 of file channel_shuffle.hpp.
◆ Forward()
| void Forward | ( | const arma::Mat< eT > & | input, |
| arma::Mat< eT > & | output | ||
| ) |
Forward pass through the layer.
- Parameters
-
input The input matrix. output The resulting interpolated output matrix.
◆ InColSize() [1/2]
|
inline |
Get the column size of the input.
Definition at line 106 of file channel_shuffle.hpp.
◆ InColSize() [2/2]
|
inline |
Modify the column size of the input.
Definition at line 108 of file channel_shuffle.hpp.
◆ InDepth() [1/2]
|
inline |
Get the depth of the input.
Definition at line 111 of file channel_shuffle.hpp.
◆ InDepth() [2/2]
|
inline |
Modify the depth of the input.
Definition at line 113 of file channel_shuffle.hpp.
◆ InGroupCount() [1/2]
|
inline |
Get the number of groups the channels is divided into.
Definition at line 116 of file channel_shuffle.hpp.
◆ InGroupCount() [2/2]
|
inline |
Modify the number of groups the channels is divided into.
Definition at line 118 of file channel_shuffle.hpp.
◆ InputShape()
|
inline |
Get the shape of the input.
Definition at line 121 of file channel_shuffle.hpp.
References ChannelShuffle< InputDataType, OutputDataType >::serialize().
◆ InRowSize() [1/2]
|
inline |
Get the row size of the input.
Definition at line 101 of file channel_shuffle.hpp.
◆ InRowSize() [2/2]
|
inline |
Modify the row size of the input.
Definition at line 103 of file channel_shuffle.hpp.
◆ OutputParameter() [1/2]
|
inline |
Get the output parameter.
Definition at line 91 of file channel_shuffle.hpp.
◆ OutputParameter() [2/2]
|
inline |
Modify the output parameter.
Definition at line 93 of file channel_shuffle.hpp.
◆ serialize()
| void serialize | ( | Archive & | ar, |
| const uint32_t | |||
| ) |
Serialize the layer.
Referenced by ChannelShuffle< InputDataType, OutputDataType >::InputShape().
The documentation for this class was generated from the following file:
- /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/channel_shuffle.hpp