channel_shuffle.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_CHANNEL_SHUFFLE_HPP
#define MLPACK_METHODS_ANN_LAYER_CHANNEL_SHUFFLE_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack {
namespace ann  {

template <
    typename InputDataType = arma::mat,
    typename OutputDataType = arma::mat
>
class ChannelShuffle
{
 public:
  ChannelShuffle();

  ChannelShuffle(const size_t inRowSize,
                 const size_t inColSize,
                 const size_t depth,
                 const size_t groupCount);

  template<typename eT>
  void Forward(const arma::Mat<eT>& input, arma::Mat<eT>& output);

  template<typename eT>
  void Backward(const arma::Mat<eT>& /*input*/,
                const arma::Mat<eT>& gradient,
                arma::Mat<eT>& output);

  OutputDataType const& OutputParameter() const { return outputParameter; }
  OutputDataType& OutputParameter() { return outputParameter; }

  OutputDataType const& Delta() const { return delta; }
  OutputDataType& Delta() { return delta; }

  size_t const& InRowSize() const { return inRowSize; }
  size_t& InRowSize() { return inRowSize; }

  size_t const& InColSize() const { return inColSize; }
  size_t& InColSize() { return inColSize; }

  size_t const& InDepth() const { return depth; }
  size_t& InDepth() { return depth; }

  size_t const& InGroupCount() const { return groupCount; }
  size_t& InGroupCount() { return groupCount; }

  size_t InputShape() const
  {
    return inRowSize;
  }

  template<typename Archive>
  void serialize(Archive& ar, const uint32_t /* version */);

 private:
  size_t inRowSize;
  size_t inColSize;
  size_t depth;
  size_t groupCount;
  size_t batchSize;
  OutputDataType delta;
  OutputDataType outputParameter;
}; // class ChannelShuffle

} // namespace ann
} // namespace mlpack

// Include implementation.
#include "channel_shuffle_impl.hpp"

#endif