dropconnect.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_DROPCONNECT_HPP
#define MLPACK_METHODS_ANN_LAYER_DROPCONNECT_HPP

#include <mlpack/prereqs.hpp>

#include "layer_types.hpp"
#include "add_merge.hpp"
#include "linear.hpp"
#include "sequential.hpp"

namespace mlpack {
namespace ann  {

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

  DropConnect(const size_t inSize,
              const size_t outSize,
              const double ratio = 0.5);

  ~DropConnect();

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

  template<typename eT>
  void Backward(arma::Mat<eT>&& input,
                arma::Mat<eT>&& gy,
                arma::Mat<eT>&& g);

  template<typename eT>
  void Gradient(arma::Mat<eT>&& input,
                arma::Mat<eT>&& error,
                arma::Mat<eT>&& /* gradient */);

  std::vector<LayerTypes>& Model() { return network; }

  OutputDataType const& Parameters() const { return parameters; }
  OutputDataType& Parameters() { return parameters; }

  InputDataType const& InputParameter() const { return inputParameter; }
  InputDataType& InputParameter() { return inputParameter; }

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

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

  OutputDataType const& Gradient() const { return gradient; }
  OutputDataType& Gradient() { return gradient; }

  bool Deterministic() const { return deterministic; }

  bool &Deterministic() { return deterministic; }

  double Ratio() const { return ratio; }

  void Ratio(const double r)
  {
    ratio = r;
    scale = 1.0 / (1.0 - ratio);
  }

  template<typename Archive>
  void Serialize(Archive& ar, const unsigned int /* version */);

private:
  double ratio;

  double scale;

  OutputDataType parameters;

  OutputDataType delta;

  OutputDataType gradient;

  InputDataType inputParameter;

  OutputDataType outputParameter;

  OutputDataType mask;

  bool deterministic;

  OutputDataType denoise;

  LayerTypes baseLayer;

  std::vector<LayerTypes> network;
}; // class DropConnect.

}  // namespace ann
}  // namespace mlpack

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

#endif