multiply_merge.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_MULTIPLY_MERGE_HPP
#define MLPACK_METHODS_ANN_LAYER_MULTIPLY_MERGE_HPP

#include <mlpack/prereqs.hpp>

#include "../visitor/delete_visitor.hpp"
#include "../visitor/delta_visitor.hpp"
#include "../visitor/output_parameter_visitor.hpp"

#include "layer_types.hpp"

namespace mlpack {
namespace ann  {

template<
    typename InputDataType = arma::mat,
    typename OutputDataType = arma::mat,
    typename... CustomLayers
>
class MultiplyMerge
{
 public:
  MultiplyMerge(const bool model = false, const bool run = true);

  MultiplyMerge(const MultiplyMerge& layer);

  MultiplyMerge(MultiplyMerge&& layer);

  MultiplyMerge& operator=(const MultiplyMerge& layer);

  MultiplyMerge& operator=(MultiplyMerge&& layer);

  ~MultiplyMerge();

  template<typename InputType, typename OutputType>
  void Forward(const InputType& /* input */, OutputType& output);

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

  /*
   * Calculate the gradient using the output delta and the input activation.
   *
   * @param input The input parameter used for calculating the gradient.
   * @param error The calculated error.
   * @param gradient The calculated gradient.
   */
  template<typename eT>
  void Gradient(const arma::Mat<eT>& input,
                const arma::Mat<eT>& error,
                arma::Mat<eT>& gradient);

  /*
   * Add a new module to the model.
   *
   * @param args The layer parameter.
   */
  template <class LayerType, class... Args>
  void Add(Args... args) { network.push_back(new LayerType(args...)); }

  /*
   * Add a new module to the model.
   *
   * @param layer The Layer to be added to the model.
   */
  void Add(LayerTypes<CustomLayers...> layer) { network.push_back(layer); }

  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; }

  std::vector<LayerTypes<CustomLayers...> >& Model()
  {
    if (model)
    {
      return network;
    }

    return empty;
  }

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

  size_t WeightSize() const { return 0; }

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

 private:
  bool model;

  bool run;

  bool ownsLayer;

  std::vector<LayerTypes<CustomLayers...> > network;

  std::vector<LayerTypes<CustomLayers...> > empty;

  DeleteVisitor deleteVisitor;

  OutputParameterVisitor outputParameterVisitor;

  DeltaVisitor deltaVisitor;

  OutputDataType delta;

  OutputDataType gradient;

  OutputDataType outputParameter;

  OutputDataType weights;
}; // class MultiplyMerge

} // namespace ann
} // namespace mlpack

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

#endif