sequential.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_SEQUENTIAL_HPP
#define MLPACK_METHODS_ANN_LAYER_SEQUENTIAL_HPP

#include <mlpack/prereqs.hpp>

#include <boost/ptr_container/ptr_vector.hpp>

#include "../visitor/delete_visitor.hpp"
#include "../visitor/copy_visitor.hpp"
#include "../visitor/delta_visitor.hpp"
#include "../visitor/output_height_visitor.hpp"
#include "../visitor/output_parameter_visitor.hpp"
#include "../visitor/output_width_visitor.hpp"
#include "../visitor/input_shape_visitor.hpp"

#include "layer_types.hpp"
#include "add_merge.hpp"

namespace mlpack {
namespace ann  {

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

  Sequential(const bool model, const bool ownsLayers);

  Sequential(const Sequential& layer);

  Sequential& operator = (const Sequential& layer);

  ~Sequential();

  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>& 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); }

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

    return empty;
  }

  const arma::mat& Parameters() const { return parameters; }
  arma::mat& Parameters() { return parameters; }

  arma::mat const& InputParameter() const { return inputParameter; }
  arma::mat& InputParameter() { return inputParameter; }

  arma::mat const& OutputParameter() const { return outputParameter; }
  arma::mat& OutputParameter() { return outputParameter; }

  arma::mat const& Delta() const { return delta; }
  arma::mat& Delta() { return delta; }

  arma::mat const& Gradient() const { return gradient; }
  arma::mat& Gradient() { return gradient; }

  size_t InputShape() const;

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

 private:
  bool model;

  bool reset;

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

  arma::mat parameters;

  DeltaVisitor deltaVisitor;

  OutputParameterVisitor outputParameterVisitor;

  DeleteVisitor deleteVisitor;

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

  arma::mat delta;

  arma::mat inputParameter;

  arma::mat outputParameter;

  arma::mat gradient;

  OutputWidthVisitor outputWidthVisitor;

  OutputHeightVisitor outputHeightVisitor;

  CopyVisitor<CustomLayers...> copyVisitor;

  size_t width;

  size_t height;

  bool ownsLayers;
}; // class Sequential

/*
 * Convenience typedef for use as Residual<> layer.
 */
template<
  typename InputDataType = arma::mat,
  typename OutputDataType = arma::mat,
  typename... CustomLayers
>
using Residual = Sequential<
    InputDataType, OutputDataType, true, CustomLayers...>;

} // namespace ann
} // namespace mlpack

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

#endif