concat.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_CONCAT_HPP
#define MLPACK_METHODS_ANN_LAYER_CONCAT_HPP
 
#include <mlpack/prereqs.hpp>
 
#include "../visitor/delete_visitor.hpp"
#include "../visitor/delta_visitor.hpp"
#include "../visitor/output_parameter_visitor.hpp"
 
#include <boost/ptr_container/ptr_vector.hpp>
 
#include "layer_types.hpp"
 
namespace mlpack {
namespace ann  {
 
template <
    typename InputDataType = arma::mat,
    typename OutputDataType = arma::mat,
    typename... CustomLayers
>
class Concat
{
 public:
  Concat(const bool model = false,
         const bool run = true);
 
  Concat(arma::Row<size_t>& inputSize,
         const size_t axis,
         const bool model = false,
         const bool run = true);
 
  ~Concat();
 
  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);
 
  template<typename eT>
  void Backward(const arma::Mat<eT>& /* input */,
                const arma::Mat<eT>& gy,
                arma::Mat<eT>& g,
                const size_t index);
 
  /*
   * 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 */);
 
  /*
   * This is the overload of Gradient() that runs a specific layer with the
   * given input.
   *
   * @param input The input parameter used for calculating the gradient.
   * @param error The calculated error.
   * @param gradient The calculated gradient.
   * @param The index of the layer to run.
   */
  template<typename eT>
  void Gradient(const arma::Mat<eT>& input,
                const arma::Mat<eT>& error,
                arma::Mat<eT>& gradient,
                const size_t index);
 
  /*
   * 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; }
 
  bool Run() const { return run; }
  bool& Run() { return run; }
 
  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 const& ConcatAxis() const { return axis; }
 
  template<typename Archive>
  void serialize(Archive& /* ar */, const unsigned int /* version */);
 
 private:
  arma::Row<size_t> inputSize;
 
  size_t axis;
 
  bool useAxis;
 
  bool model;
 
  bool run;
 
  size_t channels;
 
  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;
}; // class Concat
 
} // namespace ann
} // namespace mlpack
 
// Include implementation.
#include "concat_impl.hpp"
 
#endif