concat_performance.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_CONCAT_PERFORMANCE_HPP
#define MLPACK_METHODS_ANN_LAYER_CONCAT_PERFORMANCE_HPP

#include <mlpack/prereqs.hpp>

#include <boost/ptr_container/ptr_vector.hpp>

#include "layer_types.hpp"

namespace mlpack {
namespace ann  {

template <
    typename OutputLayerType = NegativeLogLikelihood<>,
    typename InputDataType = arma::mat,
    typename OutputDataType = arma::mat
>
class ConcatPerformance
{
 public:
  ConcatPerformance(const size_t inSize,
                    OutputLayerType&& outputLayer = OutputLayerType());

  /*
   * Computes the Negative log likelihood.
   *
   * @param input Input data used for evaluating the specified function.
   * @param output Resulting output activation.
   */
  template<typename eT>
  double Forward(const arma::Mat<eT>&& input, arma::Mat<eT>&& target);
  template<typename eT>
  void Backward(const arma::Mat<eT>&& input,
                const arma::Mat<eT>&& target,
                arma::Mat<eT>&& output);

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

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

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

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

 private:
  size_t inSize;

  OutputLayerType outputLayer;

  OutputDataType delta;

  InputDataType inputParameter;

  OutputDataType outputParameter;
}; // class ConcatPerformance

} // namespace ann
} // namespace mlpack

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

#endif