add_impl.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_ADD_IMPL_HPP
#define MLPACK_METHODS_ANN_LAYER_ADD_IMPL_HPP

// In case it hasn't yet been included.
#include "add.hpp"

namespace mlpack {
namespace ann  {

template<typename InputDataType, typename OutputDataType>
Add<InputDataType, OutputDataType>::Add(const size_t outSize) :
    outSize(outSize)
{
  weights.set_size(WeightSize(), 1);
}

template<typename InputDataType, typename OutputDataType>
template<typename eT>
void Add<InputDataType, OutputDataType>::Forward(
    const arma::Mat<eT>& input, arma::Mat<eT>& output)
{
  output = input;
  output.each_col() += weights;
}

template<typename InputDataType, typename OutputDataType>
template<typename eT>
void Add<InputDataType, OutputDataType>::Backward(
    const arma::Mat<eT>& /* input */,
    const arma::Mat<eT>& gy,
    arma::Mat<eT>& g)
{
  g = gy;
}

template<typename InputDataType, typename OutputDataType>
template<typename eT>
void Add<InputDataType, OutputDataType>::Gradient(
    const arma::Mat<eT>& /* input */,
    const arma::Mat<eT>& error,
    arma::Mat<eT>& gradient)
{
  gradient = error;
}

template<typename InputDataType, typename OutputDataType>
template<typename Archive>
void Add<InputDataType, OutputDataType>::serialize(
    Archive& ar, const uint32_t /* version */)
{
  ar(CEREAL_NVP(outSize));

  if (cereal::is_loading<Archive>())
    weights.set_size(outSize, 1);
}

} // namespace ann
} // namespace mlpack

#endif