celu_impl.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_CELU_IMPL_HPP
#define MLPACK_METHODS_ANN_LAYER_CELU_IMPL_HPP

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

namespace mlpack {
namespace ann  {

template<typename InputDataType, typename OutputDataType>
CELU<InputDataType, OutputDataType>::CELU(const double alpha) :
    alpha(alpha),
    deterministic(false)
{
  if (alpha == 0)
  {
    Log::Fatal << "The value of alpha cannot be equal to 0, "
               << "terminating the program." << std::endl;
  }
}

template<typename InputDataType, typename OutputDataType>
template<typename InputType, typename OutputType>
void CELU<InputDataType, OutputDataType>::Forward(
    const InputType& input, OutputType& output)
{
  output = arma::ones<OutputDataType>(arma::size(input));
  for (size_t i = 0; i < input.n_elem; ++i)
  {
    output(i) = (input(i) >= 0) ? input(i) : alpha *
                (std::exp(input(i) / alpha) - 1);
  }

  if (!deterministic)
  {
    derivative.set_size(arma::size(input));
    for (size_t i = 0; i < input.n_elem; ++i)
    {
      derivative(i) = (input(i) >= 0) ? 1 :
          (output(i) / alpha) + 1;
    }
  }
}

template<typename InputDataType, typename OutputDataType>
template<typename DataType>
void CELU<InputDataType, OutputDataType>::Backward(
    const DataType& /* input */, const DataType& gy, DataType& g)
{
  g = gy % derivative;
}

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

} // namespace ann
} // namespace mlpack

#endif