log_cosh_loss_impl.hpp

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#ifndef MLPACK_METHODS_ANN_LOSS_FUNCTION_LOG_COSH_LOSS_IMPL_HPP
#define MLPACK_METHODS_ANN_LOSS_FUNCTION_LOG_COSH_LOSS_IMPL_HPP

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

namespace mlpack {
namespace ann  {

template<typename InputDataType, typename OutputDataType>
LogCoshLoss<InputDataType, OutputDataType>::LogCoshLoss(const double a) :
    a(a)
{
  Log::Assert(a > 0, "Hyper-Parameter \'a\' must be positive");
}

template<typename InputDataType, typename OutputDataType>
template<typename PredictionType, typename TargetType>
typename PredictionType::elem_type
LogCoshLoss<InputDataType, OutputDataType>::Forward(
    const PredictionType& prediction,
    const TargetType& target)
{
  return arma::accu(arma::log(arma::cosh(a * (target - prediction)))) / a;
}

template<typename InputDataType, typename OutputDataType>
template<typename PredictionType, typename TargetType, typename LossType>
void LogCoshLoss<InputDataType, OutputDataType>::Backward(
    const PredictionType& prediction,
    const TargetType& target,
    LossType& loss)
{
  loss = arma::tanh(a * (target - prediction));
}

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

} // namespace ann
} // namespace mlpack

#endif