relu6_impl.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_RELU6_IMPL_HPP
#define MLPACK_METHODS_ANN_LAYER_RELU6_IMPL_HPP

// In case it hasn't yet been included.
#include "relu6.hpp"

namespace mlpack {
namespace ann  {

template<typename InputDataType, typename OutputDataType>
ReLU6<InputDataType, OutputDataType>::ReLU6()
{
  // Nothing to do here.
}

template<typename InputDataType, typename OutputDataType>
template<typename InputType, typename OutputType>
void ReLU6<InputDataType, OutputDataType>::Forward(
    const InputType& input, OutputType& output)
{ 
  OutputType outputTemp(arma::size(input));
  outputTemp.fill(6.0);
  output = arma::zeros<OutputType>(arma::size(input));
  output = arma::min(arma::max(output, input), outputTemp);
}

template<typename InputDataType, typename OutputDataType>
template<typename DataType>
void ReLU6<InputDataType, OutputDataType>::Backward(
    const DataType& input, const DataType& gy, DataType& g)
{
  DataType derivative(arma::size(gy));
  derivative.fill(0.0);
  for (size_t i = 0; i < input.n_elem; ++i)
  {
    if (input(i) < 6 && input(i) > 0)
      derivative(i) = 1.0;
  }

  g = gy % derivative;
}

template<typename InputDataType, typename OutputDataType>
template<typename Archive>
void ReLU6<InputDataType, OutputDataType>::serialize(
    Archive& ar,
    const uint32_t /* version */)
{
  // Nothing to do here.
}

} // namespace ann
} // namespace mlpack

#endif