multiply_merge_impl.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_MULTIPLY_MERGE_IMPL_HPP
#define MLPACK_METHODS_ANN_LAYER_MULTIPLY_MERGE_IMPL_HPP

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

#include "../visitor/forward_visitor.hpp"
#include "../visitor/backward_visitor.hpp"
#include "../visitor/gradient_visitor.hpp"

namespace mlpack {
namespace ann  {

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::MultiplyMerge(
    const bool model, const bool run) :
    model(model), run(run), ownsLayer(!model)
{
  // Nothing to do here.
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::MultiplyMerge(
    const MultiplyMerge& layer) :
    model(layer.model),
    run(layer.run),
    ownsLayer(layer.ownsLayer),
    network(layer.network),
    weights(layer.weights)
{
  // Nothing to do here.
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::MultiplyMerge(
    MultiplyMerge&& layer) :
    model(std::move(layer.model)),
    run(std::move(layer.run)),
    ownsLayer(std::move(layer.ownsLayer)),
    network(std::move(layer.network)),
    weights(std::move(layer.weights))
{
  // Nothing to do here.
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>&
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::operator=(
    const MultiplyMerge& layer)
{
  if (this != &layer)
  {
    model = layer.model;
    run = layer.run;
    ownsLayer = layer.ownsLayer;
    network = layer.network;
    weights = layer.weights;
  }
  return *this;
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>&
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::operator=(
    MultiplyMerge&& layer)
{
  if (this != &layer)
  {
    model = std::move(layer.model);
    run = std::move(layer.run);
    ownsLayer = std::move(layer.ownsLayer);
    network = std::move(layer.network);
    weights = std::move(layer.weights);
  }
  return *this;
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::~MultiplyMerge()
{
  if (ownsLayer)
  {
    std::for_each(network.begin(), network.end(),
        boost::apply_visitor(deleteVisitor));
  }
}

template <typename InputDataType, typename OutputDataType,
          typename... CustomLayers>
template<typename InputType, typename OutputType>
void MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::Forward(
    const InputType& input, OutputType& output)
{
  if (run)
  {
    for (size_t i = 0; i < network.size(); ++i)
    {
      boost::apply_visitor(ForwardVisitor(input,
          boost::apply_visitor(outputParameterVisitor, network[i])),
          network[i]);
    }
  }

  output = boost::apply_visitor(outputParameterVisitor, network.front());
  for (size_t i = 1; i < network.size(); ++i)
  {
    output %= boost::apply_visitor(outputParameterVisitor, network[i]);
  }
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
template<typename eT>
void MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::Backward(
    const arma::Mat<eT>& /* input */, const arma::Mat<eT>& gy, arma::Mat<eT>& g)
{
  if (run)
  {
    for (size_t i = 0; i < network.size(); ++i)
    {
      boost::apply_visitor(BackwardVisitor(boost::apply_visitor(
          outputParameterVisitor, network[i]), gy,
          boost::apply_visitor(deltaVisitor, network[i])), network[i]);
    }

    g = boost::apply_visitor(deltaVisitor, network[0]);
    for (size_t i = 1; i < network.size(); ++i)
    {
      g += boost::apply_visitor(deltaVisitor, network[i]);
    }
  }
  else
    g = gy;
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
template<typename eT>
void MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::Gradient(
    const arma::Mat<eT>& input,
    const arma::Mat<eT>& error,
    arma::Mat<eT>& /* gradient */ )
{
  if (run)
  {
    for (size_t i = 0; i < network.size(); ++i)
    {
      boost::apply_visitor(GradientVisitor(input, error), network[i]);
    }
  }
}

template<typename InputDataType, typename OutputDataType,
         typename... CustomLayers>
template<typename Archive>
void MultiplyMerge<InputDataType, OutputDataType, CustomLayers...>::serialize(
    Archive& ar, const uint32_t /* version */)
{
  // Be sure to clear other layers before loading.
  if (cereal::is_loading<Archive>())
    network.clear();

  ar(CEREAL_VECTOR_VARIANT_POINTER(network));
  ar(CEREAL_NVP(model));
  ar(CEREAL_NVP(run));
  ar(CEREAL_NVP(ownsLayer));
}

} // namespace ann
} // namespace mlpack

#endif