network_init.hpp

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#ifndef MLPACK_METHODS_ANN_INIT_RULES_NETWORK_INIT_HPP
#define MLPACK_METHODS_ANN_INIT_RULES_NETWORK_INIT_HPP

#include <mlpack/prereqs.hpp>

#include "../visitor/reset_visitor.hpp"
#include "../visitor/weight_size_visitor.hpp"
#include "../visitor/weight_set_visitor.hpp"
#include "init_rules_traits.hpp"

#include <mlpack/methods/ann/layer/layer_types.hpp>

namespace mlpack {
namespace ann  {

template<typename InitializationRuleType, typename... CustomLayers>
class NetworkInitialization
{
 public:
  NetworkInitialization(
      const InitializationRuleType& initializeRule = InitializationRuleType()) :
      initializeRule(initializeRule)
  {
    // Nothing to do here.
  }

  void Initialize(const std::vector<LayerTypes<CustomLayers...> >& network,
                  arma::mat& parameter, size_t parameterOffset = 0)
  {
    // Determine the number of parameter/weights of the given network.
    if (parameter.is_empty())
    {
      size_t weights = 0;
      for (size_t i = 0; i < network.size(); ++i)
        weights += boost::apply_visitor(weightSizeVisitor, network[i]);
      parameter.set_size(weights, 1);
    }

    // Initialize the network layer by layer or the complete network.
    if (ann::InitTraits<InitializationRuleType>::UseLayer)
    {
      for (size_t i = 0, offset = parameterOffset; i < network.size(); ++i)
      {
        // Initialize the layer with the specified parameter/weight
        // initialization rule.
        const size_t weight = boost::apply_visitor(weightSizeVisitor,
            network[i]);
        arma::mat tmp = arma::mat(parameter.memptr() + offset,
            weight, 1, false, false);
        initializeRule.Initialize(tmp, tmp.n_elem, 1);

        // Increase the parameter/weight offset for the next layer.
        offset += weight;
      }
    }
    else
    {
      initializeRule.Initialize(parameter, parameter.n_elem, 1);
    }

    // Note: We can't merge the for loop into the for loop above because
    // WeightSetVisitor also sets the parameter/weights of the inner modules.
    // Inner Modules are held by the parent module e.g. the concat module can
    // hold various other modules.
    for (size_t i = 0, offset = parameterOffset; i < network.size(); ++i)
    {
      offset += boost::apply_visitor(WeightSetVisitor(parameter, offset),
          network[i]);

      boost::apply_visitor(resetVisitor, network[i]);
    }
  }

 private:
  InitializationRuleType initializeRule;

  ResetVisitor resetVisitor;

  WeightSizeVisitor weightSizeVisitor;
}; // class NetworkInitialization

} // namespace ann
} // namespace mlpack

#endif