gaussian_init.hpp

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#ifndef MLPACK_METHODS_ANN_INIT_RULES_GAUSSIAN_INIT_HPP
#define MLPACK_METHODS_ANN_INIT_RULES_GAUSSIAN_INIT_HPP

#include <mlpack/prereqs.hpp>
#include <mlpack/core/math/random.hpp>

using namespace mlpack::math;

namespace mlpack {
namespace ann  {

class GaussianInitialization
{
 public:
  GaussianInitialization(const double mean = 0, const double variance = 1) :
      mean(mean), variance(variance)
  {
    // Nothing to do here.
  }

  template<typename eT>
  void Initialize(arma::Mat<eT>& W,
                  const size_t rows,
                  const size_t cols)
  {
    if (W.is_empty())
    {
      W = arma::Mat<eT>(rows, cols);
    }
    W.imbue( [&]() { return arma::as_scalar(RandNormal(mean, variance)); } );
  }

  template<typename eT>
  void Initialize(arma::Cube<eT> & W,
                  const size_t rows,
                  const size_t cols,
                  const size_t slices)
  {
    W = arma::Cube<eT>(rows, cols, slices);

    for (size_t i = 0; i < slices; i++)
      Initialize(W.slice(i), rows, cols);
  }

 private:
  double mean;

  double variance;
}; // class GaussianInitialization

} // namespace ann
} // namespace mlpack

#endif