sparse_autoencoder.hpp

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#ifndef MLPACK_METHODS_SPARSE_AUTOENCODER_SPARSE_AUTOENCODER_HPP
#define MLPACK_METHODS_SPARSE_AUTOENCODER_SPARSE_AUTOENCODER_HPP

#include <mlpack/prereqs.hpp>
#include <mlpack/core/optimizers/lbfgs/lbfgs.hpp>

#include "sparse_autoencoder_function.hpp"

namespace mlpack {
namespace nn {

template<
  template<typename> class OptimizerType = mlpack::optimization::L_BFGS
>
class SparseAutoencoder
{
 public:
  SparseAutoencoder(const arma::mat& data,
                    const size_t visibleSize,
                    const size_t hiddenSize,
                    const double lambda = 0.0001,
                    const double beta = 3,
                    const double rho = 0.01);

  SparseAutoencoder(OptimizerType<SparseAutoencoderFunction>& optimizer);

  void GetNewFeatures(arma::mat& data, arma::mat& features);

  void Sigmoid(const arma::mat& x, arma::mat& output) const
  {
    output = (1.0 / (1 + arma::exp(-x)));
  }

  void VisibleSize(const size_t visible)
  {
    this->visibleSize = visible;
  }

  size_t VisibleSize() const
  {
    return visibleSize;
  }

  void HiddenSize(const size_t hidden)
  {
    this->hiddenSize = hidden;
  }

  size_t HiddenSize() const
  {
    return hiddenSize;
  }

  void Lambda(const double l)
  {
    this->lambda = l;
  }

  double Lambda() const
  {
    return lambda;
  }

  void Beta(const double b)
  {
    this->beta = b;
  }

  double Beta() const
  {
    return beta;
  }

  void Rho(const double r)
  {
    this->rho = r;
  }

  double Rho() const
  {
    return rho;
  }

 private:
  arma::mat parameters;
  size_t visibleSize;
  size_t hiddenSize;
  double lambda;
  double beta;
  double rho;
};

} // namespace nn
} // namespace mlpack

// Include implementation.
#include "sparse_autoencoder_impl.hpp"

#endif