subview.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_SUBVIEW_HPP
#define MLPACK_METHODS_ANN_LAYER_SUBVIEW_HPP

#include <mlpack/prereqs.hpp>
#include <mlpack/methods/ann/activation_functions/identity_function.hpp>

namespace mlpack {
namespace ann {

template <
    typename InputDataType = arma::mat,
    typename OutputDataType = arma::mat
>
class Subview
{
 public:
  Subview(const size_t inSize = 1,
          const size_t beginRow = 0,
          const size_t endRow = 0,
          const size_t beginCol = 0,
          const size_t endCol = 0) :
      inSize(inSize),
      beginRow(beginRow),
      endRow(endRow),
      beginCol(beginCol),
      endCol(endCol)
  {
    /* Nothing to do here */
  }

  template<typename InputType, typename OutputType>
  void Forward(InputType&& input, OutputType&& output)
  {
    size_t batchSize = input.n_cols / inSize;

    // Check if subview parameters are within the indices of input sample.
    endRow = ((endRow < input.n_rows) && (endRow >= beginRow))?
        endRow : (input.n_rows - 1);
    endCol = ((endCol < inSize) && (endCol >= beginCol)) ?
        endCol : (inSize - 1);

    output.set_size(
        (endRow - beginRow + 1) * (endCol - beginCol + 1), batchSize);

    size_t batchBegin = beginCol;
    size_t batchEnd = endCol;

    // Check whether the input is already in desired form.
    if ((input.n_rows != ((endRow - beginRow + 1) *
        (endCol - beginCol + 1))) || (input.n_cols != batchSize))
    {
      for (size_t i = 0; i < batchSize; i++)
      {
        output.col(i) = arma::vectorise(
            input.submat(beginRow, batchBegin, endRow, batchEnd));

        // Move to next batch.
        batchBegin += inSize;
        batchEnd += inSize;
      }
    }
    else
    {
      output = input;
    }
  }

  template<typename eT>
  void Backward(arma::Mat<eT>&& /* input */,
                arma::Mat<eT>&& gy,
                arma::Mat<eT>&& g)
  {
    g = gy;
  }

  OutputDataType const& OutputParameter() const { return outputParameter; }
  OutputDataType& OutputParameter() { return outputParameter; }

  OutputDataType const& Delta() const { return delta; }
  OutputDataType& Delta() { return delta; }

  template<typename Archive>
  void serialize(Archive& ar, const unsigned int /* version */)
  {
    ar & BOOST_SERIALIZATION_NVP(inSize);
    ar & BOOST_SERIALIZATION_NVP(beginRow);
    ar & BOOST_SERIALIZATION_NVP(endRow);
    ar & BOOST_SERIALIZATION_NVP(beginCol);
    ar & BOOST_SERIALIZATION_NVP(endCol);
  }

 private:
  size_t inSize;

  size_t beginRow;

  size_t endRow;

  size_t beginCol;

  size_t endCol;

  OutputDataType delta;

  OutputDataType outputParameter;
}; // class Subview

} // namespace ann
} // namespace mlpack

#endif