convolution.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_CONVOLUTION_HPP
#define MLPACK_METHODS_ANN_LAYER_CONVOLUTION_HPP

#include <mlpack/prereqs.hpp>

#include <mlpack/methods/ann/convolution_rules/border_modes.hpp>
#include <mlpack/methods/ann/convolution_rules/naive_convolution.hpp>
#include <mlpack/methods/ann/convolution_rules/fft_convolution.hpp>
#include <mlpack/methods/ann/convolution_rules/svd_convolution.hpp>
#include <mlpack/core/util/to_lower.hpp>

#include "layer.hpp"
#include "padding.hpp"

namespace mlpack {
namespace ann  {

template <
    typename ForwardConvolutionRule = NaiveConvolution<ValidConvolution>,
    typename BackwardConvolutionRule = NaiveConvolution<FullConvolution>,
    typename GradientConvolutionRule = NaiveConvolution<ValidConvolution>,
    typename MatType = arma::mat
>
class ConvolutionType : public Layer<MatType>
{
 public:
  ConvolutionType();

  ConvolutionType(const size_t maps,
                  const size_t kernelWidth,
                  const size_t kernelHeight,
                  const size_t strideWidth = 1,
                  const size_t strideHeight = 1,
                  const size_t padW = 0,
                  const size_t padH = 0,
                  const std::string& paddingType = "none");

  ConvolutionType(const size_t maps,
                  const size_t kernelWidth,
                  const size_t kernelHeight,
                  const size_t strideWidth,
                  const size_t strideHeight,
                  const std::tuple<size_t, size_t>& padW,
                  const std::tuple<size_t, size_t>& padH,
                  const std::string& paddingType = "none");

  ConvolutionType* Clone() const { return new ConvolutionType(*this); }

  ConvolutionType(const ConvolutionType& layer);

  ConvolutionType(ConvolutionType&&);

  ConvolutionType& operator=(const ConvolutionType& layer);

  ConvolutionType& operator=(ConvolutionType&& layer);

  // Virtual destructor.
  virtual ~ConvolutionType() { }

  /*
   * Set the weight and bias term.
   */
  void SetWeights(typename MatType::elem_type* weightsPtr);

  void Forward(const MatType& input, MatType& output);

  void Backward(const MatType& /* input */,
                const MatType& gy,
                MatType& g);

  void Gradient(const MatType& /* input */,
                const MatType& error,
                MatType& gradient);

  MatType const& Parameters() const { return weights; }
  MatType& Parameters() { return weights; }

  arma::Cube<typename MatType::elem_type> const& Weight() const
  {
    return weight;
  }
  arma::Cube<typename MatType::elem_type>& Weight() { return weight; }

  MatType const& Bias() const { return bias; }
  MatType& Bias() { return bias; }

  size_t const& Maps() const { return maps; }

  size_t const& KernelWidth() const { return kernelWidth; }
  size_t& KernelWidth() { return kernelWidth; }

  size_t const& KernelHeight() const { return kernelHeight; }
  size_t& KernelHeight() { return kernelHeight; }

  size_t const& StrideWidth() const { return strideWidth; }
  size_t& StrideWidth() { return strideWidth; }

  size_t const& StrideHeight() const { return strideHeight; }
  size_t& StrideHeight() { return strideHeight; }

  size_t const& PadHTop() const { return padHTop; }
  size_t& PadHTop() { return padHTop; }

  size_t const& PadHBottom() const { return padHBottom; }
  size_t& PadHBottom() { return padHBottom; }

  size_t const& PadWLeft() const { return padWLeft; }
  size_t& PadWLeft() { return padWLeft; }

  size_t const& PadWRight() const { return padWRight; }
  size_t& PadWRight() { return padWRight; }

  size_t WeightSize() const
  {
    return (maps * inMaps * higherInDimensions * kernelWidth * kernelHeight) +
        maps;
  }

  void ComputeOutputDimensions();

  template<typename Archive>
  void serialize(Archive& ar, const uint32_t /* version */);

 private:
  size_t ConvOutSize(const size_t size,
                     const size_t k,
                     const size_t s,
                     const size_t pSideOne,
                     const size_t pSideTwo)
  {
    return std::floor(size + pSideOne + pSideTwo - k) / s + 1;
  }

  void InitializeSamePadding();

  template<typename eT>
  void Rotate180(const arma::Cube<eT>& input, arma::Cube<eT>& output)
  {
    output = arma::Cube<eT>(input.n_rows, input.n_cols, input.n_slices);

    // * left-right flip, up-down flip */
    for (size_t s = 0; s < output.n_slices; s++)
      output.slice(s) = arma::fliplr(arma::flipud(input.slice(s)));
  }

  template<typename eT>
  void Rotate180(const arma::Mat<eT>& input, arma::Mat<eT>& output)
  {
    // * left-right flip, up-down flip */
    output = arma::fliplr(arma::flipud(input));
  }

  size_t maps;

  size_t batchSize;

  size_t kernelWidth;

  size_t kernelHeight;

  size_t strideWidth;

  size_t strideHeight;

  size_t padWLeft;

  size_t padWRight;

  size_t padHBottom;

  size_t padHTop;

  MatType weights;

  arma::Cube<typename MatType::elem_type> weight;

  MatType bias;

  arma::Cube<typename MatType::elem_type> outputTemp;

  MatType inputPadded;

  arma::Cube<typename MatType::elem_type> gTemp;

  arma::Cube<typename MatType::elem_type> gradientTemp;

  ann::Padding padding;

  std::string paddingType;

  size_t inMaps;
  size_t higherInDimensions;
}; // class Convolution

// Standard Convolution layer.
typedef ConvolutionType<
    NaiveConvolution<ValidConvolution>,
    NaiveConvolution<FullConvolution>,
    NaiveConvolution<ValidConvolution>,
    arma::mat
> Convolution;

} // namespace ann
} // namespace mlpack

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

#endif