lookup.hpp

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#ifndef MLPACK_METHODS_ANN_LAYER_LOOKUP_HPP
#define MLPACK_METHODS_ANN_LAYER_LOOKUP_HPP

#include <mlpack/prereqs.hpp>
#include <mlpack/methods/ann/layer/layer_traits.hpp>

namespace mlpack {
namespace ann /* Artificial Neural Network. */ {

template <
    typename InputDataType = arma::mat,
    typename OutputDataType = arma::mat
>
class Lookup
{
 public:
  Lookup(const size_t vocabSize = 0, const size_t embeddingSize = 0);

  template<typename eT>
  void Forward(const arma::Mat<eT>& input, arma::Mat<eT>& output);

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

  template<typename eT>
  void Gradient(const arma::Mat<eT>& input,
                const arma::Mat<eT>& error,
                arma::Mat<eT>& gradient);

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

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

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

  OutputDataType const& Gradient() const { return gradient; }
  OutputDataType& Gradient() { return gradient; }

  size_t VocabSize() const { return vocabSize; }

  size_t EmbeddingSize() const { return embeddingSize; }

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

 private:
  size_t vocabSize;

  size_t embeddingSize;

  OutputDataType weights;

  OutputDataType delta;

  OutputDataType gradient;

  OutputDataType outputParameter;
}; // class Lookup

// Alias for using as embedding layer.
template<typename MatType = arma::mat>
using Embedding = Lookup<MatType, MatType>;

} // namespace ann
} // namespace mlpack

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

#endif