segmentation_eigen_inference_impl.h

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// Copyright 2021 CEA LIST
// SPDX-FileCopyrightText: 2022 CEA LIST <gael.de-chalendar@cea.fr>
//
// SPDX-License-Identifier: MIT
 
#ifndef DEEPLIMA_SRC_INCLUDE_SEGMENTATION_SEGMENTATION_EIGEN_INFERENCE_IMPL_H
#define DEEPLIMA_SRC_INCLUDE_SEGMENTATION_SEGMENTATION_EIGEN_INFERENCE_IMPL_H
 
#include <eigen3/Eigen/Dense>
 
#include "bilstm.h"
#include "bilstm_and_dense.h"
 
#include "embd_dict.h"
 
#include "deeplima/segmentation/impl/char_ngram.h"
#include "birnn_inference_base.h"
 
namespace deeplima
{
namespace segmentation
{
namespace eigen_impl
{
#ifdef WIN32
#ifdef SEGM_EXPORTING
  #define SEGM_EXPORT __declspec(dllexport)
#else
  #define SEGM_EXPORT  __declspec(dllimport)
#endif
#else
  #define SEGM_EXPORT
#endif
 
class SEGM_EXPORT BiRnnEigenInferenceForSegmentation : public deeplima::eigen_impl::BiRnnInferenceBase
{
public:
  typedef Eigen::MatrixXf Matrix;
  typedef Eigen::VectorXf Vector;
  typedef float Scalar;
  typedef Eigen::MatrixXf tensor_t;
  typedef EmbdUInt64FloatHolder dicts_holder_t;
  typedef deeplima::eigen_impl::BiRnnInferenceBase Parent;
 
  virtual void load(const std::string& fn)
  {
    convert_from_torch(fn);
  }
 
  const std::vector<impl::ngram_descr_t>& get_ngram_descr() const
  {
    return m_ngram_gescr;
  }
 
  virtual void precompute_inputs(
      const Eigen::MatrixXf& /*inputs*/,
      Eigen::MatrixXf& /*outputs*/,
      int64_t /*input_size*/
      )
  {
    throw std::runtime_error("Precomputing isn't supported for segmentation");
  }
 
  virtual void predict(
      size_t worker_id,
      const Eigen::MatrixXf& inputs,
      int64_t input_begin,
      int64_t input_end,
      int64_t output_begin,
      int64_t output_end,
      std::shared_ptr< StdMatrix<uint8_t> >& output,
      const std::vector<std::string>& /*outputs_names*/
      )
  {
    auto p_op = std::dynamic_pointer_cast<deeplima::eigen_impl::Op_BiLSTM_Dense_ArgMax<Eigen::MatrixXf, Eigen::VectorXf, float>>(Parent::m_ops[0]);
    assert(Parent::m_wb.size() > 0);
    assert(worker_id < Parent::m_wb[0].size());
    p_op->execute(Parent::m_wb[0][worker_id], inputs, Parent::m_params[0], output->m_tensor,
                  input_begin, input_end, output_begin, output_end);
  }
 
protected:
  std::vector<impl::ngram_descr_t> m_ngram_gescr;
 
  virtual void convert_from_torch(const std::string& fn);
};
 
 
} // namespace eigen_impl
} // namespace segmentation
} // namespace deeplima
 
#endif