convert_dense.cpp

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#include "../../../include/common/monolish_dense.hpp"
#include "../../../include/common/monolish_logger.hpp"
#include "../../../include/common/monolish_matrix.hpp"
#include "../../internal/monolish_internal.hpp"
 
namespace monolish {
namespace matrix {
 
template <typename T> void Dense<T>::convert(const COO<T> &coo) {
  Logger &logger = Logger::get_instance();
  logger.util_in(monolish_func);
 
  set_row(coo.get_row());
  set_col(coo.get_col());
  set_nnz(get_row() * get_col());
  val.resize(get_row() * get_col());
 
#pragma omp parallel for
  for (size_t i = 0; i < get_nnz(); i++) {
    val[i] = 0.0;
  }
 
  for (size_t i = 0; i < coo.get_nnz(); i++) {
    insert(coo.row_index[i], coo.col_index[i], coo.val[i]);
  }
  logger.util_out();
}
template void Dense<double>::convert(const COO<double> &coo);
template void Dense<float>::convert(const COO<float> &coo);
 
template <typename T> void Dense<T>::convert(const Dense<T> &mat) {
  Logger &logger = Logger::get_instance();
  logger.util_in(monolish_func);
 
  val.resize(mat.get_nnz());
 
  rowN = mat.get_row();
  colN = mat.get_col();
  nnz = mat.get_nnz();
 
#if MONOLISH_USE_GPU
  if (mat.get_device_mem_stat()) {
    throw std::runtime_error(
        "error can not convert CRS->CRS when gpu_status == true");
  }
#endif
  internal::vcopy(get_nnz(), mat.val.data(), val.data(), false);
 
  logger.util_out();
}
template void Dense<double>::convert(const Dense<double> &mat);
template void Dense<float>::convert(const Dense<float> &mat);
 
} // namespace matrix
} // namespace monolish