Program Listing for File cfg.h

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#ifndef MINDSPORE_INCLUDE_API_CFG_H
#define MINDSPORE_INCLUDE_API_CFG_H

#include <cstddef>
#include <string>
#include <vector>
#include <memory>
#include "include/api/data_type.h"
#include "include/api/dual_abi_helper.h"
#include "include/api/types.h"

namespace mindspore {
constexpr int iter_th = 1000;
class MS_API MixPrecisionCfg {
 public:
  MixPrecisionCfg() {
    this->dynamic_loss_scale_ = false;
    this->loss_scale_ = 128.0f;
    this->keep_batchnorm_fp32_ = true;
    this->num_of_not_nan_iter_th_ = iter_th;
  }
  MixPrecisionCfg(const MixPrecisionCfg &rhs) {
    this->dynamic_loss_scale_ = rhs.dynamic_loss_scale_;
    this->loss_scale_ = rhs.loss_scale_;
    this->keep_batchnorm_fp32_ = rhs.keep_batchnorm_fp32_;
    this->num_of_not_nan_iter_th_ = rhs.num_of_not_nan_iter_th_;
  }
  ~MixPrecisionCfg() = default;

  bool dynamic_loss_scale_ = false;
  float loss_scale_;
  bool keep_batchnorm_fp32_ = true;
  uint32_t num_of_not_nan_iter_th_;
  bool is_raw_mix_precision_ = false;
};

class MS_API TrainCfg {
 public:
  TrainCfg() = default;
  TrainCfg(const TrainCfg &rhs) {
    this->loss_name_ = rhs.loss_name_;
    this->mix_precision_cfg_ = rhs.mix_precision_cfg_;
    this->accumulate_gradients_ = rhs.accumulate_gradients_;
  }
  ~TrainCfg() = default;

  inline std::vector<std::string> GetLossName() const;
  inline void SetLossName(const std::vector<std::string> &loss_name);

  OptimizationLevel optimization_level_ = kO0;
  MixPrecisionCfg mix_precision_cfg_;
  bool accumulate_gradients_ = false;

 private:
  std::vector<std::vector<char>> loss_name_ = VectorStringToChar({"loss_fct", "_loss_fn", "SigmoidCrossEntropy"});
};

std::vector<std::string> TrainCfg::GetLossName() const { return VectorCharToString(loss_name_); }
void TrainCfg::SetLossName(const std::vector<std::string> &loss_name) { loss_name_ = VectorStringToChar(loss_name); }
}  // namespace mindspore
#endif  // MINDSPORE_INCLUDE_API_CFG_H