| |
| |
| import copy |
| import os |
| from typing import Any, Dict, Union |
|
|
| import yaml |
|
|
|
|
| CONFIG_FILE = "config.yaml" |
| DISCRIMINATOR_CONFIG_FILE = "discriminator_config.yaml" |
|
|
|
|
| class PretrainedConfig(object): |
| def __init__(self, **kwargs): |
| pass |
|
|
| @classmethod |
| def _dict_from_yaml_file(cls, yaml_file: Union[str, os.PathLike]): |
| with open(yaml_file, encoding="utf-8") as f: |
| config_dict = yaml.safe_load(f) |
| return config_dict |
|
|
| @classmethod |
| def get_config_dict( |
| cls, pretrained_model_name_or_path: Union[str, os.PathLike] |
| ) -> Dict[str, Any]: |
| if os.path.isdir(pretrained_model_name_or_path): |
| config_file = os.path.join(pretrained_model_name_or_path, CONFIG_FILE) |
| else: |
| config_file = pretrained_model_name_or_path |
| config_dict = cls._dict_from_yaml_file(config_file) |
| return config_dict |
|
|
| @classmethod |
| def from_dict(cls, config_dict: Dict[str, Any], **kwargs): |
| for k, v in kwargs.items(): |
| if k in config_dict.keys(): |
| config_dict[k] = v |
| config = cls(**config_dict) |
| return config |
|
|
| @classmethod |
| def from_pretrained( |
| cls, |
| pretrained_model_name_or_path: Union[str, os.PathLike], |
| **kwargs, |
| ): |
| config_dict = cls.get_config_dict(pretrained_model_name_or_path) |
| return cls.from_dict(config_dict, **kwargs) |
|
|
| def to_dict(self): |
| output = copy.deepcopy(self.__dict__) |
| return output |
|
|
| def to_yaml_file(self, yaml_file_path: Union[str, os.PathLike]): |
| config_dict = self.to_dict() |
|
|
| with open(yaml_file_path, "w", encoding="utf-8") as writer: |
| yaml.safe_dump(config_dict, writer) |
|
|
|
|
| if __name__ == '__main__': |
| pass |
|
|
