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