Remove BaseConfig.get_config_dict since it is the same implementation…

… as the base class (PretrainedConfig)

optimum/configuration_utils.py

@@ -124,37 +124,6 @@ def get_configuration_file(cls, configuration_files: List[str]) -> str:
 
  return configuration_file
 
- # Adapted from transformers.configuration_utils.PretrainedConfig.get_config_dict
- @classmethod
- def get_config_dict(
- cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs
- ) -> Tuple[Dict[str, Any], Dict[str, Any]]:
- """
- From a `pretrained_model_name_or_path`, resolve to a dictionary of parameters, to be used for instantiating a
- [`PretrainedConfig`] using `from_dict`.
-
- Parameters:
- pretrained_model_name_or_path (`str` or `os.PathLike`):
- The identifier of the pre-trained checkpoint from which we want the dictionary of parameters.
-
- Returns:
- `Tuple[Dict, Dict]`: The dictionary(ies) that will be used to instantiate the configuration object.
- """
- original_kwargs = copy.deepcopy(kwargs)
- # Get config dict associated with the base config file
- config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
- if "_commit_hash" in config_dict:
- original_kwargs["_commit_hash"] = config_dict["_commit_hash"]
-
- # That config file may point us toward another config file to use.
- if "configuration_files" in config_dict:
- configuration_file = cls.get_configuration_file(config_dict["configuration_files"])
- config_dict, kwargs = cls._get_config_dict(
- pretrained_model_name_or_path, _configuration_file=configuration_file, **original_kwargs
- )
-
- return config_dict, kwargs
-
  # Adapted from transformers.configuration_utils.PretrainedConfig._get_config_dict
  @classmethod
  def _get_config_dict(