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.

        """
        cls._set_token_in_kwargs(kwargs)

        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 = 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

        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.

        
dpkd/transformers/src/transformers/configuration_utils.py