def METHOD_NAME(self, model_id: str, trial_id: str) -> Tuple[torch.jit.ScriptModule, Dict]:
    """
    Returns:
        jit_model: a ScriptModule contains model architecture and parameters, which can be deployed cross-platform
        model_config: a dict contains model attributes
    """
    file_path = os.path.join(self.__model_dir, f'{model_id}', f'{trial_id}.pt')
    if model_id in self.__model_cache:
        return self.__model_cache[file_path]
    else:
        if not os.path.exists(file_path):
            raise ModelNotExistError(file_path)
        else:
            tmp_dict = {'model_config': ''}
            jit_model = torch.jit.load(file_path, _extra_files=tmp_dict)
            model_config = json.loads(tmp_dict['model_config'])
            self.__model_cache[file_path] = jit_model, model_config
            return jit_model, model_config