def METHOD_NAME(self,
               model: nn.Module,
               model_config: Dict,
               model_id: str,
               trial_id: str) -> str:
    """
    Note: model config for time series should contain 'input_len' and 'input_vars'
    """
    model_dir_path = os.path.join(self.__model_dir, f'{model_id}')
    if not os.path.exists(model_dir_path):
        os.makedirs(model_dir_path)
    model_file_path = os.path.join(model_dir_path, f'{trial_id}.pt')
    sample_input = [torch.randn(1, model_config['input_len'], model_config['input_vars'])]
    torch.jit.save(torch.jit.trace(model, sample_input),
                   model_file_path,
                   _extra_files={'model_config': json.dumps(model_config)})
    return os.path.abspath(model_file_path)