def METHOD_NAME(self, input: Dict[str,
                              Tensor]) -> Dict[str, Union[list, Tensor]]:
    """return the result by the model
    Args:
        input (Dict[str, Tensor]): the preprocessed data
    Returns:
        Dict[str, Union[list, Tensor]]: results
    """
    for key, value in input.items():
        input[key] = input[key].to(self._device)
    if 'target' in input:
        return self._evaluate_postprocess(**input)
    else:
        return self._inference_forward(**input)