import tensorflow as tf

        if mode == compat.ModeKeys.INFER:
            input_dict["trg_input"] = target_bos
        else:
            input_dict["trg"] = batch_of_data["label"]
            input_dict["trg_length"] = deduce_text_length(batch_of_data["label"],
                                                          self._multilingual_dp.meta["pad_id"],
                                                          self._multilingual_dp.meta["padding_mode"])
            input_dict["trg_input"] = tf.concat([tf.expand_dims(target_bos, axis=1),
                                                 batch_of_data["label"][:, :-1]], axis=1)
        return input_dict

    def get_data_postprocess_fn(self, data_status, **kwargs) -> callable:
        if data_status == compat.DataStatus.PROJECTED:
            return self._multilingual_dp.decode
