def METHOD_NAME(
    self,
    tokenized_sentences: List[torch.LongTensor],
    *args,
    inference_step_args=None,
    skip_invalid_size_inputs=False,
    **kwargs
) -> List[List[Dict[str, torch.Tensor]]]:
    inference_step_args = inference_step_args or {}
    if "prefix_tokens" in inference_step_args:
        raise NotImplementedError("prefix generation not implemented for BART")
    res = []
    for batch in self._build_batches(tokenized_sentences, skip_invalid_size_inputs):
        src_tokens = batch["net_input"]["src_tokens"]
        inference_step_args["prefix_tokens"] = src_tokens.new_full(
            (src_tokens.size(0), 1), fill_value=self.task.source_dictionary.bos()
        ).to(device=self.device)
        results = super().METHOD_NAME(
            src_tokens,
            *args,
            inference_step_args=inference_step_args,
            skip_invalid_size_inputs=skip_invalid_size_inputs,
            **kwargs
        )
        for id, hypos in zip(batch["id"].tolist(), results):
            res.append((id, hypos))
    res = [hypos for _, hypos in sorted(res, key=lambda x: x[0])]
    return res