def METHOD_NAME(
    self,
    label_sequence: List[int],
    states: Optional[Any] = None,
) -> Tuple[torch.Tensor, None]:
    """One-step forward hypothesis.
    Args:
        label_sequence: Current label sequence.
        states: Decoder hidden states. None
    Returns:
        : Decoder output sequence. (1, D_emb)
        state: Decoder hidden states. None
    """
    str_labels = "_".join(map(str, label_sequence))
    if str_labels in self.score_cache:
        embed = self.score_cache[str_labels]
    else:
        label = torch.full(
            (1, 1),
            label_sequence[-1],
            dtype=torch.long,
            device=self.device,
        )
        embed = self.embed(label)
        self.score_cache[str_labels] = embed
    return embed[0], None