def METHOD_NAME(
    self,
    xs_pad: torch.Tensor,
    ilens: torch.Tensor,
    prev_states: torch.Tensor = None,
) -> Tuple[torch.Tensor, torch.Tensor, Optional[torch.Tensor]]:
    """Embed positions in tensor.
    Args:
        xs_pad: input tensor (B, L, D)
        ilens: input length (B)
        prev_states: Not to be used now.
    Returns:
        position embedded tensor and mask
    """
    masks = (~make_pad_mask(ilens)[:, None, :]).to(xs_pad.device)
    xs_pad = self.embed(xs_pad)
    xs_pad, masks = self.encoders(xs_pad, masks)
    if self.normalize_before:
        xs_pad = self.after_norm(xs_pad)
    olens = masks.squeeze(1).sum(1)
    return xs_pad, olens