import torch

class TriangularCausalMask():

    def __init__(self, B, L, device="cpu"):

        mask_shape = [B, 1, L, L]

        with torch.no_grad():

            self._mask = torch.triu(torch.ones(mask_shape, dtype=torch.bool), diagonal=1).to(device)

    @property

    def mask(self):

        return self._mask

class ProbMask():

    def __init__(self, B, H, L, index, scores, device="cpu"):

        _mask = torch.ones(L, scores.shape[-1], dtype=torch.bool).to(device).triu(1)

        _mask_ex = _mask[None, None, :].expand(B, H, L, scores.shape[-1])

        indicator = _mask_ex[torch.arange(B)[:, None, None],

                    torch.arange(H)[None, :, None],

                    index, :].to(device)

        self._mask = indicator.view(scores.shape).to(device)

    @property

    def mask(self):

        return self._mask