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26
utils/masking.py
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26
utils/masking.py
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import torch
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class TriangularCausalMask():
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def __init__(self, B, L, device="cpu"):
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mask_shape = [B, 1, L, L]
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with torch.no_grad():
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self._mask = torch.triu(torch.ones(mask_shape, dtype=torch.bool), diagonal=1).to(device)
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@property
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def mask(self):
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return self._mask
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class ProbMask():
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def __init__(self, B, H, L, index, scores, device="cpu"):
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_mask = torch.ones(L, scores.shape[-1], dtype=torch.bool).to(device).triu(1)
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_mask_ex = _mask[None, None, :].expand(B, H, L, scores.shape[-1])
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indicator = _mask_ex[torch.arange(B)[:, None, None],
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torch.arange(H)[None, :, None],
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index, :].to(device)
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self._mask = indicator.view(scores.shape).to(device)
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@property
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def mask(self):
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return self._mask
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