espnet.nets.pytorch_backend.nets_utils.make_pad_mask

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espnet.nets.pytorch_backend.nets_utils.make_pad_mask(lengths, xs=None, length_dim=-1, maxlen=None)

Make mask tensor containing indices of padded part.

• Parameters:
  • lengths (LongTensor or List) – Batch of lengths (B,).
  • xs (Tensor , optional) – The reference tensor. If set, masks will be the same shape as this tensor.
  • length_dim (int , optional) – Dimension indicator of the above tensor. See the example.
• Returns: Mask tensor containing indices of padded part. : dtype=torch.uint8 in PyTorch 1.2- dtype=torch.bool in PyTorch 1.2+ (including 1.2)
• Return type: Tensor

Examples

With only lengths.

>>> lengths = [5, 3, 2]
>>> make_pad_mask(lengths)
masks = [[0, 0, 0, 0 ,0],
         [0, 0, 0, 1, 1],
         [0, 0, 1, 1, 1]]

With the reference tensor.

>>> xs = torch.zeros((3, 2, 4))
>>> make_pad_mask(lengths, xs)
tensor([[[0, 0, 0, 0],
         [0, 0, 0, 0]],
        [[0, 0, 0, 1],
         [0, 0, 0, 1]],
        [[0, 0, 1, 1],
         [0, 0, 1, 1]]], dtype=torch.uint8)
>>> xs = torch.zeros((3, 2, 6))
>>> make_pad_mask(lengths, xs)
tensor([[[0, 0, 0, 0, 0, 1],
         [0, 0, 0, 0, 0, 1]],
        [[0, 0, 0, 1, 1, 1],
         [0, 0, 0, 1, 1, 1]],
        [[0, 0, 1, 1, 1, 1],
         [0, 0, 1, 1, 1, 1]]], dtype=torch.uint8)

With the reference tensor and dimension indicator.

>>> xs = torch.zeros((3, 6, 6))
>>> make_pad_mask(lengths, xs, 1)
tensor([[[0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0],
         [1, 1, 1, 1, 1, 1]],
        [[0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0],
         [1, 1, 1, 1, 1, 1],
         [1, 1, 1, 1, 1, 1],
         [1, 1, 1, 1, 1, 1]],
        [[0, 0, 0, 0, 0, 0],
         [0, 0, 0, 0, 0, 0],
         [1, 1, 1, 1, 1, 1],
         [1, 1, 1, 1, 1, 1],
         [1, 1, 1, 1, 1, 1],
         [1, 1, 1, 1, 1, 1]]], dtype=torch.uint8)
>>> make_pad_mask(lengths, xs, 2)
tensor([[[0, 0, 0, 0, 0, 1],
         [0, 0, 0, 0, 0, 1],
         [0, 0, 0, 0, 0, 1],
         [0, 0, 0, 0, 0, 1],
         [0, 0, 0, 0, 0, 1],
         [0, 0, 0, 0, 0, 1]],
        [[0, 0, 0, 1, 1, 1],
         [0, 0, 0, 1, 1, 1],
         [0, 0, 0, 1, 1, 1],
         [0, 0, 0, 1, 1, 1],
         [0, 0, 0, 1, 1, 1],
         [0, 0, 0, 1, 1, 1]],
        [[0, 0, 1, 1, 1, 1],
         [0, 0, 1, 1, 1, 1],
         [0, 0, 1, 1, 1, 1],
         [0, 0, 1, 1, 1, 1],
         [0, 0, 1, 1, 1, 1],
         [0, 0, 1, 1, 1, 1]]], dtype=torch.uint8)