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Initial drafts/work on bidirectional conformer

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Daniel Povey 2021-09-17 13:47:54 +08:00
parent 2b0370eb18
commit cfdfcf657d
2 changed files with 883 additions and 95 deletions
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974
egs/librispeech/ASR/conformer_ctc_bn_2d/conformer.py
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4
egs/librispeech/ASR/conformer_ctc_bn_2d/transformer.py
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@ -939,7 +939,7 @@ def decoder_padding_mask(
return ys_mask return ys_mask
def generate_square_subsequent_mask(sz: int) -> torch.Tensor: def generate_square_subsequent_mask(sz: int, device: torch.device = torch.device('cpu')) -> torch.Tensor:
"""Generate a square mask for the sequence. The masked positions are """Generate a square mask for the sequence. The masked positions are
filled with float('-inf'). Unmasked positions are filled with float(0.0). filled with float('-inf'). Unmasked positions are filled with float(0.0).
The mask can be used for masked self-attention. The mask can be used for masked self-attention.
@ -956,7 +956,7 @@ def generate_square_subsequent_mask(sz: int) -> torch.Tensor:
Returns: Returns:
A square mask of dimension (sz, sz) A square mask of dimension (sz, sz)
""" """
mask = (torch.triu(torch.ones(sz, sz)) == 1).transpose(0, 1) mask = (torch.triu(torch.ones(sz, sz, device=device)) == 1).transpose(0, 1)
mask = ( mask = (
mask.float() mask.float()
.masked_fill(mask == 0, float("-inf")) .masked_fill(mask == 0, float("-inf"))