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Add BasicNorm on output of Conv2dSubsampling module

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This commit is contained in:
Daniel Povey 2022-12-20 15:00:01 +08:00
parent d2b272ab50
commit f59697555f
1 changed files with 2 additions and 0 deletions
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egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
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@ -1821,6 +1821,7 @@ class Conv2dSubsampling(nn.Module):
self.out = nn.Linear(out_height * layer3_channels, out_channels) self.out = nn.Linear(out_height * layer3_channels, out_channels)
self.out_norm = BasicNorm(out_channels, channel_dim=-1)
self.dropout = Dropout2(dropout) self.dropout = Dropout2(dropout)
@ -1856,6 +1857,7 @@ class Conv2dSubsampling(nn.Module):
max=float(self.scale_max)) max=float(self.scale_max))
x = self.out(x) x = self.out(x)
x = self.out_norm(x)
# Now x is of shape (N, ((T-1)//2 - 1))//2, odim) # Now x is of shape (N, ((T-1)//2 - 1))//2, odim)
x = self.dropout(x) x = self.dropout(x)
return x return x