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dohe0342 2023-01-04 23:25:50 +09:00
parent 16972b56a7
commit 807139dfad
4 changed files with 2 additions and 5 deletions
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egs/librispeech/ASR/pruned_transducer_stateless5/.conformer.py.swp Normal file
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egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py
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@ -695,8 +695,6 @@ class ConformerEncoder(nn.Module):
outputs = [] outputs = []
layer_output = []
for i, mod in enumerate(self.layers): for i, mod in enumerate(self.layers):
output = mod( output = mod(
output, output,
@ -708,11 +706,9 @@ class ConformerEncoder(nn.Module):
if i in self.aux_layers: if i in self.aux_layers:
outputs.append(output) outputs.append(output)
layer_output.append(output)
output = self.combiner(outputs) output = self.combiner(outputs)
return output, layer_output return output
@torch.jit.export @torch.jit.export
def chunk_forward( def chunk_forward(

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egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp
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egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py
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@ -204,6 +204,7 @@ class Conformer(EncoderInterface):
x = x.permute(1, 0, 2) # (T, N, C) ->(N, T, C) x = x.permute(1, 0, 2) # (T, N, C) ->(N, T, C)
layer_output = [x.permute(1, 0, 2) for x in layer_output] layer_output = [x.permute(1, 0, 2) for x in layer_output]
x = self.layer_norm(1/6*(self.sigmoid(self.alpha[0])*layer_output[2] + \ x = self.layer_norm(1/6*(self.sigmoid(self.alpha[0])*layer_output[2] + \
self.sigmoid(self.alpha[1])*layer_output[5] + \ self.sigmoid(self.alpha[1])*layer_output[5] + \
self.sigmoid(self.alpha[2])*layer_output[8] + \ self.sigmoid(self.alpha[2])*layer_output[8] + \