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Reduce scale from 50 to 20

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This commit is contained in:
Daniel Povey 2022-03-04 15:56:45 +08:00
parent 9cc5999829
commit eb3ed54202
2 changed files with 5 additions and 5 deletions
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4
egs/librispeech/ASR/conformer_ctc/subsampling.py
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@ -48,12 +48,12 @@ class Conv2dSubsampling(nn.Module):
in_channels=1, out_channels=odim, kernel_size=3, stride=2 in_channels=1, out_channels=odim, kernel_size=3, stride=2
), ),
nn.ReLU(), nn.ReLU(),
ExpScale(odim, 1, 1, speed=50.0), ExpScale(odim, 1, 1, speed=20.0),
nn.Conv2d( nn.Conv2d(
in_channels=odim, out_channels=odim, kernel_size=3, stride=2 in_channels=odim, out_channels=odim, kernel_size=3, stride=2
), ),
nn.ReLU(), nn.ReLU(),
ExpScale(odim, 1, 1, speed=50.0), ExpScale(odim, 1, 1, speed=20.0),
) )
self.out = nn.Linear(odim * (((idim - 1) // 2 - 1) // 2), odim) self.out = nn.Linear(odim * (((idim - 1) // 2 - 1) // 2), odim)
self.out_norm = nn.LayerNorm(odim, elementwise_affine=False) self.out_norm = nn.LayerNorm(odim, elementwise_affine=False)

6
egs/librispeech/ASR/transducer_stateless/conformer.py
View File

@ -156,14 +156,14 @@ class ConformerEncoderLayer(nn.Module):
self.feed_forward = nn.Sequential( self.feed_forward = nn.Sequential(
nn.Linear(d_model, dim_feedforward), nn.Linear(d_model, dim_feedforward),
ExpScaleSwish(dim_feedforward, speed=50.0), ExpScaleSwish(dim_feedforward, speed=20.0),
nn.Dropout(dropout), nn.Dropout(dropout),
nn.Linear(dim_feedforward, d_model), nn.Linear(dim_feedforward, d_model),
) )
self.feed_forward_macaron = nn.Sequential( self.feed_forward_macaron = nn.Sequential(
nn.Linear(d_model, dim_feedforward), nn.Linear(d_model, dim_feedforward),
ExpScaleSwish(dim_feedforward, speed=50.0), ExpScaleSwish(dim_feedforward, speed=20.0),
nn.Dropout(dropout), nn.Dropout(dropout),
nn.Linear(dim_feedforward, d_model), nn.Linear(dim_feedforward, d_model),
) )
@ -874,7 +874,7 @@ class ConvolutionModule(nn.Module):
bias=bias, bias=bias,
) )
# shape: (channels, 1), broadcasts with (batch, channel, time). # shape: (channels, 1), broadcasts with (batch, channel, time).
self.activation = ExpScaleSwish(channels, 1, speed=50.0) self.activation = ExpScaleSwish(channels, 1, speed=20.0)
self.pointwise_conv2 = nn.Conv1d( self.pointwise_conv2 = nn.Conv1d(
channels, channels,