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Remove small_conv_module and make nonlin_attention_module slightly wider

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This commit is contained in:
Daniel Povey 2023-02-08 13:56:22 +08:00
parent 80b2c751e3
commit 659ca97001
1 changed files with 1 additions and 11 deletions
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12
egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
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@ -439,7 +439,6 @@ class ZipformerEncoderLayer(nn.Module):
# to work correctly.
layer_skip_rate: FloatLike = ScheduledFloat((0.0, 0.5), (4000.0, 0.05), default=0),
attention_skip_rate: FloatLike = ScheduledFloat((0.0, 0.2), (4000.0, 0.05), (16000, 0.0), default=0),
small_conv_skip_rate: FloatLike = ScheduledFloat((0.0, 0.5), (4000.0, 0.2), (16000, 0.1), default=0),
conv_skip_rate: FloatLike = ScheduledFloat((0.0, 0.2), (4000.0, 0.05), (16000, 0.0), default=0),
const_attention_rate: FloatLike = ScheduledFloat((0.0, 0.25), (4000.0, 0.025), default=0),
ff2_skip_rate: FloatLike = 0.01,
@ -457,10 +456,6 @@ class ZipformerEncoderLayer(nn.Module):
# contributing too much early on.
self.conv_skip_rate = copy.deepcopy(conv_skip_rate)
# skip rate for small_conv_module; it is fairly high and remains nonzero
# because we don't want this submodule to contribute too much.
self.small_conv_skip_rate = copy.deepcopy(small_conv_skip_rate)
# ff2_skip_rate is to prevent the ff2 module from having output that's too big
# compared to its residual.
self.ff2_skip_rate = copy.deepcopy(ff2_skip_rate)
@ -489,9 +484,7 @@ class ZipformerEncoderLayer(nn.Module):
dropout)
self.nonlin_attention = NonlinAttention(embed_dim,
hidden_channels=embed_dim // 2)
self.small_conv_module = SmallConvolutionModule(embed_dim)
hidden_channels=3 * embed_dim // 4)
self.conv_module = ConvolutionModule(embed_dim,
cnn_module_kernel)
@ -637,9 +630,6 @@ class ZipformerEncoderLayer(nn.Module):
selected_attn_weights[0:1]))
if torch.jit.is_scripting() or random.random() >= float(self.small_conv_skip_rate):
src = src + self.small_conv_module(src, src_key_padding_mask=src_key_padding_mask)
src = src + self.feed_forward1(src)
## pooling module