deepgeek/CosyVoice
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add cosyvoice2

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lyuxiang.lx
2024-12-11 16:14:19 +08:00
parent cde3cec6fa
commit 3e381002d7
9 changed files with 484 additions and 32 deletions
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14
cosyvoice/transformer/encoder_layer.py
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@@ -49,8 +49,8 @@ class TransformerEncoderLayer(nn.Module):
super().__init__()
self.self_attn = self_attn
self.feed_forward = feed_forward
self.norm1 = nn.LayerNorm(size, eps=1e-5)
self.norm2 = nn.LayerNorm(size, eps=1e-5)
self.norm1 = nn.LayerNorm(size, eps=1e-12)
self.norm2 = nn.LayerNorm(size, eps=1e-12)
self.dropout = nn.Dropout(dropout_rate)
self.size = size
self.normalize_before = normalize_before
@@ -142,17 +142,17 @@ class ConformerEncoderLayer(nn.Module):
self.feed_forward = feed_forward
self.feed_forward_macaron = feed_forward_macaron
self.conv_module = conv_module
self.norm_ff = nn.LayerNorm(size, eps=1e-5) # for the FNN module
self.norm_mha = nn.LayerNorm(size, eps=1e-5) # for the MHA module
self.norm_ff = nn.LayerNorm(size, eps=1e-12) # for the FNN module
self.norm_mha = nn.LayerNorm(size, eps=1e-12) # for the MHA module
if feed_forward_macaron is not None:
self.norm_ff_macaron = nn.LayerNorm(size, eps=1e-5)
self.norm_ff_macaron = nn.LayerNorm(size, eps=1e-12)
self.ff_scale = 0.5
else:
self.ff_scale = 1.0
if self.conv_module is not None:
self.norm_conv = nn.LayerNorm(size, eps=1e-5) # for the CNN module
self.norm_conv = nn.LayerNorm(size, eps=1e-12) # for the CNN module
self.norm_final = nn.LayerNorm(
size, eps=1e-5) # for the final output of the block
size, eps=1e-12) # for the final output of the block
self.dropout = nn.Dropout(dropout_rate)
self.size = size
self.normalize_before = normalize_before