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use gelu act

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This commit is contained in:
James Betker 2022-05-18 09:34:01 -06:00
parent b2b37453df
commit 208a703080
1 changed files with 3 additions and 3 deletions
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codes/models/audio/mel2vec.py
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@ -365,11 +365,11 @@ class Mel2Vec(nn.Module):
super().__init__() super().__init__()
self.input_blocks = nn.Sequential(nn.Conv1d(mel_input_channels, inner_dim//2, kernel_size=5, padding=2, stride=2), self.input_blocks = nn.Sequential(nn.Conv1d(mel_input_channels, inner_dim//2, kernel_size=5, padding=2, stride=2),
nn.GroupNorm(num_groups=8, num_channels=inner_dim//2, affine=True), nn.GroupNorm(num_groups=8, num_channels=inner_dim//2, affine=True),
nn.SiLU(), nn.GELU(),
nn.Conv1d(inner_dim//2, inner_dim, kernel_size=3, padding=1, stride=2), nn.Conv1d(inner_dim//2, inner_dim, kernel_size=3, padding=1, stride=2),
nn.SiLU(), nn.GELU(),
nn.Conv1d(inner_dim, inner_dim, kernel_size=3, padding=1), nn.Conv1d(inner_dim, inner_dim, kernel_size=3, padding=1),
nn.SiLU(), nn.GELU(),
) )
self.projector = Mel2Vec2FeatureProjection(inner_dim, dropout) self.projector = Mel2Vec2FeatureProjection(inner_dim, dropout)
self.masked_spec_embed = nn.Parameter(torch.rand(inner_dim,)) self.masked_spec_embed = nn.Parameter(torch.rand(inner_dim,))