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Add time_embed_dim_multiplier

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This commit is contained in:
James Betker 2021-10-26 08:55:55 -06:00
parent ba6e46c02a
commit 43e389aac6
1 changed files with 3 additions and 2 deletions
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codes/models/gpt_voice/unet_diffusion_vocoder_with_ref.py
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@ -90,6 +90,7 @@ class DiffusionVocoderWithRef(nn.Module):
scale_factor=2, scale_factor=2,
conditioning_inputs_provided=True, conditioning_inputs_provided=True,
conditioning_input_dim=80, conditioning_input_dim=80,
time_embed_dim_multiplier=4,
): ):
super().__init__() super().__init__()
@ -111,7 +112,7 @@ class DiffusionVocoderWithRef(nn.Module):
padding = 1 if kernel_size == 3 else 2 padding = 1 if kernel_size == 3 else 2
time_embed_dim = model_channels * 4 time_embed_dim = model_channels * time_embed_dim_multiplier
self.time_embed = nn.Sequential( self.time_embed = nn.Sequential(
linear(model_channels, time_embed_dim), linear(model_channels, time_embed_dim),
nn.SiLU(), nn.SiLU(),
@ -332,5 +333,5 @@ if __name__ == '__main__':
spec = torch.randn(2,512,160) spec = torch.randn(2,512,160)
cond = torch.randn(2, 3, 80, 173) cond = torch.randn(2, 3, 80, 173)
ts = torch.LongTensor([555, 556]) ts = torch.LongTensor([555, 556])
model = DiffusionVocoderWithRef(32, conditioning_inputs_provided=True) model = DiffusionVocoderWithRef(32, conditioning_inputs_provided=True, time_embed_dim_multiplier=8)
print(model(clip, ts, spec, cond, 3).shape) print(model(clip, ts, spec, cond, 3).shape)