Use non-uniform noise in diffusion_tts6
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@ -381,7 +381,7 @@ class DiffusionTts(nn.Module):
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assert lr_input is not None
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if self.super_sampling_max_noising_factor > 0:
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noising_factor = random.uniform(0,self.super_sampling_max_noising_factor)
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lr_input = torch.rand_like(lr_input) * noising_factor + lr_input
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lr_input = torch.randn_like(lr_input) * noising_factor + lr_input
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lr_input = F.interpolate(lr_input, size=(x.shape[-1],), mode='nearest')
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x = torch.cat([x, lr_input], dim=1)
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