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do not noise for the last step in ddim

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Phil Wang
2022-07-09 18:38:40 -07:00
parent 4878762627
commit a598820012
2 changed files with 5 additions and 4 deletions
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7
dalle2_pytorch/dalle2_pytorch.py
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@@ -1059,10 +1059,10 @@ class DiffusionPrior(nn.Module):
c1 = eta * ((1 - alpha / alpha_next) * (1 - alpha_next) / (1 - alpha)).sqrt() c1 = eta * ((1 - alpha / alpha_next) * (1 - alpha_next) / (1 - alpha)).sqrt()
c2 = ((1 - alpha_next) - torch.square(c1)).sqrt() c2 = ((1 - alpha_next) - torch.square(c1)).sqrt()
new_noise = torch.randn_like(image_embed) noise = torch.randn_like(image_embed) if time_next > 0 else 0.
img = x_start * alpha_next.sqrt() + \ img = x_start * alpha_next.sqrt() + \
c1 * new_noise + \ c1 * noise + \
c2 * pred_noise c2 * pred_noise
return image_embed return image_embed
@@ -2275,9 +2275,10 @@ class Decoder(nn.Module):
c1 = eta * ((1 - alpha / alpha_next) * (1 - alpha_next) / (1 - alpha)).sqrt() c1 = eta * ((1 - alpha / alpha_next) * (1 - alpha_next) / (1 - alpha)).sqrt()
c2 = ((1 - alpha_next) - torch.square(c1)).sqrt() c2 = ((1 - alpha_next) - torch.square(c1)).sqrt()
noise = torch.randn_like(img) if time_next > 0 else 0.
img = x_start * alpha_next.sqrt() + \ img = x_start * alpha_next.sqrt() + \
c1 * torch.randn_like(img) + \ c1 * noise + \
c2 * pred_noise c2 * pred_noise
img = self.unnormalize_img(img) img = self.unnormalize_img(img)

2
dalle2_pytorch/version.py
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@@ -1 +1 @@
__version__ = '0.19.3' __version__ = '0.19.4'