aljaz/DALLE2-pytorch
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revert restriction for classifier free guidance for diffusion prior, given @crowsonkb advice

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Phil Wang
2022-05-07 20:55:31 -07:00
parent 2eac7996fa
commit dde51fd362
2 changed files with 2 additions and 2 deletions
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dalle2_pytorch/dalle2_pytorch.py
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@@ -834,7 +834,7 @@ class DiffusionPrior(BaseGaussianDiffusion):
self.image_embed_dim = default(image_embed_dim, lambda: clip.dim_latent) self.image_embed_dim = default(image_embed_dim, lambda: clip.dim_latent)
self.channels = default(image_channels, lambda: clip.image_channels) self.channels = default(image_channels, lambda: clip.image_channels)
self.cond_drop_prob = cond_drop_prob if not predict_x_start else 0. self.cond_drop_prob = cond_drop_prob
self.condition_on_text_encodings = condition_on_text_encodings self.condition_on_text_encodings = condition_on_text_encodings
# in paper, they do not predict the noise, but predict x0 directly for image embedding, claiming empirically better results. I'll just offer both. # in paper, they do not predict the noise, but predict x0 directly for image embedding, claiming empirically better results. I'll just offer both.

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setup.py
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@@ -10,7 +10,7 @@ setup(
'dream = dalle2_pytorch.cli:dream' 'dream = dalle2_pytorch.cli:dream'
], ],
}, },
version = '0.1.9', version = '0.1.10',
license='MIT', license='MIT',
description = 'DALL-E 2', description = 'DALL-E 2',
author = 'Phil Wang', author = 'Phil Wang',