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fix self conditioning shape in diffusion prior

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This commit is contained in:
Phil Wang
2022-08-12 12:30:03 -07:00
parent 9440411954
commit 05192ffac4
2 changed files with 3 additions and 3 deletions
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4
dalle2_pytorch/dalle2_pytorch.py
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@@ -1004,9 +1004,9 @@ class DiffusionPriorNetwork(nn.Module):
# setup self conditioning
self_cond = None
if self.self_cond:
self_cond = default(self_cond, lambda: torch.zeros(batch, 1, self.dim, device = device, dtype = dtype))
self_cond = default(self_cond, lambda: torch.zeros(batch, self.dim, device = device, dtype = dtype))
self_cond = rearrange(self_cond, 'b d -> b 1 d')
# in section 2.2, last paragraph
# "... consisting of encoded text, CLIP text embedding, diffusion timestep embedding, noised CLIP image embedding, final embedding for prediction"

2
dalle2_pytorch/version.py
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@@ -1 +1 @@
__version__ = '1.6.1'
__version__ = '1.6.3'