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fix self conditioning shape in diffusion prior
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@@ -1004,9 +1004,9 @@ class DiffusionPriorNetwork(nn.Module):
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# setup self conditioning
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# setup self conditioning
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self_cond = None
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if self.self_cond:
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if self.self_cond:
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self_cond = default(self_cond, lambda: torch.zeros(batch, 1, self.dim, device = device, dtype = dtype))
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self_cond = default(self_cond, lambda: torch.zeros(batch, self.dim, device = device, dtype = dtype))
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self_cond = rearrange(self_cond, 'b d -> b 1 d')
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# in section 2.2, last paragraph
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# in section 2.2, last paragraph
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# "... consisting of encoded text, CLIP text embedding, diffusion timestep embedding, noised CLIP image embedding, final embedding for prediction"
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# "... consisting of encoded text, CLIP text embedding, diffusion timestep embedding, noised CLIP image embedding, final embedding for prediction"
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@@ -1 +1 @@
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__version__ = '1.6.1'
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__version__ = '1.6.3'
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