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Hi, I think this may be related to the pre-trained model used. (I used celeba256_250000.pt)
When I change learn_sigma in .yml from True to False, it will prompt:
RuntimeError: Error(s) in loading state_dict for UNetModel:
size mismatch for out.2.weight: copying a param with shape torch.Size([6, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([3, 256, 3, 3]).
size mismatch for out.2.bias: copying a param with shape torch.Size([6]) from checkpoint, the shape in current model is torch.Size([3]).
And I noticed that in the create_model function in ./guided_diffusion/script_util.py, where the value is returned , It is as follows:
return UNetModel(
image_size=image_size,
in_channels=3,
model_channels=num_channels,
out_channels=(3 if not learn_sigma else 6), ## here!
num_res_blocks=num_res_blocks,
... ...
According to this line:
RePaint/guided_diffusion/gaussian_diffusion.py
Line 239 in 8e2a055
I think the lean_sigma argument must be True.
If that is true, please mention this!
Thank
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