RuntimeError: Error(s) in loading state_dict for StyleGAN2Generator:
size mismatch for synthesis.layer7.weight: copying a param with shape torch.Size([256, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
size mismatch for synthesis.layer7.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for synthesis.layer8.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
size mismatch for synthesis.layer8.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for synthesis.layer8.style.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
size mismatch for synthesis.layer8.style.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for synthesis.output4.weight: copying a param with shape torch.Size([3, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 512, 1, 1]).
size mismatch for synthesis.output4.style.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
size mismatch for synthesis.output4.style.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for synthesis.layer9.weight: copying a param with shape torch.Size([128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 512, 3, 3]).
size mismatch for synthesis.layer9.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for synthesis.layer9.style.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
size mismatch for synthesis.layer9.style.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for synthesis.layer10.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for synthesis.layer10.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for synthesis.layer10.style.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
size mismatch for synthesis.layer10.style.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for synthesis.output5.weight: copying a param with shape torch.Size([3, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 256, 1, 1]).
size mismatch for synthesis.output5.style.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
size mismatch for synthesis.output5.style.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for synthesis.layer11.weight: copying a param with shape torch.Size([64, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]).
size mismatch for synthesis.layer11.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for synthesis.layer11.style.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
size mismatch for synthesis.layer11.style.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for synthesis.layer12.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for synthesis.layer12.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for synthesis.layer12.style.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
size mismatch for synthesis.layer12.style.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for synthesis.output6.weight: copying a param with shape torch.Size([3, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 128, 1, 1]).
size mismatch for synthesis.output6.style.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
size mismatch for synthesis.output6.style.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
After I check the stylegan2_generator.py, I found that the default value of 'fmaps_base' is said to be 16 << 10, but actually it is 32 << 10 in the python code. When I change the 'fmaps_base' into 16 << 10, the code works?
![image](https://private-user-images.githubusercontent.com/68332728/319027955-f5fa8b8f-edf2-40bc-b568-a24d99357989.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.XvIL4dUvQHuilV-hvHDo0cNcp6ov6jb54eDzIBhCvvQ)
However, in the genforce (where I obtain the model weight), the 'fmaps_base' is 32 << 10! It seems that the same parameter does not work for the same model??
![image](https://private-user-images.githubusercontent.com/68332728/319028262-27d60b9b-f9b5-4548-99ea-4e97432fd077.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.WwbvObnoR4yjKnsk8yk34lt0APpN0fYB_J0h-DMKsX0)
Can anyone tell me what happens? Thank you very much!