Size mismatch error

[nightrain-vampire]

When I load weight from genforce format, it reports error as follow:

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? 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?? Can anyone tell me what happens? Thank you very much!