Was the convert_weights file ever made compatible with ada-pytorch versions of StyleGAN2?

[Pizzawookiee]

No description provided.

[snow1929]

@rosinality
I face the same problem.
I train the model by stylegan2-ada-pytorch. <-----------256x256 img
Then try to convert pkl to pt by convert_weight.py with channel_multiplier value "2"
there is an error happended.

python convert_weight.py --repo /mnt/stylegan2-ada --gen --channel_multiplier 2 /mnt/StyleGAN-nada/models/mydataset-network-snapshot-003000.pkl
Traceback (most recent call last):
  File "convert_weight.py", line 248, in <module>
    state_dict = fill_statedict(state_dict, g_ema.vars, size, n_mlp)
  File "convert_weight.py", line 161, in fill_statedict
    convert_torgb(vars, f"G_synthesis/{reso}x{reso}/ToRGB", f"to_rgbs.{i}"),
  File "convert_weight.py", line 101, in update
    raise ValueError(f"Shape mismatch: {v.shape} vs {state_dict[k].shape}")
ValueError: Shape mismatch: torch.Size([1, 3, 256, 1, 1]) vs torch.Size([1, 3, 512, 1, 1])

And I can get the pt file with channel_multiplier value "1".
but this file cannot be used for training e4e model

RuntimeError: Error(s) in loading state_dict for Generator:
        size mismatch for convs.6.conv.weight: copying a param with shape torch.Size([1, 256, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 512, 512, 3, 3]).
        size mismatch for convs.6.activate.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for convs.7.conv.weight: copying a param with shape torch.Size([1, 256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 512, 512, 3, 3]).
        size mismatch for convs.7.conv.modulation.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 convs.7.conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for convs.7.activate.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for convs.8.conv.weight: copying a param with shape torch.Size([1, 128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 512, 3, 3]).
        size mismatch for convs.8.conv.modulation.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 convs.8.conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for convs.8.activate.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for convs.9.conv.weight: copying a param with shape torch.Size([1, 128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 256, 3, 3]).
        size mismatch for convs.9.conv.modulation.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 convs.9.conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for convs.9.activate.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for convs.10.conv.weight: copying a param with shape torch.Size([1, 64, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 128, 256, 3, 3]).
        size mismatch for convs.10.conv.modulation.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 convs.10.conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for convs.10.activate.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for convs.11.conv.weight: copying a param with shape torch.Size([1, 64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 128, 128, 3, 3]).
        size mismatch for convs.11.conv.modulation.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 convs.11.conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for convs.11.activate.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for to_rgbs.3.conv.weight: copying a param with shape torch.Size([1, 3, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 512, 1, 1]).
        size mismatch for to_rgbs.3.conv.modulation.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 to_rgbs.3.conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for to_rgbs.4.conv.weight: copying a param with shape torch.Size([1, 3, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 256, 1, 1]).
        size mismatch for to_rgbs.4.conv.modulation.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 to_rgbs.4.conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for to_rgbs.5.conv.weight: copying a param with shape torch.Size([1, 3, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 128, 1, 1]).
        size mismatch for to_rgbs.5.conv.modulation.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 to_rgbs.5.conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).

[Pizzawookiee]

Will confirm that I have the same issue as @snow1929 is describing. Tried using the modified convert_weight file on https://github.com/senior-sigan/rosinality-stylegan2-pytorch-cpu with no success.

[LeandreSassi]

Im running into the same problem. Did someone get how to fix it?