about pretrained mode to finetune

[523997931]

Hello,
I try to use the pretrained model that you provided to finetune, but when I use train script to set the ckpt, it tell me like this:
2021/07/08 20:26:17 File "train.py", line 377, in
Loading model from: /opt/conda/lib/python3.7/site-packages/lpips/weights/v0.1/vgg.pth
182021/07/08 20:26:17 G_A2B.load_state_dict(ckpt['G_A2B'])
192021/07/08 20:26:17 Unexpected key(s) in state_dict: "encoder.stem.5.conv1.0.weight", "encoder.stem.5.conv1.1.bias", "encoder.stem.5.conv2.0.weight", "encoder.stem.5.conv2.1.bias", "encoder.stem.4.skip.0.kernel", "encoder.stem.4.skip.1.weight", "encoder.stem.4.conv2.2.bias", "encoder.stem.4.conv2.0.kernel", "encoder.stem.4.conv2.1.weight", "encoder.style.3.weight", "encoder.style.3.bias", "convs.6.conv.weight", "convs.6.conv.blur.kernel", "convs.6.conv.modulation.weight", "convs.6.conv.modulation.bias", "convs.6.activate.bias", "convs.7.conv.weight", "convs.7.conv.modulation.weight", "convs.7.conv.modulation.bias", "convs.7.activate.bias", "to_rgbs.3.bias", "to_rgbs.3.upsample.kernel", "to_rgbs.3.conv.weight", "to_rgbs.3.conv.modulation.weight", "to_rgbs.3.conv.modulation.bias".
202021/07/08 20:26:17 size mismatch for convs.0.conv.weight: copying a param with shape torch.Size([1, 512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 512, 3, 3]).
212021/07/08 20:26:17 RuntimeError: Error(s) in loading state_dict for Generator:
222021/07/08 20:26:17 size mismatch for encoder.style.4.weight: copying a param with shape torch.Size([8, 512]) from checkpoint, the shape in current model is torch.Size([512, 8192]).
232021/07/08 20:26:17 size mismatch for convs.0.activate.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
242021/07/08 20:26:17 size mismatch for convs.1.conv.modulation.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
252021/07/08 20:26:17 size mismatch for convs.2.conv.modulation.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
262021/07/08 20:26:17 size mismatch for convs.1.conv.modulation.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
272021/07/08 20:26:17 size mismatch for convs.2.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, 128, 256, 3, 3]).
282021/07/08 20:26:17 size mismatch for convs.3.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, 128, 128, 3, 3]).
292021/07/08 20:26:17 size mismatch for convs.2.activate.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
302021/07/08 20:26:17 size mismatch for convs.3.conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
312021/07/08 20:26:17 size mismatch for convs.4.conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
322021/07/08 20:26:17 size mismatch for convs.5.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, 64, 64, 3, 3]).
332021/07/08 20:26:17 size mismatch for convs.5.activate.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
342021/07/08 20:26:17 size mismatch for convs.3.activate.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
352021/07/08 20:26:17 size mismatch for to_rgbs.0.conv.weight: copying a param with shape torch.Size([1, 3, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 256, 1, 1]).
362021/07/08 20:26:17 size mismatch for convs.5.conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([64, 512]).
372021/07/08 20:26:17 size mismatch for convs.4.conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
382021/07/08 20:26:17 size mismatch for to_rgbs.1.conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
392021/07/08 20:26:17 size mismatch for to_rgbs.0.conv.modulation.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
402021/07/08 20:26:17 size mismatch for to_rgbs.2.conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
412021/07/08 20:26:17 size mismatch for to_rgbs.1.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, 128, 1, 1]).
422021/07/08 20:26:17 size mismatch for to_rgbs.2.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, 64, 1, 1]).
432021/07/08 20:26:17 size mismatch for convs.2.conv.modulation.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
442021/07/08 20:26:17 category=DeprecationWarning,
452021/07/08 20:26:17 Missing key(s) in state_dict: "encoder.stem.4.conv2.0.weight", "encoder.stem.4.conv2.1.bias", "encoder.style.2.0.kernel", "encoder.style.2.1.weight", "encoder.style.2.2.bias", "encoder.style.5.weight", "encoder.style.5.bias".
462021/07/08 20:26:17 size mismatch for convs.3.conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
472021/07/08 20:26:17 size mismatch for convs.4.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, 64, 128, 3, 3]).
482021/07/08 20:26:17 size mismatch for convs.1.conv.weight: copying a param with shape torch.Size([1, 512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 256, 3, 3]).
492021/07/08 20:26:17 size mismatch for convs.1.activate.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
502021/07/08 20:26:17 size mismatch for to_rgbs.1.conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
512021/07/08 20:26:17 size mismatch for to_rgbs.2.conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([64, 512]).
522021/07/08 20:26:17 File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1045, in load_state_dict
532021/07/08 20:26:17 size mismatch for to_rgbs.0.conv.modulation.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
542021/07/08 20:26:17 Traceback (most recent call last):
552021/07/08 20:26:17 size mismatch for encoder.style.4.bias: copying a param with shape torch.Size([8]) from checkpoint, the shape in current model is torch.Size([512]).
562021/07/08 20:26:17 size mismatch for convs.4.activate.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
572021/07/08 20:26:17 size mismatch for convs.5.conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
how can i fix this? maybe strict=False?

[mchong6]

Try setting num_down=4